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Recommender systems (RSs) have emerged as very useful tools to help customers with their decision-making process, find items of their interest, and alleviate the information overload problem.
Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations (2019)
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G. Salton · 1989
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Using collaborative filtering to weave an information tapestry
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Corpora as expert knowledge domains: the oxford advanced learner’s dictionary
E. Wilson · 1993
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Grouplens: An open architecture for collaborative filtering of netnews
P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl · 1994
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Disseminating active map information to mobile hosts
B. N. Schilit and M. M. Theimer · 1994
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Letizia: An agent that assists web browsing
H. Lieberman · 1995
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Social information filtering: Algorithms for automating ”word of mouth”
U. Shardanand and P. Maes · 1995
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Mining sequential patterns
R. Agrawal and R. Srikant · 1995
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The influence of the sigmoid function parameters on the speed of backpropagation learning
J. Han and C. Moraga · 1995
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Toward a new generation of personality theories: Theoretical contexts for the five-factor model
P. Costa and R. McCrae · 1996
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Content-based, collaborative recommendation
M. Balabanovic and Y. Shoham · 1997
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Recommendation as classification: Using social and content-based information in recommendation
C. Basu, H. Hirsh, and W. W. Cohen · 1998
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Empirical analysis of predictive algorithms for collaborative filtering
J. S. Breese, D. Heckerman, and C. M. Kadie · 1998
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Clustering methods for collaborative filtering (1998)
L. H. Ungar and D. Foster · 1998
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Learning collaborative information filters
D. Billsus and M. J. Pazzani · 1998
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Concept features in re:agent, an intelligent email agent
G. Boone · 1998
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Citeseer: An autonomous web agent for automatic retrieval and identification of interesting publications
G. Boone · 1998
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Gradient-based learning applied to document recognition
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Principles of forecasting - A short overview
E. Pelikán · 1999
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A framework for collaborative, content-based and demographic filtering
M. J. Pazzani · 1999
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Modern Information Retrieval (ACM Press / Addison-Wesley, 1999)
R. A. Baeza-Yates and B. A. Ribeiro-Neto · 1999
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Combining content-based and collaborative filters in an online newspaper
M. Claypool, A. Gokhale, T. Miranda, D. N. P. Murnikov, , and M. Sartin · 1999
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An algorithmic framework for performing collaborative filtering
J. L. Herlocker, J. A. Konstan, A. Borchers, and J. Riedl · 1999
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Combining collaborative filtering with personal agents for better recommendations
N. Good, J. B. Schafer, J. A. Konstan, A. Borchers, B. M. Sarwar, J. L. Herlocker, and J. Riedl · 1999
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Bayesian mixed-effects models for recommender systems (1999)
M. Condliff, D. Lewis, D. Madigan, and T. Inc · 1999
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Using association rules for product assortment decisions: A case study
T. Brijs, G. Swinnen, K. Vanhoof, and G. Wets · 1999
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Linguistic styles: Language use as an individual difference
J. Pennebaker and L. King · 1999
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Combining content-based and collaborative filters in an online newspaper
M. Claypool, A. Gokhale, T. Miranda, P. Murnikov, D. Netes, and M. Sartin · 1999
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Towards a better understanding of context and context-awareness
G. D. Abowd, A. K. Dey, P. J. Brown, N. Davies, M. Smith, and P. Steggles · 1999
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Collaborative filtering with the simple bayesian classifier
K. Miyahara and M. J. Pazzani · 2000
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Visualization of navigation patterns on a web site using model-based clustering
I. V. Cadez, D. Heckerman, C. Meek, P. Smyth, and S. White · 2000
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Data Mining: Concepts and Techniques (Morgan Kaufmann, 2000)
J. Han and M. Kamber · 2000
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Analysis of recommendation algorithms for e-commerce
B. M. Sarwar, G. Karypis, J. A. Konstan, and J. Riedl · 2000
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Out of context: Computer systems that adapt to, and learn from, context
H. Lieberman and T. Selker · 2000
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Hybrid recommender systems for electronic commerce
T. T. Tran and R. Cohen · 2000
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PTV: intelligent personalised TV guides
P. Cotter and B. Smyth · 2000
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Internet recommendation systems
A. Ansari, S. Essegaier, and R. Kohli · 2000
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User modeling for adaptive news access
D. Billsus and M. J. Pazzani · 2000
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Rectree: An efficient collaborative filtering method
S. H. S. Chee, J. Han, and K. Wang · 2001
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Modern information retrieval: A brief overview
A. Singhal · 2001
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Using temporal data for making recommendations
A. Zimdars, D. M. Chickering, and C. Meek · 2001
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Personality
D. Funder · 2001
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Effective personalization based on association rule discovery from web usage data
B. Mobasher, H. Dai, T. Luo, and M. Nakagawa · 2001
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Item-based collaborative filtering recommendation algorithms
B. M. Sarwar, G. Karypis, J. A. Konstan, and J. Riedl · 2001
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Efficient adaptive-support association rule mining for recommender systems
W. Lin, S. A. Alvarez, and C. Ruiz · 2002
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Hybrid recommender systems: Survey and experiments
R. D. Burke · 2002
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Content-boosted collaborative filtering for improved recommendations
P. Melville, R. J. Mooney, and R. Nagarajan · 2002
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A hybrid recommender system combining collaborative filtering with neural network
M. Lee, P. Choi, and Y. Woo · 2002
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Mining frequent sequential patterns under a similarity constraint
M. Capelle, C. Masson, and J. Boulicaut · 2002
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Amazon.com recommendations: Item-to-item collaborative filtering
G. Linden, B. Smith, and J. York · 2003
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Intimate:a web-based movie recommender using text categorization
H. Mak, I. Koprinska, and J. Poon · 2003
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Flexible mixture model for collaborative filtering
L. Si and R. Jin · 2003
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The do re mi’s of everyday life: The structure and personality correlates of music preferences
e. a. Peter J. Rentfrow, Samuel D. Gosling · 2003
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Latent dirichlet allocation
D. M. Blei, A. Y. Ng, and M. I. Jordan · 2003
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Probabilistic memory-based collaborative filtering
K. Yu, A. Schwaighofer, V. Tresp, X. Xu, and H. Kriegel · 2004
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Latent semantic models for collaborative filtering
T. Hofmann · 2004
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Evaluating collaborative filtering recommender systems
J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. Riedl · 2004
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Survey for trust-aware recommender systems: A deep learning perspective (2020)
M. Dong, F. Yuan, L. Yao, X. Wang, X. Xu, and L. Zhu · 2004
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Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
G. Adomavicius and A. Tuzhilin · 2005
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Fast maximum margin matrix factorization for collaborative prediction
J. D. M. Rennie and N. Srebro · 2005
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Incorporating contextual information in recommender systems using a multidimensional approach
G. Adomavicius, R. Sankaranarayanan, S. Sen, and A. Tuzhilin · 2005
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Attitudes, personality, and behavior
I. Ajzen · 2005
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Web path recommendations based on page ranking and markov models
M. Eirinaki, M. Vazirgiannis, and D. Kapogiannis · 2005
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Foafing the music: A music recommendation system based on RSS feeds and user preferences
Ò. Celma, M. Ramírez, and P. Herrera · 2005
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An mdp-based recommender system
G. Shani, D. Heckerman, and R. I. Brafman · 2005
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Computing and Applying Trust in Web-based Social Networks
J. Golbeck · 2005
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A hybrid movie recommender system based on neural networks
C. Christakou and A. Stafylopatis · 2005
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Collaborative filtering for multi-class data using belief nets algorithms
X. Su and T. M. Khoshgoftaar · 2006
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Being accurate is not enough: how accuracy metrics have hurt recommender systems
S. M. McNee, J. Riedl, and J. A. Konstan · 2006
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Using sequential pattern mining for links recommendation in adaptive hypermedia educational systems
C. R. Morales, A. P. Pérez, S. V. Soto, C. H. Martınez, and A. Zafra · 2006
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Foafing the music: Bridging the semantic gap in music recommendation
Ò. Celma · 2006
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Merriam-webster
M. Webster · 2006
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Inverted files for text search engines
J. Zobel and A. Moffat · 2006
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Using sequential pattern mining for links recommendation in adaptive hypermedia educational systems (2006)
C. Romero, A. Pérez, S. Ventura, C. Martínez, and A. Zafra · 2006
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Efficient sequential access pattern mining for web recommendations
B. Zhou, S. C. Hui, and A. C. M. Fong · 2006
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Incorporating pageview weight into an association-rule-based web recommendation system
L. Yan and C. Li · 2006
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An introduction to ROC analysis
T. Fawcett · 2006
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Using linguistic cues for the automatic recognition of personality in conversation and text
F. Mairesse, M. A. Walker, M. R. Mehl, and R. K. Moore · 2007
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Development and psychometric properties of liwc
J. Pennebaker, C. Chung, and M. Ireland · 2007
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Building personalized recommendation system in e-commerce using association rule-based mining and classification
X. Zhang · 2007
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A content-collaborative recommender that exploits wordnet-based user profiles for neighborhood formation
M. Degemmis, P. Lops, and G. Semeraro · 2007
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Trust-aware recommender systems
P. Massa and P. Avesani · 2007
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Restricted boltzmann machines for collaborative filtering
R. Salakhutdinov, A. Mnih, and G. E. Hinton · 2007
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A hybrid ga-based collaborative filtering model for online recommenders
Y. Ho, S. Fong, and Z. Yan · 2007
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Mining frequent ordered patterns without candidate generation
C. Ji and Z. Deng · 2007
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Efficient hybrid web recommendations based on markov clickstream models and implicit search
Z. Zhang and O. Nasraoui · 2007
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Content-based recommendation systems
M. J. Pazzani and D. Billsus · 2007
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Probabilistic matrix factorization
R. Salakhutdinov and A. Mnih · 2007
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Discovering and exploiting causal dependencies for robust mobile context-aware recommenders
G. Yap, A. Tan, and H. Pang · 2007
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Integrated personal recommender systems
R. Chung, D. Sundaram, and A. Srinivasan · 2007
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Collaborative filtering for implicit feedback datasets
Y. Hu, Y. Koren, and C. Volinsky · 2008
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Foafing the music: Bridging the semantic gap in music recommendation
Ò. Celma and X. Serra · 2008
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Tag-aware recommender systems by fusion of collaborative filtering algorithms
K. H. L. Tso-Sutter, L. B. Marinho, and L. Schmidt-Thieme · 2008
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Hybrid personalized recommended model based on genetic algorithm
L.Gao and C. Li · 2008
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Fuzzy-genetic approach to recommender systems based on a novel hybrid user model
M. Y. H. Al-Shamri and K. K. Bharadwaj · 2008
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A hybrid recommender approach based on widrow-hoff learning
L. Ren, L. He, J. Gu, W. Xia, and F. Wu · 2008
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A new framework for detecting weighted sequential patterns in large sequence databases
U. Yun · 2008
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A rule-based recommender system for online discussion forums
F. Abel, I. I. Bittencourt, N. Henze, D. Krause, and J. Vassileva · 2008
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Factorization meets the neighborhood: a multifaceted collaborative filtering model
Y. Koren · 2008
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A hybrid approach for movie recommendation
G. Lekakos and P. Caravelas · 2008
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BPR: bayesian personalized ranking from implicit feedback
S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme · 2009
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Personality aware recommendations to groups
J. A. Recio-García, G. Jiménez-Díaz, A. A. Sánchez-Ruiz-Granados, and B. Díaz-Agudo · 2009
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Matrix factorization techniques for recommender systems
Y. Koren, R. M. Bell, and C. Volinsky · 2009
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A survey of collaborative filtering techniques
X. Su and T. M. Khoshgoftaar · 2009
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Regression-based latent factor models
D. Agarwal and B. Chen · 2009
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The five-factor model of personality traits: Consensus and controversy
R. McCrae · 2009
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Personality based user similarity measure for a collaborative recommender system
M. Tkalcic, M. Kunaver, J. Tasic, and A. Kosir · 2009
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Evaluating interface variants on personality acquisition for recommender systems
G. Dunn, J. Wiersema, J. Ham, and L. Aroyo · 2009
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User profiles for personalizing digital libraries
G. Semeraro, P. Basile, M. de Gemmis, and P. Lops · 2009
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Beyond the stars: Exploiting free-text user reviews to improve the accuracy of movie recommendations
N. Jakob, S. Weber, M.-C. Müller, and I. Gurevych · 2009
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Emergence of consensus and shared vocabularies in collaborative tagging systems
V. Robu, H. Halpin, and H. Shepherd · 2009
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Tagommenders: connecting users to items through tags
S. Sen, J. Vig, and J. Riedl · 2009
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Beyond the stars: Exploiting free-text user reviews to improve the accuracy of movie recommendations
N. Jakob, S. Weber, M.-C. Müller, and I. Gurevych · 2009
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On social networks and collaborative recommendation
I. Konstas, V. Stathopoulos, and J. M. Jose · 2009
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Social network analysis for information flow in disconnected delay-tolerant manets
E. M. Daly and M. Haahr · 2009
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TrustWalker : a random walk model for combining trust-based and item-based recommendation
M. Jamali and M. Ester · 2009
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Context-aware systems: A literature review and classification
J. Hong, E. Suh, and S. Kim · 2009
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Towards time-dependant recommendation based on implicit feedback
L. Baltrunas and X. Amatriain · 2009
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Hybrid recommender system using latent features
S. Maneeroj and A. Takasu · 2009
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Handling sequential pattern decay: Developing a two-stage collaborative recommender system
C. Huang and W. Huang · 2009
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Web page personalization based on weighted association rules
R. Forsati, M. R. Meybodi, and A. G. Neiat · 2009
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The cambridge handbook of personality psychology
P. J. Corr and G. Matthews · 2009
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The impact of youtube recommendation system on video views
R. Zhou, S. Khemmarat, and L. Gao · 2010
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Recommender Systems - An Introduction (Cambridge University Press, 2010)
D. Jannach, M. Zanker, A. Felfernig, and G. Friedrich · 2010
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Factorizing personalized markov chains for next-basket recommendation
S. Rendle, C. Freudenthaler, and L. Schmidt-Thieme · 2010
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The youtube video recommendation system
J. Davidson, B. Liebald, J. Liu, P. Nandy, T. V. Vleet, U. Gargi, S. Gupta, Y. He, M. Lambert, B. Livingston, and D. Sampath · 2010
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A group recommendation system for online communities
J. K. Kim, H. K. Kim, H. Y. Oh, and Y. U. Ryu · 2010
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Comparison of implicit and explicit feedback from an online music recommendation service
G. Jawaheer, M. Szomszor, and P. Kostkova · 2010
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You are where you tweet: a content-based approach to geo-locating twitter users
Z. Cheng, J. Caverlee, and K. Lee · 2010
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What is twitter, a social network or a news media?
H. Kwak, C. Lee, H. Park, and S. B. Moon · 2010
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Exploiting contextual information from event logs for personalized recommendation
D. Lee, S. E. Park, M. Kahng, S. Lee, and S. Lee · 2010
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Who watches what? assessing the impact of gender and personality on film preferences (2010)
O. Chausson · 2010
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Organizational behavior
J. Hellriegel Don, Slocum · 2010
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A study on user perception of personality-based recommender systems
R. Hu and P. Pu · 2010
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Combining content-based and collaborative recommendations: A hybrid approach based on bayesian networks
L. M. de Campos, J. M. Fernández-Luna, J. F. Huete, and M. A. Rueda-Morales · 2010
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Recommendations in online discussion forums for e-learning systems
F. Abel, I. I. Bittencourt, E. de Barros Costa, N. Henze, D. Krause, and J. Vassileva · 2010
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Developing a web recommendation system based on closed sequential patterns
U. Niranjan, R. B. V. Subramanyam, and V. Khanaa · 2010
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Developing a web recommendation system based on closed sequential patterns
U. Niranjan, R. B. V. Subramanyam, and V. Khanaa · 2010
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Adaptive subgradient methods for online learning and stochastic optimization
J. C. Duchi, E. Hazan, and Y. Singer · 2010
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Social trust in opportunistic networks
S. Trifunovic, F. Legendre, and C. Anastasiades · 2010
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Social media mobile internet use among teens and young adults
A. Lenhart, K. Purcell, A. Smith, and K. Zickuhr · 2010
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A survey on transfer learning
S. J. Pan and Q. Yang · 2010
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Enhancing collaborative filtering systems with personality information
R. Hu and P. Pu · 2011
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Collaborative topic modeling for recommending scientific articles
C. Wang and D. M. Blei · 2011
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Introduction to Recommender Systems Handbook , pp. 1–35 (Springer US, Boston, MA, 2011)
F. Ricci, L. Rokach, and B. Shapira · 2011
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Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems
F. Cacheda, V. Carneiro, D. Fernández, and V. Formoso · 2011
Cited alongside, same era.
Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy
N. Koenigstein, G. Dror, and Y. Koren · 2011
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Content-based recommender systems: State of the art and trends
P. Lops, M. de Gemmis, and G. Semeraro · 2011
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SLIM: sparse linear methods for top-n recommender systems
X. Ning and G. Karypis · 2011
Cited alongside, same era.
Handling data sparsity in collaborative filtering using emotion and semantic based features
Y. Moshfeghi, B. Piwowarski, and J. M. Jose · 2011
Cited alongside, same era.
Context-aware recommender systems
SCA-CNN: spatial and channel-wise attention in convolutional networks for image captioning
L. Chen and et al · 2016
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Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering
R. He and J. J. McAuley · 2016
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Evaluating prediction accuracy for collaborative filtering algorithms in recommender systems (2016)
Z. S. Patrous and S. Najafi · 2016
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Hotel recommendation system based on review and context information: a collaborative filtering appro
Y. Hu, P. Lee, K. Chen, J. M. Tarn, and D. Dang · 2016
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Capturing semantic correlation for item recommendation in tagging systems
C. Chen, X. Zheng, Y. Wang, F. Hong, and D. Chen · 2016
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G. Adomavicius and A. Tuzhilin · 2011
Cited alongside, same era.
Context-aware recommender systems
G. Adomavicius, B. Mobasher, F. Ricci, and A. Tuzhilin · 2011
Cited alongside, same era.
Falling asleep with angry birds, facebook and kindle: A large scale study on mobile application usage
M. Böhmer, B. Hecht, J. Schöning, A. Krüger, and G. Bauer · 2011
Cited alongside, same era.
Introduction to personality
J. Burger · 2011
Cited alongside, same era.
Our twitter profiles, our selves: Predicting personality with twitter
D. Quercia, M. Kosinski, D. Stillwell, and J. Crowcroft · 2011
Cited alongside, same era.
Listening, watching, and reading: the structure and correlates of entertainment preferences
Z. R. Rentfrow PJ, Goldberg LR · 2011
Cited alongside, same era.
Novelty and diversity in top-n recommendation - analysis and evaluation
N. Hurley and M. Zhang · 2011
Cited alongside, same era.
Fast matrix factorization for online recommendation with implicit feedback
X. He, H. Zhang, M. Kan, and T. Chua · 2016
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Hierarchical attention networks for document classification
Z. Y. et.al · 2016
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Context-aware location recommendation by using a random walk-based approach
H. Bagci and P. Karagoz · 2016
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The contextual turn: from context-aware to context-driven recommender systems
R. Pagano, P. Cremonesi, M. A. Larson, B. Hidasi, D. Tikk, A. Karatzoglou, and M. Quadrana · 2016
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Context-aware sequential recommendation
Q. Liu, S. Wu, D. Wang, Z. Li, and L. Wang · 2016
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Process Analytics - Concepts and Techniques for Querying and Analyzing Process Data (Springer, 2016)
S. Beheshti, B. Benatallah, S. Sakr, D. Grigori, H. R. Motahari-Nezhad, M. C. Barukh, A. Gater, and S. H. Ryu · 2016
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Neural attentive session-based recommendation
J. Li, P. Ren, Z. Chen, Z. Ren, T. Lian, and J. Ma · 2017
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A systematic review and comparative analysis of cross-document coreference resolution methods and tools
S. Beheshti, B. Benatallah, S. Venugopal, S. H. Ryu, H. R. Motahari-Nezhad, and W. Wang · 2017
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On automating basic data curation tasks
S. Beheshti, A. Tabebordbar, B. Benatallah, and R. Nouri · 2017
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Armica-improved: A new approach for association rule mining
S. Yakhchi, S. M. Ghafari, C. Tjortjis, and M. Fazeli · 2017
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Recurrent recommender networks
C. Wu, A. Ahmed, A. Beutel, A. J. Smola, and H. Jing · 2017
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A personality-based recommender system for semantic searches in vehicles sales portals
F. A. P. de Paiva, J. A. F. Costa, and C. R. M. Silva · 2017
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Recurrent neural networks with top-k gains for session-based recommendations
B. Hidasi and A. Karatzoglou · 2017
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Multi-behavioral sequential prediction with recurrent log-bilinear model
Q. Liu, S. Wu, and L. Wang · 2017
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Improving cold start recommendation by mapping feature-based preferences to item comparisons
S. Kalloori and F. Ricci · 2017
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Determining characteristics of successful recommendations from log data: a case study
D. Jannach and M. Ludewig · 2017
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A deep architecture for content-based recommendations exploiting recurrent neural networks
A. Suglia, C. Greco, C. Musto, M. de Gemmis, P. Lops, and G. Semeraro · 2017
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Aggressive, tense or shy? identifying personality traits from crowd videos
A. Bera, T. Randhavane, and D. Manocha · 2017
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What your facebook profile picture reveals about your personality
C. Segalin, F. Celli, L. Polonio, M. Kosinski, D. Stillwell, N. Sebe, M. Cristani, and B. Lepri · 2017
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Joint deep modeling of users and items using reviews for recommendation
L. Zheng, V. Noroozi, and P. S. Yu · 2017
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Neural survival recommender
H. Jing and A. J. Smola · 2017
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Deepfm: A factorization-machine based neural network for CTR prediction
H. Guo, R. Tang, Y. Ye, Z. Li, and X. He · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Interpretable convolutional neural networks with dual local and global attention for review rating prediction
S. Seo, J. Huang, H. Yang, and Y. Liu · 2017
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Attentive collaborative filtering: Multimedia recommendation with item- and component-level attention
J. Chen, H. Zhang, X. He, L. Nie, W. Liu, and T. Chua · 2017
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Dynamic key-value memory networks for knowledge tracing
J. Zhang, X. Shi, I. King, and D. Yeung · 2017
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3d convolutional networks for session-based recommendation with content features
T. X. Tuan and T. M. Phuong · 2017
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Long and short-term recommendations with recurrent neural networks
R. Devooght and H. Bersini · 2017
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Situation recognition with graph neural networks
R. Li, M. Tapaswi, R. Liao, J. Jia, R. Urtasun, and S. Fidler · 2017
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Atrank: An attention-based user behavior modeling framework for recommendation
C. Zhou, J. Bai, J. Song, X. Liu, Z. Zhao, X. Chen, and J. Gao · 2017
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Contextual sequence modeling for recommendation with recurrent neural networks
E. Smirnova and F. Vasile · 2017
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Perceiving the next choice with comprehensive transaction embeddings for online recommendation
S. Wang, L. Hu, and L. Cao · 2017
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Improving session recommendation with recurrent neural networks by exploiting dwell time
A. Dallmann, A. Grimm, C. Pölitz, D. Zoller, and A. Hotho · 2017
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Personalizing session-based recommendations with hierarchical recurrent neural networks
M. Quadrana, A. Karatzoglou, B. Hidasi, and P. Cremonesi · 2017
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Sequential user-based recurrent neural network recommendations
T. Donkers, B. Loepp, and J. Ziegler · 2017
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Show, adapt and tell: Adversarial training of cross-domain image captioner
T. Chen, Y. Liao, C. Chuang, W. T. Hsu, J. Fu, and M. Sun · 2017
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IRGAN: A minimax game for unifying generative and discriminative information retrieval models
J. Wang, L. Yu, W. Zhang, Y. Gong, Y. Xu, B. Wang, P. Zhang, and D. Zhang · 2017
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Diversifying personalized recommendation with user-session context
L. Hu and et al · 2017
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Performance evaluation of recommender systems
M. Chena and P. Liu · 2017
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Effective dependency rule-based aspect extraction for social recommender systems
Y. Y. Chen, N. Wiratunga, and R. Lothian · 2017
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Neural collaborative filtering
X. He and et al · 2017
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Deep matrix factorization models for recommender systems
H. Xue, X. Dai, J. Zhang, S. Huang, and J. Chen · 2017
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A generic coordinate descent framework for learning from implicit feedback
I. Bayer and et al · 2017
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SPMC: socially-aware personalized markov chains for sparse sequential recommendation
C. Cai, R. He, and J. J. McAuley · 2017
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Modeling user session and intent with an attention-based encoder-decoder architecture
P. Loyola, C. Liu, and Y. Hirate · 2017
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Deep learning-based document modeling for personality detection from text
N. Majumder, S. Poria, A. F. Gelbukh, and E. Cambria · 2017
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Interpreting CNN models for apparent personality trait regression
C. Ventura, D. Masip, and À. Lapedriza · 2017
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Coredb: a data lake service
A. Beheshti, B. Benatallah, R. Nouri, V. M. Chhieng, H. Xiong, and X. Zhao · 2017
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Autosvd++: An efficient hybrid collaborative filtering model via contractive auto-encoders
S. Zhang, L. Yao, and X. Xu · 2017
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Contextual sequence modeling for recommendation with recurrent neural networks
E. Smirnova and F. Vasile · 2017
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Personalizing session-based recommendations with hierarchical recurrent neural networks
M. Quadrana, A. Karatzoglou, B. Hidasi, and P. Cremonesi · 2017
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Cross domain recommender systems: A systematic literature review
M. M. Khan, R. Ibrahim, and I. Ghani · 2017
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Personalized top-n sequential recommendation via convolutional sequence embedding
J. Tang and K. Wang · 2018
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Sequential recommender system based on hierarchical attention networks
H. Ying, F. Zhuang, F. Zhang, Y. Liu, G. Xu, X. Xie, H. Xiong, and J. Wu · 2018
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Adaptive rule monitoring system
A. Tabebordbar and A. Beheshti · 2018
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iprocess: Enabling iot platforms in data-driven knowledge-intensive processes
A. Beheshti, F. Schiliro, S. Ghodratnama, F. Amouzgar, B. Benatallah, J. Yang, Q. Z. Sheng, F. Casati, and H. R. Motahari-Nezhad · 2018
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Sequence-aware recommender systems
M. Quadrana, P. Cremonesi, and D. Jannach · 2018
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Learning from history and present: Next-item recommendation via discriminatively exploiting user behaviors
Z. Li, H. Zhao, Q. Liu, Z. Huang, T. Mei, and E. Chen · 2018
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CNR: cross-network recommendation embedding user’s personality
S. Yakhchi, S. M. Ghafari, and A. Beheshti · 2018
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isheets: A spreadsheet-based machine learning development platform for data-driven process analytics
F. Amouzgar, A. Beheshti, S. Ghodratnama, B. Benatallah, J. Yang, and Q. Z. Sheng · 2018
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icop: Iot-enabled policing processes
F. Schiliro, A. Beheshti, S. Ghodratnama, F. Amouzgar, B. Benatallah, J. Yang, Q. Z. Sheng, F. Casati, and H. R. Motahari-Nezhad · 2018
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Crowdcorrect: A curation pipeline for social data cleansing and curation
A. Beheshti, K. Vaghani, B. Benatallah, and A. Tabebordbar · 2018
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Recurrent collaborative filtering for unifying general and sequential recommender
D. Dong, X. Zheng, R. Zhang, and Y. Wang · 2018
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Attention-based transactional context embedding for next-item recommendation
S. Wang, L. Hu, L. Cao, X. Huang, D. Lian, and W. Liu · 2018
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Sequential recommendation with user memory networks
X. Chen, H. Xu, Y. Zhang, J. Tang, Y. Cao, Z. Qin, and H. Zha · 2018
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Personalized top-n sequential recommendation via convolutional sequence embedding
J. Tang and K. Wang · 2018
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Social context-aware trust prediction: Methods for identifying fake news
S. M. Ghafari, S. Yakhchi, A. Beheshti, and M. A. Orgun · 2018
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Recommender systems: A systematic review of the state of the art literature and suggestions for future research
F. Alyari and N. J. Navimipour · 2018
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NAIS: neural attentive item similarity model for recommendation
X. He, Z. He, J. Song, Z. Liu, Y. Jiang, and T. Chua · 2018
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Outer product-based neural collaborative filtering
X. He, X. Du, X. Wang, F. Tian, J. Tang, and T. Chua · 2018
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Graph convolutional neural networks for web-scale recommender systems
R. Ying, R. He, K. Chen, P. Eksombatchai, W. L. Hamilton, and J. Leskovec · 2018
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Processatlas: A scalable and extensible platform for business process analytics
A. Beheshti, B. Benatallah, and H. R. Motahari-Nezhad · 2018
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Attentive contextual denoising autoencoder for recommendation
Y. Jhamb, T. Ebesu, and Y. Fang · 2018
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Latent relational metric learning via memory-based attention for collaborative ranking
Y. Tay, L. A. Tuan, and S. C. Hui · 2018
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STAMP: short-term attention/memory priority model for session-based recommendation
Q. Liu, Y. Zeng, R. Mokhosi, and H. Zhang · 2018
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Improving sequential recommendation with knowledge-enhanced memory networks
J. Huang, W. X. Zhao, H. Dou, J. Wen, and E. Y. Chang · 2018
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Constructing narrative event evolutionary graph for script event prediction
Z. Li, X. Ding, and T. Liu · 2018
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Modeling contemporaneous basket sequences with twin networks for next-item recommendation
D. Le, H. W. Lauw, and Y. Fang · 2018
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Z. Li, H. Zhao, Q. Liu, Z. Huang, T. Mei, and E. Chen · 2018
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Repeatnet: A repeat aware neural recommendation machine for session-based recommendation
P. Ren, Z. Chen, J. Li, Z. Ren, J. Ma, and M. de Rijke · 2018
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TEXUS: table extraction system for PDF documents
R. Rastan, H. Paik, J. Shepherd, S. H. Ryu, and A. Beheshti · 2018
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Explanations for temporal recommendations
H. Bharadhwaj and S. Joshi · 2018
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Graph neural networks: A review of methods and applications
J. Zhou, G. Cui, Z. Zhang, C. Yang, Z. Liu, and M. Sun · 2018
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Self-attentive sequential recommendation
W. Kang and J. J. McAuley · 2018
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Modeling consumer buying decision for recommendation based on multi-task deep learning
Q. Xia, P. Jiang, F. Sun, Y. Zhang, X. Wang, and Z. Sui · 2018
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Generative adversarial network for abstractive text summarization
L. Liu, Y. Lu, M. Yang, Q. Qu, J. Zhu, and H. Li · 2018
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PLASTIC: prioritize long and short-term information in top-n recommendation using adversarial training
W. Zhao, B. Wang, J. Ye, Y. Gao, M. Yang, and X. Chen · 2018
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Syntax-directed attention for neural machine translation
K. Chen and et al · 2018
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Recommendation through mixtures of heterogeneous item relationships
W. Kang, M. Wan, and J. J. McAuley · 2018
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SETTRUST: social exchange theory based context-aware trust prediction in online social networks
S. M. Ghafari, S. Yakhchi, A. Beheshti, and M. A. Orgun · 2018
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The role of propensity to trust and the five factor model across the trust process
G. M. Alarcon, J. B. Lyons, J. C. Christensen, M. A. Bowers, S. L. Klosterman, and A. Capiola · 2018
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Corekg: a knowledge lake service
A. Beheshti, B. Benatallah, R. Nouri, and A. Tabebordbar · 2018
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Incremental matrix co-factorization for recommender systems with implicit feedback
S. C. Anyosa, J. Vinagre, and A. M. Jorge · 2018
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Explicit feedbacks meet with implicit feedbacks: A combined approach for recommendation system
S. Mandal and A. Maiti · 2018
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Matrix factorization for recommendation with explicit and implicit feedback
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Neural cross-session filtering: Next-item prediction under intra- and inter-session context
L. Hu, Q. Chen, H. Zhao, S. Jian, L. Cao, and J. Cao · 2018
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An attribute-aware neural attentive model for next basket recommendation
T. Bai, J. Nie, W. X. Zhao, Y. Zhu, P. Du, and J. Wen · 2018
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Memory-augmented attention network for sequential recommendation
C. Hu, P. He, C. Sha, and J. Niu · 2019
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Enabling the analysis of personality aspects in recommender systems
S. Yakhchi, A. Beheshti, S. M. Ghafari, and M. Orgun · 2019
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A survey on session-based recommender systems
S. Wang, L. Cao, and Y. Wang · 2019
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A survey on association rules mining using heuristics
S. M. Ghafari and C. Tjortjis · 2019
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Deep learning based recommender system: A survey and new perspectives
S. Zhang, L. Yao, A. Sun, and Y. Tay · 2019
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Session-based recommendation with graph neural networks
S. Wu, Y. Tang, Y. Zhu, L. Wang, X. Xie, and T. Tan · 2019
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Towards context-aware social behavioral analytics
A. Beheshti, V. M. Hashemi, and S. Yakhchi · 2019
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Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations
H. Fang, G. Guo, D. Zhang, and Y. Shu · 2019
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Deep item-based collaborative filtering for top-n recommendation
F. Xue, X. He, X. Wang, J. Xu, K. Liu, and R. Hong · 2019
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DCAT: A deep context-aware trust prediction approach for online social networks
S. M. Ghafari, A. Joshi, A. Beheshti, C. Paris, S. Yakhchi, and M. A. Orgun · 2019
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Tutorial: Sequence-aware recommender systems
M. Quadrana, D. Jannach, and P. Cremonesi · 2019
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Modeling multi-purpose sessions for next-item recommendations via mixture-channel purpose routing networks
S. Wang, L. Hu, Y. Wang, Q. Z. Sheng, M. A. Orgun, and L. Cao · 2019
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Towards neural mixture recommender for long range dependent user sequences
J. Tang, F. Belletti, S. Jain, M. Chen, A. Beutel, C. Xu, and E. H. Chi · 2019
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Adaptive rule adaptation in unstructured and dynamic environments
A. Tabebordbar, A. Beheshti, B. Benatallah, and M. C. Barukh · 2019
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A simple convolutional generative network for next item recommendation
F. Yuan, A. Karatzoglou, I. Arapakis, J. M. Jose, and X. He · 2019
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Graph contextualized self-attention network for session-based recommendation
C. Xu, P. Zhao, Y. Liu, V. S. Sheng, J. Xu, F. Zhuang, J. Fang, and X. Zhou · 2019
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Learning to recommend with multiple cascading behaviors
C. Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, T. Chua, L. Yao, Y. Song, and D. Jin · 2019
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Repeatnet: A repeat aware neural recommendation machine for session-based recommendation
P. Ren, Z. Chen, J. Li, Z. Ren, J. Ma, and M. de Rijke · 2019
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Lifelong sequential modeling with personalized memorization for user response prediction
K. Ren, J. Qin, Y. Fang, W. Zhang, L. Zheng, W. Bian, G. Zhou, J. Xu, Y. Yu, X. Zhu, and K. Gai · 2019
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A long-short demands-aware model for next-item recommendation
T. Bai, P. Du, W. X. Zhao, J. Wen, and J. Nie · 2019
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Adaptive user modeling with long and short-term preferences for personalized recommendation
Z. Yu and et.al · 2019
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Recurrent convolutional neural network for sequential recommendation
C. Xu and et.al · 2019
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Deep learning based recommender system: A survey and new perspectives
S. Zhang, L. Yao, A. Sun, and Y. Tay · 2019
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Personet: Friend recommendation system based on big-five personality traits and hybrid filtering
H. Ning, S. Dhelim, and N. Aung · 2019
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Sequential recommender systems: Challenges, progress and prospects
S. Wang, L. Hu, Y. Wang, L. Cao, Q. Z. Sheng, and M. A. Orgun · 2019
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Neural demographic prediction using search query
C. Wu, F. Wu, J. Liu, S. He, Y. Huang, and X. Xie · 2019
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NPA: neural news recommendation with personalized attention
C. Wu, F. Wu, M. An, J. Huang, Y. Huang, and X. Xie · 2019
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Datasynapse: A social data curation foundry
A. Beheshti, B. Benatallah, A. Tabebordbar, H. R. Motahari-Nezhad, M. C. Barukh, and R. Nouri · 2019
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Context-aware sequential recommendations withstacked recurrent neural networks
L. Rakkappan and V. Rajan · 2019
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A collaborative session-based recommendation approach with parallel memory modules
M. Wang, P. Ren, L. Mei, Z. Chen, J. Ma, and M. de Rijke · 2019
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Conceptmap: A conceptual approach for formulating user preferences in large information spaces
A. Tabebordbar, A. Beheshti, and B. Benatallah · 2019
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A. Beheshti, A. Tabebordbar, and B. Benatallah · 2020
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Towards a deep attention-based sequential recommender system
S. Yakhchi, A. Beheshti, S. M. Ghafari, M. A. Orgun, and G. Liu · 2020
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Towards cognitive recommender systems
A. Beheshti, S. Yakhchi, S. Mousaeirad, S. M. Ghafari, S. R. Goluguri, and M. A. Edrisi · 2020
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Deep feature learnt by conventional deep neural network
H. Niu, W. Xu, H. Akbarzadeh, H. Parvin, A. Beheshti, and H. Alinejad-Rokny · 2020
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Feature-based and adaptive rule adaptation in dynamic environments
A. Tabebordbar, A. Beheshti, B. Benatallah, and M. C. Barukh · 2020
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Inferring implicit rules by learning explicit and hidden item dependency
S. Wang and L. Cao · 2020
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Cognitive privacy: Ai-enabled privacy using EEG signals in the internet of things
F. Schiliro, N. Moustafa, and A. Beheshti · 2020
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Convolutional neural network for medical image classification using wavelet features
A. Khatami, A. Nazari, A. Beheshti, T. T. Nguyen, S. Nahavandi, and J. Zieba · 2020
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A novel cognitive computing technique using convolutional networks for automating the criminal investigation process in policing
F. Schiliro, A. Beheshti, and N. Moustafa · 2020
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Attention mechanism in predictive business process monitoring
A. Jalayer, M. Kahani, A. Beheshti, A. Pourmasoumi, and H. R. Motahari-Nezhad · 2020
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Attentive sequential models of latent intent for next item recommendation
M. M. Tanjim, C. Su, E. Benjamin, D. Hu, L. Hong, and J. J. McAuley · 2020
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Sequential recommender systems: Challenges, progress and prospects
S. Wang, L. Hu, Y. Wang, L. Cao, Q. Z. Sheng, and M. A. Orgun · 2020
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Linking textual and contextual features for intelligent cyberbullying detection in social media
N. Rezvani, A. Beheshti, and A. Tabebordbar · 2020
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Modeling personalized item frequency information for next-basket recommendation
H. Hu, X. He, J. Gao, and Z. Zhang · 2020
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personality2vec: Enabling the analysis of behavioral disorders in social networks
A. Beheshti, V. M. Hashemi, S. Yakhchi, H. R. Motahari-Nezhad, S. M. Ghafari, and J. Yang · 2020
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A survey on trust prediction in online social networks
S. M. Ghafari, A. Beheshti, A. Joshi, C. Paris, A. Mahmood, S. Yakhchi, and M. A. Orgun · 2020
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Intelligent knowledge lakes: The age of artificial intelligence and big data
A. Beheshti, B. Benatallah, Q. Z. Sheng, and F. Schiliro · 2020
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Exploiting cross-session information for session-based recommendation with graph neural networks
R. Qiu, Z. Huang, J. Li, and H. Yin · 2020
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