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In this paper, we introduce the notion of motif closure and describe higher-order ranking and link prediction methods based on the notion of closing higher-order network motifs.
Item-based top-n recommendation algorithms
Mukund Deshpande and George Karypis. 2004 · 2004
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Understanding Search Engines: Mathematical Modeling and Text Retrieval
Michael W Berry and Murray Browne. 2005 · 2005
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The link-prediction problem for social networks
David Liben-Nowell and Jon Kleinberg. 2007 · 2007
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Introduction to information retrieval
Christopher Manning, Prabhakar Raghavan, and Hinrich Schütze. 2010 · 2010
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Real-time top-n recommendation in social streams. In
Ernesto Diaz-Aviles, Lucas Drumond, Lars Schmidt-Thieme, and Wolfgang Nejdl. 2012 · 2012
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Transforming graph data for statistical relational learning
Ryan A. Rossi, Luke K. McDowell, David W. Aha, and Jennifer Neville. 2012 · 2012
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Ranking via robust binary classification. In
Hyokun Yun, Parameswaran Raman, and S Vishwanathan. 2014 · 2014
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Efficient Graphlet Counting for Large Networks. In
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, and Nick Duffield. 2015 · 2015
Cited alongside, same era.
Online ranking with top-1 feedback. In
Sougata Chaudhuri and Ambuj Tewari. 2015 · 2015
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The Network Data Repository with Interactive Graph Analytics and Visualization. In
Ryan A. Rossi and Nesreen K. Ahmed. 2015 · 2015
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Estimation of Graphlet Counts in Massive Networks. In
Ryan A. Rossi, Rong Zhou, and Nesreen K. Ahmed. 2018 · 2018
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Verse: Versatile graph embeddings from similarity measures. In
Anton Tsitsulin, Davide Mottin, Panagiotis Karras, and Emmanuel Müller. 2018 · 2018
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