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Computers understand very little of the meaning of human language.
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Viewing stemming as recall enhancement
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Empirical analysis of predictive algorithms for collaborative filtering
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The anatomy of a large-scale hypertextual Web search engine
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Combining local context and WordNet similarity for word sense identification
Leacock, C., and Chodrow, M. (1998) · 1998
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Automatic retrieval and clustering of similar words
Lin, D. (1998) · 1998
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Spamcop: A spam classification and organization program
Pantel, P., and Lin, D. (1998) · 1998
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A Bayesian approach to filtering junk e-mail
Sahami, M., Dumais, S., Heckerman, D., and Horvitz, E. (1998) · 1998
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Automatic word sense discrimination
Schütze, H. (1998) · 1998
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A framework for learning predictive structures from multiple tasks and unlabeled data
Ando, R. K., and Zhang, T. (2005) · 2005
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Integrating word relationships into language models
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Statistical language modeling for information retrieval
Liu, X., and Croft, W. B. (2005) · 2005
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Inducing ontological co-occurrence vectors
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Randomized algorithms and nlp: using locality sensitive hash function for high speed noun clustering
Ravichandran, D., Pantel, P., and Hovy, E. (2005) · 2005
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Learning from text: Matching readers and texts by latent semantic analysis
Wolfe, M. B. W., Schreiner, M. E., Rehder, B., Laham, D., Foltz, P. W., Kintsch, W., and Landauer, T. K. (1998) · 1998
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Modern Information Retrieval
Baeza-Yates, R., and Ribeiro-Neto, B. (1999) · 1999
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Vector-based natural language call routing
Chu-carroll, J., and Carpenter, B. (1999) · 1999
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Similarity-based models of word cooccurrence probabilities
Dagan, I., Lee, L., and Pereira, F. C. N. (1999) · 1999
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The intelligent essay assessor: Applications to educational technology
Foltz, P. W., Laham, D., and Landauer, T. K. (1999) · 1999
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Probabilistic Latent Semantic Indexing
Hofmann, T. (1999) · 1999
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An introduction to random indexing
Sahlgren, M. (2005) · 2005
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Measuring semantic similarity by latent relational analysis
Turney, P. D. (2005) · 2005
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Corpus-based learning of analogies and semantic relations
Turney, P. D., and Littman, M. L. (2005) · 2005
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Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations
Witten, I. H., and Frank, E. (2005) · 2005
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Word Sense Disambiguation: Algorithms and Applications
Agirre, E., and Edmonds, P. G. (2006) · 2006
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Clustering word pairs to answer analogy questions
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Fast low-rank modifications of the thin singular value decomposition
Brand, M. (2006) · 2006
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Evaluating wordnet-based measures of semantic distance
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Relational web search
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Overview of the TREC 2006 question answering track
Dang, H. T., Lin, J., and Kelly, D. (2006) · 2006
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Scaling distributional similarity to large corpora
Gorman, J., and Curran, J. R. (2006) · 2006
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Generalized Hebbian algorithm for incremental singular value decomposition in natural language processing
Gorrell, G. (2006) · 2006
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Generating query substitutions
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Automatically assessing review helpfulness
Kim, S.-M., Pantel, P., Chklovski, T., and Pennacchiotti, M. (2006) · 2006
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Effects of high-order co-occurrences on word semantic similarity
Lemaire, B., and Denhière, G. (2006) · 2006
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Distributional measures of concept-distance: A task-oriented evaluation
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Learning noun-modifier semantic relations with corpus-based and WordNet-based features
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Names and similarities on the Web: Fact extraction in the fast lane
Paşca, M., Lin, D., Bigham, J., Lifchits, A., and Jain, A. (2006) · 2006
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Using wordnet-based context vectors to estimate the semantic relatedness of concepts
Patwardhan, S., and Pedersen, T. (2006) · 2006
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Unsupervised corpus-based methods for WSD
Pedersen, T. (2006) · 2006
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Ontologizing semantic relations
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The Word-Space Model: Using distributional analysis to represent syntagmatic and paradigmatic relations between words in high-dimensional vector spaces
Sahlgren, M. (2006) · 2006
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Semantic taxonomy induction from heterogenous evidence
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Similarity of semantic relations
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Scaling up all pairs similarity search
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Extracting semantic representations from word co-occurrence statistics: A computational study
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Cross-language information retrieval using PARAFAC2
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Combining symbolic and distributional models of meaning
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A simple, similarity-based model for selectional preferences
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Semeval-2007 task 04: Classification of semantic relations between nominals
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Handbook of Latent Semantic Analysis
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