Information retrieval using a singular value decomposition model of latent semantic structure
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
About retrieval models and logic
The Computer Journal - Special issue on information retrieval
The nature of statistical learning theory
The nature of statistical learning theory
Information calculus for information retrieval
Journal of the American Society for Information Science
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A vector space model for automatic indexing
Communications of the ACM
DIRT @SBT@discovery of inference rules from text
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Journal of Intelligent Information Systems
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Introduction to the special issue on computational linguistics using large corpora
Computational Linguistics - Special issue on using large corpora: I
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
The Geometry of Information Retrieval
The Geometry of Information Retrieval
Geometry and Meaning
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Automatically discovering word senses
NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations - Volume 4
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Semantic Kernels for Text Classification Based on Topological Measures of Feature Similarity
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
A study on convolution kernels for shallow semantic parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
Dependency-Based Construction of Semantic Space Models
Computational Linguistics
Euclidean Embedding of Co-occurrence Data
The Journal of Machine Learning Research
Tree kernels for semantic role labeling
Computational Linguistics
Document-Word Co-regularization for Semi-supervised Sentiment Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Semantic classification with distributional kernels
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Automatic induction of FrameNet lexical units
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A structured vector space model for word meaning in context
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Combined syntactic and semantic Kernels for text classification
ECIR'07 Proceedings of the 29th European conference on IR research
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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The distributional hypothesis states that words with similar distributional properties have similar semantic properties (Harris 1968). This perspective on word semantics, was early discussed in linguistics (Firth 1957; Harris 1968), and then successfully applied to Information Retrieval (Salton, Wong and Yang 1975). In Information Retrieval, distributional notions (e.g. document frequency and word co-occurrence counts) have proved a key factor of success, as opposed to early logic-based approaches to relevance modeling (van Rijsbergen 1986; Chiaramella and Chevallet 1992; van Rijsbergen and Lalmas 1996).