Similarity-Based Models of Word Cooccurrence Probabilities
Machine Learning - Special issue on natural language learning
Placing search in context: the concept revisited
ACM Transactions on Information Systems (TOIS)
Modern Information Retrieval
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Introduction to topic detection and tracking
Topic detection and tracking
On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
SEXTANT: exploring unexplored contexts for semantic extraction from syntactic analysis
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Newsjunkie: providing personalized newsfeeds via analysis of information novelty
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Information diffusion through blogspace
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Identifying similarities, periodicities and bursts for online search queries
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Measures of distributional similarity
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Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
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Temporal analysis of a very large topically categorized Web query log
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WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using wiktionary for computing semantic relatedness
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Extended gloss overlaps as a measure of semantic relatedness
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Compact full-text indexing of versioned document collections
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WikiWalk: random walks on Wikipedia for semantic relatedness
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Leveraging temporal dynamics of document content in relevance ranking
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Wisdom of crowds versus wisdom of linguists – measuring the semantic relatedness of words
Natural Language Engineering
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ECIR'07 Proceedings of the 29th European conference on IR research
Linear time series models for term weighting in information retrieval
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Temporal latent semantic analysis for collaboratively generated content: preliminary results
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Modeling and predicting behavioral dynamics on the web
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Detecting unexpected correlation between a current topic and products from buzz marketing sites
DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
Large-scale learning of word relatedness with constraints
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Explanatory semantic relatedness and explicit spatialization for exploratory search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Measuring word relatedness using heterogeneous vector space models
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
KORE: keyphrase overlap relatedness for entity disambiguation
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Theme chronicle model: chronicle consists of timestamp and topical words over each theme
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Supervised learning of semantic relatedness
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
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WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Computing semantic relatedness using word frequency and layout information of Wikipedia
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Steeler nation, 12th man, and boo birds: classifying Twitter user interests using time series
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Computing the degree of semantic relatedness of words is a key functionality of many language applications such as search, clustering, and disambiguation. Previous approaches to computing semantic relatedness mostly used static language resources, while essentially ignoring their temporal aspects. We believe that a considerable amount of relatedness information can also be found in studying patterns of word usage over time. Consider, for instance, a newspaper archive spanning many years. Two words such as "war" and "peace" might rarely co-occur in the same articles, yet their patterns of use over time might be similar. In this paper, we propose a new semantic relatedness model, Temporal Semantic Analysis (TSA), which captures this temporal information. The previous state of the art method, Explicit Semantic Analysis (ESA), represented word semantics as a vector of concepts. TSA uses a more refined representation, where each concept is no longer scalar, but is instead represented as time series over a corpus of temporally-ordered documents. To the best of our knowledge, this is the first attempt to incorporate temporal evidence into models of semantic relatedness. Empirical evaluation shows that TSA provides consistent improvements over the state of the art ESA results on multiple benchmarks.