Enriching web taxonomies through subject categorization of query terms from search engine logs
Decision Support Systems - Web retrieval and mining
Mining longitudinal web queries: trends and patterns
Journal of the American Society for Information Science and Technology
Semantic Log Analysis Based on a User Query Behavior Model
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
ACM SIGKDD Explorations Newsletter
Proceedings of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge
Analysis of multiple query reformulations on the web: The interactive information retrieval context
Information Processing and Management: an International Journal
Using the web to validate lexico-semantic relations
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Explaining query modifications: an alternative interpretation of term addition and removal
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
A spatial structure analysis of candidate chinese hyponymy based on concept space
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
On the evaluation and improvement of Arabic WordNet coverage and usability
Language Resources and Evaluation
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A web search engine log is a very rich source of semantic knowledge. In this paper we focus on the extraction of hyponymy relations from individual user sessions by examining, search behavior. The results obtained allow us to identify specific reformulation models as ones that more frequently represent hyponymy relations. The extracted relations reflect the knowledge that the user is employing while searching the web. Simultaneously, this study leads to a better understanding of web user search behavior.