ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Using Wikipedia and Wiktionary in domain-specific information retrieval
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
ANITA: a narrative interpretation of taxonomies for their adaptation to text collections
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Editorial: Narrative-based taxonomy distillation for effective indexing of text collections
Data & Knowledge Engineering
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This paper studies the influence of lexical semantic knowledge upon two related tasks: ad-hoc information retrieval and text similarity. For this purpose, we compare the performance of two algorithms: (i) using semantic relatedness, and (ii) using a conventional extended Boolean model [12]. For the evaluation, we use two different test collections in the German language: (i) GIRT [5] for the information retrieval task, and (ii) a collection of descriptions of professions built to evaluate a system for electronic career guidance in the information retrieval and text similarity task. We found that integrating lexical semantic knowledge improves performance for both tasks. On the GIRT corpus, the performance is improved only for short queries. The performance on the collection of professional descriptions is improved, but crucially depends on the preprocessing of natural language essays employed as topics.