Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A unified framework for automatic evaluation using N-gram co-occurrence statistics
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Web-based list question answering
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
Query modeling for entity search based on terms, categories, and examples
ACM Transactions on Information Systems (TOIS)
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The most important work that takes the center stage in the Entity Ranking track of INEX is proper query formation. Both the subtasks, namely Entity Ranking and List Completion, would immensely benefit if the given query can be expanded with more relevant terms, thereby improving the efficiency of the search engine. This paper stresses on the correct identification of "Meaningful n-grams" from the given title and proper selection of the "Prominent n-grams" among them as the utmost important task that improves query formation and hence improves the efficiencies of the overall Entity Ranking tasks. We also exploit the Initial Descriptions (IDES) of the Wikipedia articles for ranking the retrieved answers based on their similarities with the given topic. List completion task is further aided by the related Wikipedia articles that boosted the score of retrieved answers.