Query-oriented keyphrase extraction
|Query-oriented keyphrase extraction|
|Author(s)||Qiu M., Li Y., Jiang J.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Informativeness, Keyphrase extraction, Language model, Phraseness (Extra: Baseline methods, Empirical evaluations, General method, Informativeness, Keyphrase extraction, Language model, Phraseness, Search results, Wikipedia, Computational linguistics, Information retrieval, Infrared devices, Natural language processing systems, Search engines, Websites, Query processing)|
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Query-oriented keyphrase extraction is a 2012 conference paper written in English by Qiu M., Li Y., Jiang J. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
People often issue informational queries to search engines to find out more about some entities or events.While aWikipedia-like summary would be an ideal answer to such queries, not all queries have a corresponding Wikipedia entry. In this work we propose to study query-oriented keyphrase extraction, which can be used to assist search results summarization. We propose a general method for keyphrase extraction for our task, where we consider both phraseness and informativeness. We discuss three criteria for phraseness and four ways to compute informativeness scores. Using a large Wikipedia corpus and 40 queries, our empirical evaluation shows that using a named entity-based phraseness criterion and a language model-based informativeness score gives the best performance on our task. This method also outperforms two state-of-the-art baseline methods.
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