Query expansion using named entity disambiguation for a question‐answering system. (27th December 2018)

• Record Type: Journal Article
• Authors: Kandasamy, Saravanakumar; Cherukuri, Aswani Kumar
• Other Names: Abdel‐Basset Mohamed guestEditor.; Zhou Yongquan guestEditor.; Smarandache Florentin guestEditor.
• Is Part Of: Concurrency and computation. Volume 32:Number 4(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-12-27
• Subjects: named entity disambiguation -- NE mentions -- NLP -- question‐answering system -- Wikipedia disambiguation -- WordNet similarity; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5119
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Due to the exponential growth in the size of available data, people often prefer direct answers in many cases, instead of a set of ranked documents while searching using a search engine. Furthermore, people often do not provide enough information regarding their search. Query expansion would help in such cases so that queries would be best understood by search engines. Although the queries are expanded, many a times, they end up with wrong results due to the entity mentions in the questions. Hence, we need to disambiguate named entities properly so as to choose the right mention. In this paper, a method is proposed for named entity disambiguation in order to help in query expansion. An adapted Lesk similarity measure is used to find the similarity between questions and the target Wikipedia disambiguation pages. The proposed approach has shown very good results in disambiguating organization‐ and miscellaneous‐type entity mentions.