JOURNAL ARTICLE

Query expansion using named entity disambiguation for a question‐answering system

Saravanakumar KandasamyAswani Kumar Cherukuri

Year: 2018 Journal:   Concurrency and Computation Practice and Experience Vol: 32 (4)   Publisher: Wiley

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.

Keywords:
Computer science Information retrieval Set (abstract data type) Query expansion Similarity (geometry) Search engine Web search query Artificial intelligence

Metrics

14
Cited By
1.39
FWCI (Field Weighted Citation Impact)
22
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems

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