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Keyword query with structure: towards semantic scoring of XML search results

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Abstract

Keyword search is an effective paradigm for information discovery and has been introduced recently to query XML documents. Scoring of XML search results is an important issue in XML keyword search. Traditional “bag-of-words” model cannot differentiate the roles of keywords as well as the relationship between keywords, thus is not proper for XML keyword queries. In this paper, we present a new scoring method based on a novel query model, called keyword query with structure (QWS), which is specially designed for XML keyword query. The method is based on a totally new view taken by the QWS model on a keyword query that, a keyword query is a composition of several query units, each representing a query condition. We believe that this method captures the semantic relevance of the search results. The paper first introduces an algorithm reformulating a keyword query to a QWS. Then, a scoring method is presented which measures the relevance of search results according to how many and how well the query conditions are matched. The scoring method is also extended to clusters of search results. Experimental results verify the effectiveness of our methods.

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Authors and Affiliations

  1. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, People’s Republic of China

    Xiping Liu, Changxuan Wan & Dexi Liu

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  1. Xiping Liu
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  2. Changxuan Wan
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  3. Dexi Liu
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Correspondence to Xiping Liu.

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Liu, X., Wan, C. & Liu, D. Keyword query with structure: towards semantic scoring of XML search results. Inf Technol Manag 17, 151–163 (2016). https://doi.org/10.1007/s10799-015-0247-z

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