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Paper
Title

An Effective Path-aware Approach for Keyword Search over Data Graphs

Year: 1399
COI: JR_JACET-6-3_005
Language: EnglishView: 34
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Authors

Asieh Ghanbarpour - Department of Computer Engineering, University of Sistan and Baluchestan, Zahedan, Iran
Hassan Naderi - Computer Engineering Department, Iran University of Science and Technology (IUST), Tehran, Iran
Soheil ZareMotlagh - University of Sistan and Baluchestan, Zahedan, Iran

Abstract:

Abstract—Keyword Search is known as a user-friendly alternative for structured languages to retrieve information from graph-structured data. Efficient retrieving of relevant answers to a keyword query and effective ranking of these answers according to their relevance are two main challenges in the keyword search over graph-structured data. In this paper, a novel scoring function is proposed, which utilizes both the textual and structural features of answers in order to produce a more accurate order of answers. In addition, a query processing algorithm is developed based on information spreading technique to enumerate answers in approximate order. This algorithm is further improved by allowing a skewed development toward more promising paths and enables a more efficient processing of keyword queries. Performance evaluation through extensive experiments on a standard benchmark of three real-world datasets shows the effectiveness and efficiency of the proposed algorithms.Index Terms—Information retrieval, Database, Keyword search, Relevant answers, Information spreading.

Keywords:

Information Retrieval, Database, Keyword search, Relevant answers, Information spreading

Paper COI Code

This Paper COI Code is JR_JACET-6-3_005. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1170732/

How to Cite to This Paper:

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Ghanbarpour, Asieh and Naderi, Hassan and ZareMotlagh, Soheil,1399,An Effective Path-aware Approach for Keyword Search over Data Graphs,https://civilica.com/doc/1170732

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Scientometrics

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Type of center: دانشگاه دولتی
Paper count: 10,178
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