Weight-adjustable ranking for keyword search in relational satabases

Jou, Chichang. and Lau, Sian Lun * (2018) Weight-adjustable ranking for keyword search in relational satabases. In: 2nd International Conference on Intelligent and Interactive Computing (IIC2018), 8-9 August 2018, Melaka, Malaysia. (Unpublished)

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Huge volumes of invaluable information are hidden behind web relational databases. They could not be extracted by search engines. The problem is especially severe for long text data, for example: book reviews, company descriptions, and product specifications. Many researches have investigated to integrate information retrieval and database indexing technologies to provide keyword search functionality for these useful contents. Due to diversifying data relationships in application domains and miscellaneous personal preferences, current ranking results of related researches do not satisfy user requirements. We design and implement a Weight-Adjustable Ranking for Keyword Search (WARKS) system to address the issue. Mean average precision (MAP) and mean rank reciprocal difference (MRRD) are proposed as measurements of ranking effectiveness. We use an integrated international trade show database as our experimental domain. User study demonstrates that WARKS performs better than previous practices.

Item Type: Conference or Workshop Item (Paper)
Additional Information: IIC2018
Uncontrolled Keywords: Keyword Search; Information Retrieval; Ranking; Mean Average Precision, Rank Reciprocal Difference. 1
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Others > Non Sunway Academics
Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 29 Mar 2021 03:02
Last Modified: 29 Mar 2021 03:02
URI: http://eprints.sunway.edu.my/id/eprint/1690

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