Weight-Adjustable Ranking for Keyword Search in  Relational Databases

淡江大學機構典藏 > 商管學院 > 資訊管理學系暨研究所 > 會議論文 > Item 987654321/115342

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题名:	Weight-Adjustable Ranking for Keyword Search in Relational Databases
作者:	Chichang Jou, Sian Lun Lau
关键词:	Keyword Search, Information Retrieval, Ranking, Mean Average Precision, Rank Reciprocal Difference
日期:	2018-08-08
上传时间:	2018-10-23 12:11:49 (UTC+8)
摘要:	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.
關聯:	NA
显示于类别:	[資訊管理學系暨研究所] 會議論文

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