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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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