The Research on the Algorithms of Keyword Search in Relational Database

  • Authors:
  • Peng Li;Qing Zhu;Shan Wang

  • Affiliations:
  • Key Laboratory of Data Engineering and Knowledge Engineering School of Information, Renmin University of China, Beijing, P.R. China 100872;Key Laboratory of Data Engineering and Knowledge Engineering School of Information, Renmin University of China, Beijing, P.R. China 100872;Key Laboratory of Data Engineering and Knowledge Engineering School of Information, Renmin University of China, Beijing, P.R. China 100872

  • Venue:
  • Advanced Web and NetworkTechnologies, and Applications
  • Year:
  • 2008

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Abstract

With the development of relational database, people require better database not only in the aspect of database performance, but also in the aspect of the database's interactive ability. So that the database is much more friendly than just before and it is possible for a common user who do not have any special knowledge on database can access the database, without knowing the schema of database and writing intricate SQL. For the reason that the information retrieval on the web has developed well to some extent, when we develop the technology of keyword search in relational database, we can draw some ideas from information retrieve. But the great differences between the text database on the web and the relational database also bring some new challenges: 1) The answer needed by user is not only one tuple in database, but the tuple sets consisting of the tuple connect from different table using the "primary key-foreign key" relationship. 2)The results of the evaluation criteria is more important, because it is directly related to the effectiveness of Search System. 3)The structure of relational database is much more intricate than text database, and the algorithms of information retrieval are not fit the relational database. So in this paper, we introduce a novel keyword search algorithm and a modified criteria of evaluating answers in order to enhance efficiency of the keyword search and return much more effective information to users, finally, the search algorithm's performance is tested and evaluated.