2011/08/23 by Yanwei Xu, Yanwei XU, XU, Yanwei
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Peer-to-Peer Network Technologies #cs.DB #cs.IR
paper · pdf · doi:10.48550/arxiv.1108.4516
arxiv created 2011/08/23 · openalex publication_date 2011/08/23 · arxiv updated 2011/08/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. Most of existing methods focus on answering snapshot keyword queries in static databases. In practice, however, databases are updated frequently, and users may have long-term interests on specific topics. To deal with such a situation, it is necessary to build effective and efficient facility in a database system to support continual keyword queries. In this paper, we propose an efficient method for answering continual top-k keyword queries over relational databases. The proposed method is built on an existing scheme of keyword search on relational data streams, but incorporates the ranking mechanisms into the query processing methods and makes two improvements to support efficient top-k keyword search in relational databases. Compared to the existing methods, our method is more efficient both in computing the top-k results in a static database and in maintaining the top-k results when the database continually being updated. Experimental results validate the effectiveness and efficiency of the proposed method.