A scalable approach for index in generic location-aware rank query. (24th November 2020)

• Record Type: Journal Article
• Authors: Buranasaksee, Utharn
• Is Part Of: International journal of intelligent information and database systems. Volume 14:Number 1(2021)
• Page Start: 26
• Page End: 48
• Publication Date: 2020-11-24
• Subjects: scalable -- generic -- location-aware -- query -- search -- keyword -- spatial; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

As location-aware information becomes more popular, many researchers have been proposed many effective approaches to solving the problem. In this work, we identify the shortcomings of the existing method from the LINQ framework as our baseline. After that, an efficient method called Multi-IRS is proposed to optimise the query search at runtime. Our analysis points out how optimisation could be done. Multi-IRS makes use of the improved algorithm that addresses numeric and textual attributes. After that, the sparse ordered set is proposed to reduce the index construction time. Finally, the external attribute-based IR-tree sort algorithm is proposed to solve the scalability issues. Throughout the extensive experiments, our proposed method significantly outperforms the baseline algorithm.