Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162865
Title: Location-based keyword search: enhancing IR-tree querying
Authors: Aik, Yu Chen
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Aik, Y. C. (2022). Location-based keyword search: enhancing IR-tree querying. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162865
Abstract: Location-based and keyword search query has been increasing in popularity throughout the years. This type of query makes use of the location information and tagged documents to locate the top K most relevant point of interest. There exists an indexing framework, IR-Tree, that allows efficient processing of such query by combining the use of inverted file for tagged documents and R-Tree for location information. However, there is still limitation on the I/O cost for loading the inverted files when processing a query. Therefore, in this paper an enhanced implementation of the IR-Tree that incorporate B+ Tree Indexing for the inverted files will be introduce. Result on the evaluation of the enhanced implementation also shows significant improvement on the performance.
URI: https://hdl.handle.net/10356/162865
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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