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dc.contributor.authorAik, Yu Chenen_US
dc.identifier.citationAik, Y. C. (2022). Location-based keyword search: enhancing IR-tree querying. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractLocation-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.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleLocation-based keyword search: enhancing IR-tree queryingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorGao Congen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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