Location-based keyword search: enhancing IR-tree querying
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 proces...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | Final Year Project |
| اللغة: | English |
| منشور في: |
Nanyang Technological University
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://hdl.handle.net/10356/162865 |
| الوسوم: |
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| المؤسسة: | Nanyang Technological University |
| اللغة: | English |
| الملخص: | 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. |
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