An efficient query indexing mechanism for filtering geo-textual data
In the information era, large amount of geo-tagged data has given rise to our ability to make more reasonable decisions. The geo-tagged data is usually associated with related text information. For example, tweets tagged with geo-locations on Tweeter, and restaurant reviews tagged with the restauran...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2014
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| Online Access: | http://hdl.handle.net/10356/59269 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In the information era, large amount of geo-tagged data has given rise to our ability to make more reasonable decisions. The geo-tagged data is usually associated with related text information. For example, tweets tagged with geo-locations on Tweeter, and restaurant reviews tagged with the restaurant locations on Yelp.
Users may want to be notified of interesting geo-textual objects. For example, a user may want to be informed when tweets containing term “discount” are posted within 10 km of the user’s home.
In this project, we build a system which matches Simplified Boolean Range Continuous queries over streams of incoming geo-textual objects in real time. In particular, we extend the existing BRCQ system and the IQ-tree structure for in-memory indexing and computation, and propose query indexing mechanisms for filtering geo-textual data. In addition, we also propose the algorithm for matching the queries with incoming geo-textual objects based on the index. Moreover, we build a web system to implement the process of submitting queries, matching queries over incoming geo-textual objects, and returning matched results to users. |
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