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...

全面介紹

Saved in:
書目詳細資料
主要作者: Cui, Yan
其他作者: School of Computer Engineering
格式: Final Year Project
語言:English
出版: 2014
主題:
在線閱讀:http://hdl.handle.net/10356/59269
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
語言: English
實物特徵
總結: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.