Search in location-based social network

• Main Author: Phan, Nhan Tue.
• Other Authors: School of Computer Engineering
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
• Online Access: http://hdl.handle.net/10356/52786
• Institution: Nanyang Technological University

It is a generally acknowledge issue that the social network has inevitably become an essential part of everybody’s life. With the location based social network, people can inform their friends and families where and what they visit and see in an un-obstructive manner. Existing services allow location owners to publish their places to the database and provide them platform to customize how the users want to find out about their places. Specifying categories and tags can greatly aid them to stand out from numerous queries of users. Hence, exploiting the searching functions on those location based social network can lead to huge benefit. Moreover, web objects that contain both geographical location information as well as the textual description had gained attention of how to efficiently deal with it. Search queries that specifically target those objects need special retrieving techniques to handle. This FYP follows that idea and has been separated into two parts. The first part is to develop a prototype application for SWORS (a System for Efficient Retrieval of Spatial Web Objects). This system is capable of providing efficient technique to retrieve spatial web objects that satisfies spatial keyword queries. It provides interfaces for browser-based desktop and laptop as well as native application on smart phones. The second objective is to explore the opportunity in optimizing the searching of these spatial objects by looking into the methods to recommend the appropriate tags to a point of interest so that it can acquire more chance to appear in the results of user queries. Two basic methods were implemented: brute force method and the heuristic method. Comparisons between the two methods and different weighting scheme for the location search engine were conducted.