Affiliated with RCfalse
A robust noise resistant algorithm for POI identification from Flickr data
Yiyang Yang1; Zhiguo Gong2; Qing Li3; Leong Hou U2; Ruichu Cai1; Zhifeng Hao4
2017
Conference Namethe Twenty-Sixth International Joint Conference on Artificial Intelligence
Source PublicationIJCAI International Joint Conference on Artificial Intelligence
Pages3294-3300
Conference DateAugust 2017
Conference PlaceMelbourne, Australia
Abstract

Point of Interests (POI) identification using social media data (e.g. Flickr, Microblog) is one of the most popular research topics in recent years. However, there exist large amounts of noises (POI irrelevant data) in such crowd-contributed collection-s. Traditional solutions to this problem is to set a global density threshold and remove the data point as noise if its density is lower than the threshold. However, the density values vary significantly a-mong POIs. As the result, some POIs with relatively lower density could not be identified. To solve the problem, we propose a technique based on the local drastic changes of the data density. First we define the local maxima of the density function as the Urban POIs, and the gradient ascent algorithm is exploited to assign data points into different clusters. To remove noises, we incorporate the Lapla-cian Zero-Crossing points along the gradient ascent process as the boundaries of the POI. Points located outside the POI region are regarded as noises. Then the technique is extended into the geographical and textual joint space so that it can make use of the heterogeneous features of social media. The experimental results show the significance of the proposed approach in removing noises.

URLView the original
Fulltext Access
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorZhiguo Gong
Affiliation1.Faculty of Computer, Guangdong University of Technology, Guangzhou, China
2.Department of Computer and Information Science, University of Macau, Macau SAR
3.Department of Computer Science, City University of Hong Kong, Hong Kong SAR
4.School of Mathematics and Big Data, Foshan University, Foshan, China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yiyang Yang,Zhiguo Gong,Qing Li,et al. A robust noise resistant algorithm for POI identification from Flickr data[C],2017:3294-3300.
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