Mining interesting locations and travel sequences from GPS trajectories

1.7kCitations
Citations of this article
954Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The increasing availability of GPS-enabled devices is changing the way people interact with the Web, and brings us a large amount of GPS trajectories representing people's location histories. In this paper, based on multiple users' GPS trajectories, we aim to mine interesting locations and classical travel sequences in a given geospatial region. Here, interesting locations mean the culturally important places, such as Tiananmen Square in Beijing, and frequented public areas, like shopping malls and restaurants, etc. Such information can help users understand surrounding locations, and would enable travel recommendation. In this work, we first model multiple individuals' location histories with a tree-based hierarchical graph (TBHG). Second, based on the TBHG, we propose a HITS (Hypertext Induced Topic Search)-based inference model, which regards an individual's access on a location as a directed link from the user to that location. This model infers the interest of a location by taking into account the following three factors. 1) The interest of a location depends on not only the number of users visiting this location but also these users' travel experiences. 2) Users' travel experiences and location interests have a mutual reinforcement relationship. 3) The interest of a location and the travel experience of a user are relative values and are region-related. Third, we mine the classical travel sequences among locations considering the interests of these locations and users' travel experiences. We evaluated our system using a large GPS dataset collected by 107 users over a period of one year in the real world. As a result, our HITS-based inference model outperformed baseline approaches like rank-by-count and rank-by-frequency. Meanwhile, when considering the users' travel experiences and location interests, we achieved a better performance beyond baselines, such as rank-by-count and rank-by-interest, etc. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

References Powered by Scopus

Reality mining: Sensing complex social systems

2096Citations
N/AReaders
Get full text

Cyberguide: A mobile context-aware tour guide

986Citations
N/AReaders
Get full text

Understanding mobility based on GPS data

939Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Friendship and mobility: User movement in location-based social networks

2570Citations
N/AReaders
Get full text

Trajectory data mining: An overview

1493Citations
N/AReaders
Get full text

Exploiting geographical influence for collaborative point-of-interest recommendation

1044Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Zheng, Y., Zhang, L., Xie, X., & Ma, W. Y. (2009). Mining interesting locations and travel sequences from GPS trajectories. In WWW’09 - Proceedings of the 18th International World Wide Web Conference (pp. 791–800). https://doi.org/10.1145/1526709.1526816

Readers over time

‘09‘10‘11‘12‘13‘14‘15‘16‘17‘18‘19‘20‘21‘22‘23‘24‘2504080120160

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 565

80%

Researcher 86

12%

Professor / Associate Prof. 41

6%

Lecturer / Post doc 17

2%

Readers' Discipline

Tooltip

Computer Science 519

75%

Engineering 117

17%

Earth and Planetary Sciences 36

5%

Social Sciences 20

3%

Article Metrics

Tooltip
Mentions
References: 1

Save time finding and organizing research with Mendeley

Sign up for free
0