太阳成8722(中国)有限公司-GREEN NO.1

标题：Semantic-Geographic Trajectory Pattern Mining Based on a New Similarity Measurement

作者：Wan, Y (Wan, You); Zhou, CH (Zhou, Chenghu); Pei, T (Pei, Tao)

来源出版物：ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 卷：6期：7 文献编号: 212 DOI：10.3390/ijgi6070212 出版年：JUL 2017

摘要：Trajectory pattern mining is becoming increasingly popular because of the development of ubiquitous computing technology. Trajectory data contain abundant semantic and geographic information that reflects people's movement patterns, i.e., who is performing a certain type of activity when and where. However, the variety and complexity of people's movement activity and the large size of trajectory datasets make it difficult to mine valuable trajectory patterns. Moreover, most existing trajectory similarity measurements only consider a portion of the information contained in trajectory data. The patterns obtained cannot be interpreted well in terms of both semantic meaning and geographic distributions. As a result, these patterns cannot be used accurately for recommendation systems or other applications. This paper introduces a novel concept of the semantic-geographic pattern that considers both semantic and geographic meaning simultaneously. A flexible density-based clustering algorithm with a new trajectory similarity measurement called semantic intensity is used to mine these semantic-geographic patterns. Comparative experiments on check-in data from the Sina Weibo service demonstrate that semantic intensity can effectively measure both semantic and geographic similarities among trajectories. The resulting patterns are more accurate and easy to interpret.

入藏号：WOS:000407506900029

文献类型：Article

语种：English

作者关键词： trajectory pattern; semantic similarity; geographic similarity; pattern mining; clustering

扩展关键词： MOVEMENT DATA; DISTANCE; TIME; OBJECTS

通讯作者地址：Pei, T (通讯作者),Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

Pei, T (通讯作者),Univ Chinese Acad Sci, Beijing 100049, Peoples R China.

Pei, T (通讯作者),Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China.

电子邮件地址：wanyou9@gmail.com; zhouch@lreis.ac.cn; peit@lreis.ac.cn

地址：

[Wan, You] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

[Zhou, Chenghu; Pei, Tao] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

[Pei, Tao] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.

[Pei, Tao] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China.

研究方向：Physical Geography; Remote Sensing

ISSN：2220-9964

影响因子：0.371