SemTraClus: an algorithm for clustering and prioritizing semantic regions of spatio-temporal trajectories

ABSTRACT

The widespread acceptance of context-sensing applications is generating voluminous movement data on high speed, which has fueled research studies in mining of spatio-temporal trajectories. The analysis of space–time points in trajectory gives insightful knowledge on the pattern of the mobility of the object and on the interest evinced by visitors in a geographic location. Significant locations of a geographical area, called Points of Interests, are extracted by means of spatial and temporal features of the moving object and enriching them with semantic information is a new trend in spatio-temporal data mining. In this paper, an algorithm called SemTraClus is proposed for identifying and clustering the semantic subtrajectories of moving traces of multiple objects. The semantic regions are clustered using the DBSCAN method. Finally, it generates a Weightage Participation value which provides priorities of user interest in different semantic cluster regions. It also identifies the most representative user trajectory that has traveled through relevant locations. To the best of our knowledge, this is the first work that clusters multiple trajectories for the identification of semantic points, considering spatial and temporal features simultaneously and providing prioritized location list. Experiments show that the proposed algorithm achieved good results in identifying significant locations and prioritizing it.

KEYWORDS:

• Location-based systems
• semantic trajectory
• spatio-temporal clustering
• spatio-temporal data analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

A. Nishad

Mr. A. Nishad (M.C.A., M.Tech) is a research scholar in School of Computer Sciences, Mahatma Gandhi University. His area of research includes Bigdata Analysis, Moving Object Data Mining, and Trajectory Clustering. He has published nine papers in International and National journals and conference proceedings.

Sajimon Abraham

Sajimon Abraham (M.C.A., M.Sc. (Mathematics), M.BA., Ph.D. (Computer Science)) has been working as Faculty Member in Computer Applications & IT, School of Management and Business Studies, Mahatma Gandhi University, Kottayam, Kerala, India. He currently holds the additional charge of Director (Hon), University Center for International Co-operation. He was previously working as Systems Analyst in Institute of Human Resource Development and Database Architect in Royal University of Bhutan under Colombo Plan on deputation through Ministry of External Affairs, Govt of India. His research area includes Data Science, Spatio-Temporal Databases, Mobility Mining, Sentiment Analysis, Big Data Analytics, and E-learning and has published 60 articles in National, International Journals and Conference Proceedings.