NDLI: A Dynamic Mobility Histogram Construction Method Based on Markov Chains

Content Provider	IEEE Xplore Digital Library
Author	Ishikawa, Y. Machida, Y. Kitagawa, H.
Copyright Year	2006
Description	Author affiliation: Nagoya Univ. (Ishikawa, Y.)
Abstract	With the recent progress of spatial information technologies and communication technologies, it has become easier to track positions of a large number of moving objects in real-time. Mobility statistics plays an important role in the interactive analysis of a large collection of moving objects trajectories and its use of movement pattern prediction. The development of an effective mobility statistics measure and its efficient computation method are critical issues. Thus, we propose an approach for constructing a mobility histogram to summarize a number of moving object trajectories. The histogram is based on a mobility statistics model called the Markov chain model. To facilitate an interactive analysis performed by a user, we provide a mobility histogram data cube-like logical representation and support an OLAP-style analysis. Since trajectory data is often received continuously as a trajectory stream, we have to support dynamic histogram construction and maintenance. We introduce a tree structure as the physical representation of a histogram and present histogram construction and maintenance methods that work efficiently within the given upper-bound size. We evaluate the performance and the precision of the proposed method by means of experiments
Starting Page	359
Ending Page	368
File Size	542245
Page Count	10
File Format	PDF
ISBN	0769525903
ISSN	15516393
DOI	10.1109/SSDBM.2006.7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-03
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Pattern analysis Statistics Spatial databases Data analysis Performance analysis Monitoring Query processing Context modeling Aggregates
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A dynamic mobility histogram construction method based on markov chains (2006)

The statistical method of closed-Euler histogram

New Sampling-Based Estimators for OLAP Queries

High performance analysis of big spatial data

Parallel data cube construction for high performance on-line analytical processing

Fast approximate query answering using precomputed statistics

Advanced a New Vector Data Query Optimization Method Based on Cost Function

A Histogram-Based Grey Estimator for Spatiotemporal Selective Queries

Interactive and Scalable Exploration of Big Spatial Data -- A Data Management Perspective

A Dynamic Mobility Histogram Construction Method Based on Markov Chains

Similar Documents

A dynamic mobility histogram construction method based on markov chains (2006)

The statistical method of closed-Euler histogram

New Sampling-Based Estimators for OLAP Queries

High performance analysis of big spatial data

Parallel data cube construction for high performance on-line analytical processing

Fast approximate query answering using precomputed statistics

Advanced a New Vector Data Query Optimization Method Based on Cost Function

A Histogram-Based Grey Estimator for Spatiotemporal Selective Queries

Interactive and Scalable Exploration of Big Spatial Data -- A Data Management Perspective

A Dynamic Mobility Histogram Construction Method Based on Markov Chains