Multiple-Aspect Analysis of Semantic Trajectories : First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings / edited by Konstantinos Tserpes, Chiara Renso, Stan Matwin.

Format:

Book

Contributor:

Tserpes, Konstantinos, editor.

Renso, Chiara, 1968- editor.

Matwin, Stan, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 11889.

Lecture Notes in Artificial Intelligence ; 11889

Language:

English

Subjects (All):

Machine learning.

Application software.

Optical data processing.

Machine Learning.

Computer Applications.

Image Processing and Computer Vision.

Local Subjects:

Machine Learning.

Computer Applications.

Image Processing and Computer Vision.

Physical Description:

1 online resource (IX, 133 pages) : 93 illustrations, 47 illustrations in color.

Edition:

First edition 2020.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full papers presented were carefully reviewed and selected from 12 submissions. They represent an interesting mix of techniques to solve recurrent as well as new problems in the semantic trajectory domain, such as data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification.

Contents:

Learning from our Movements - The Mobility Data Analytics Era

Uncovering hidden concepts from AIS data: A network abstraction of maritime traffic for anomaly detection

Nowcasting Unemployment Rates with Smartphone GPS data

Online long-term trajectory prediction based on mined route patterns

EvolvingClusters: Online Discovery of Group Patterns in Enriched Maritime Data

Prospective Data Model and Distributed Query Processing for Mobile Sensing Data Streams

Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning

A Neighborhood-augmented LSTM Model for Taxi-Passenger Demand Prediction

Multi-Channel Convolutional Neural Networks for Handling Multi-Dimensional Semantic Trajectories and Predicting Future Semantic Locations.

Other Format:

Printed edition:

ISBN:

978-3-030-38081-6

9783030380816

Access Restriction:

Restricted for use by site license.