A Description Logic based QSTR Framework for Recognizing Motion Patterns from Spatio-temporal Data

被引：0

作者：

Talukdar, Upasana ^{[1
]}

Barua, Rupam ^{[2
]}

Hazarika, Shyamanta M. ^{[1
]}

机构：

[1] Tezpur Univ, Biomimet & Cognit Robot Lab, Tezpur, Assam, India

[2] Jorhat Engn Coll, Dept Comp Sci & Engn, Jorhat, Assam, India

来源：

2015 IEEE 2ND INTERNATIONAL CONFERENCE ON RECENT TRENDS IN INFORMATION SYSTEMS (RETIS) | 2015年

关键词：

Qualitative Spatio-temporal Reasoning; Spatio-temporal; Description Logic; Motion Patterns;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Learning patterns from spatio-temporal data streams is an important problem within Artificial Intelligence. Knowledge is important for recognition of patterns. Representation of large and diverse knowledge requires formal basis. Description Logics (DLs) constitute a family of knowledge representation formalism which provide object-oriented representation with formal semantics. Qualitative spatial and temporal reasoning (QSTR) encompass efforts devoted to providing useful and well-grounded models to be used as high level qualitative descriptions of spatio-temporal change. In this paper we combine DL with QSTR and put forward a formal, explicit knowledge representation formalism for representation of motion patterns. Reasoning services of the DL system is used for recognizing motion patterns from spatio-temporal data.

引用

页码：38 / 43

页数：6

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