DocumentCode :
259999
Title :
Smart Meeting System: An Approach to Recognize Patterns Using Tree Based Mining
Author :
Kose, Puja R. ; Bharne, Pankaj K.
Author_Institution :
Dept. of Comput. Sci. & Eng., SSGMCE, Shegaon, India
fYear :
2014
fDate :
22-24 Dec. 2014
Firstpage :
206
Lastpage :
208
Abstract :
Mining Human Interaction in Meetings is useful to identify how a person reacts in different situations. Behavior represents the nature of the person and mining helps to analyze, how the person express their opinion in meeting. For this, study of semantic knowledge is important. Human interactions in meeting are categorized as propose, comment, acknowledgement, ask opinion, positive opinion and negative opinion. The sequence of human interactions is represented as a Tree. Tree structure is used to represent the Human Interaction flow in meeting. Interaction flow helps to assure the probability of another type of interaction. Tree pattern mining and sub tree pattern mining algorithms are automated to analyze the structure of the tree and to extract interaction flow patterns. The extracted patterns are interpreted from human interactions. The frequent patterns are used as an indexing tool to access a particular semantics, and that patterns are clustered to determine the behavior of the person.
Keywords :
behavioural sciences; data mining; indexing; pattern clustering; tree data structures; ask opinion; human interaction flow pattern extraction; human interaction mining; negative opinion; pattern clustering; pattern recognition; person behavior; positive opinion; semantic knowledge; smart meeting system; subtree pattern mining algorithms; tree structure; Atmospheric measurements; Computer science; Data mining; Information technology; Particle measurements; Proposals; Semantics; Human interaction; Interaction Pattern; Interaction flow; Meeting; Tree based mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology (ICIT), 2014 International Conference on
Conference_Location :
Bhubaneswar
Print_ISBN :
978-1-4799-8083-3
Type :
conf
DOI :
10.1109/ICIT.2014.45
Filename :
7033323
Link To Document :
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