Smart Meeting System: An Approach to Recognize Patterns Using Tree Based Mining

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.