智能会议系统:基于树挖掘的模式识别方法

Puja R. Kose, P. K. Bharne
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引用次数: 0

摘要

挖掘会议中的人际互动有助于确定一个人在不同情况下的反应。行为代表了一个人的本性,挖掘有助于分析这个人在会议上如何表达自己的意见。为此,语义知识的研究就显得尤为重要。会议中的人际互动分为提议、评论、确认、询问意见、积极意见和消极意见。人类互动的序列被表示为一个树。采用树形结构表示会议中的人机交互流程。交互流有助于确保另一种类型交互的可能性。树模式挖掘和子树模式挖掘算法自动分析树的结构并提取交互流模式。提取的模式是从人类互动中解释的。频繁模式被用作访问特定语义的索引工具,并且该模式被聚类以确定该人的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Meeting System: An Approach to Recognize Patterns Using Tree Based Mining
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.
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