ChatTrack: Chat Room Topic Detection Using Classification
ChatTrack: Chat Room Topic Detection Using Classification
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DOI：
10.1007/978-3-540-25952-7_20
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发表时间：
2004-06
期刊：
影响因子：
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通讯作者：
Jason Bengel;Susan Gauch;Eera Mittur;Rajan Vijayaraghavan
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文献类型：
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作者：
Jason Bengel;Susan Gauch;Eera Mittur;Rajan Vijayaraghavan
对互联网聊天室讨论的传统分析给情报界带来了资源负担，因为监控数千个连续聊天会话需要时间。聊天室几乎可以用来讨论任何主题，包括计算机黑客攻击和炸弹制造，为犯罪分子合作创造了一个虚拟庇护所。鉴于人们对国土安全问题的兴趣高涨，我们开发了一种文本分类系统，该系统创建基于概念的配置文件，该配置文件代表聊天室或个人参与者讨论的主题的摘要。然后，我们讨论这个基本的聊天分析系统，并演示用对代理有意义的新概念选择性地扩充标准概念数据库的能力。最后，我们展示了调查员如何在通过个人资料收到感兴趣的用户或会话警报后，如何通过我们的聊天存档和搜索系统检索有关聊天会话的详细信息。
The traditional analysis of Internet chat room discussions places a resource burden on the intelligence community because of the time required to monitor thousands of continuous chat sessions. Chat rooms are used to discuss virtually any subject, including computer hacking and bomb making, creating a virtual sanctuary for criminals to collaborate. Given the upsurge of interest in homeland security issues, we have developed a text classification system that creates a concept-based profile that represents a summary of the topics discussed in a chat room or by an individual participant. We then discuss this basic chat profiling system and demonstrate the ability to selectively augment the standard concept database with new concepts of significance to an agent. Finally, we show how an investigator can, once alerted to a user or session of interest via the profile, retrieve details about the chat session through our chat archiving and search system.