Performance Optimization Of Web Topic Detection System

With the rapid development of the Internet, WWW has become the largest distributed information and knowledge database in the world. This development has on the one hand provided a good platform for the co-construction and sharing of information resources, on the other hand greatly increased the cost for information retrieving and knowledge acquiring, making it more and more difficult to look for information. As a new tool for information retrieval which is combined with filtering methods, the web topic detection is becoming a research hotspot in the web information searching.The deficiencies of searching engines, and breakthroughs needing to be made in information service are firstly analyzed here. It is pointed out that to develop topic-oriented intelligent detecting systems based on the Internet is the trend for developing a new generation of searching engines. Secondly, in order to improve the performance of the Web Topic Detection System, the paper introduces one performance optimization method, which is the TDT recognition model on event topic. Finally, the paper mainly discusses the automatic construction of event topic knowledge, and the topic searching system framework model has been set up according to existing topic detection systems.