Network Information Retrieval Model Of The Web2.0 Environment

With the rich information resources collected and shared, Internet brings challenges to information retrieval. Though Search Engines have continually been improved, people have not satisfied the efficiency of retrieval. A new Internet revolution has been coming to us due to the out coming of Web2.0 in which Long Tail theory has replaced the status of 80/20 rule as the basic principle of the advance of Internet Business. The appearances and using of new technologies of Web2.0 such as Blog, RSS, Wiki, Tags, not merely brought the upgrading of the industry of the network, have brought enormous impact to old information retrieval. As to Web2.0, it has a lot of divergence with Web1.0. For instance, Web2.0 focuses on the concept of "everything based on user". In my view, the pattern of Internet Retrieval should make a change according to the environment of internet has changed a lot. The information retrieval with personalization, interaction, semantic characteristics reflected the inherent trends of Internet.Firstly, the paper gives an overview about Web2.0 from the concept, characteristics, and the major application, analyses its change in the area of information resource, the way of communication and the user's need. Then it points out the problem of old information retrieval, and discusses the reason why information retrieval in the context of Web2.0 should be changed. On this basis, the paper discusses the trend of information retrieval in the context of Web2.0. The main part of this paper analyses the information retrieval mode in Web2.0. It combines new technologies of Web2.0 with traditional information retrieval in order to improve efficiency and quality of information retrieval, by users' participating. It analyses some representative retrieval modes, and states some application examples, such as picture retrieval based on Tag, personalization information retrieval based on RSS, knowledge retrieval based on semantic Wiki. Finally, the paper compares them with traditional information retrieval under Web1.0 environment, and points out the superiority and insufficiency.