Clustering Research Of Web Resource Based On Formal Concept Analysis

With the advances in information technology and network development, thereare various categories of information resources on the network, a wide variety ofnetwork information resources can be divided into a network database, the onlinecollection catalog, electronic publications, government agencies, information,entertainment and other information resources. A variety of information resources alsoappeared on the Internet in different forms and ways, the Web-site as a storage site inthe Internet. The Web resources are also subjected to the general resource by theInternet users. The Web information resources are loved and attentioned by themajority of Internet users. But, Web information resources scattered distribution, theclassification is not clear, garbage information too much led to user spend a lot of timeand energy on searching information. But they could not get a satisfactory result. Theproblem that users want to get valuable Web information resource is desire to besolved to the user’s information needs.Therefore, this article will cluster the recruiting Web resource. There are avariety of traditional clustering methods, according to different classification criteria,clustering can be divided into the hard clustering, the fuzzy clustering, the clustering,the dynamic clustering, the partition-based clustering, the density-based clustering,the network-based clustering, and so on. There are many clustering algorithms, suchas the K-means algorithm, the neural network algorithm, the PAM algorithm. Thisarticle has a comparative analysis of the various clustering algorithms which based onthe complexity of time, the data format. But, the application of traditional clusteringalgorithm on the recruitment Web resources, the clustering results are not satisfactory.Formal Concept Analysis as a concept lattice formed with the visual hasse map.The technology is widely used in knowledge retrieval, data mining and other fields.Therefore, the formal concept analysis and traditional clustering algorithm can becombined and applied to the clustering of the Web resources. The comparative analysis of the clustering tools which based on the formal concept analysis to identifythe best way of the clustering of the Web resource. After choosing the best clusteringtools to cluster the zhilian zhaopin Web resources in all aspects. Forming thevisualization clustering effect by the formal concept analysis to satificity the users’information needs and provid better information service for users.