Traditional information retrieval method use keywords occurring in documents to determine the class of the documents, but usually retrieves unrelated web pages. In order to effectively classify web pages solving the synonymous keyword problem, we propose a web page classification based on support vector machine using a weighted vote schema for various features. The system uses both latent seman...

Besides the basic content, a web document also contains a set of hyperlinks pointing to other related documents. Hyperlinks in a document provide much information about its relation with other web documents. By analyzing hyperlinks in documents, inter-relationship among documents can be identi ed. In this paper, we will propose an algorithm to classify web documents into subsets based on hyperl...

During this quarter we have concentrated on the analysis of crossover data in Antarctica from both GLAS laser 1 and laser 2. The results of these analyses are presented below. Thomas Herring gave a talk on ICESat to the faculty of the Department of Earth, Atmospheric and Planetary Sciences on the day that Laser 2 was turned on. The talk has been added to the MIT ICESat web page (http://www-gpsg...

A web page is a complex document which can share conventions of several genres, or contain several parts, each belonging to a different genre. To properly address the genre interplay, a recent proposal in automatic web genre identification is multi-label classification. The dominant approach to such classification is to transform one multi-label machine learning problem into several sub-problem...

Assistance in retrieving documents on the World Wide Web is provided either by search engines, through keyword-based queries, or by catalogues, which organize documents into hierarchical collections. Maintaining catalogues manually is becoming increasingly difficult, due to the sheer amount of material on the Web; it is thus becoming necessary to resort to techniques for the automatic classific...