We have made a case here for utilizing tensor framework for hypertext mining. Tensor is a generalization of vector and tensor framework discussed here is a generalization of vector space model which is widely used in the information retrieval and web mining literature. Most hypertext documents have an inherent internal tag structure and external link structure that render the desirable use of m...

The development of learning objects (LO) and e-pedagogical practices has significantly influenced changed the performance e-learning systems. This promotes a genuine sharing resources creates new opportunities for learners to explore them easily. Therefore, need system categorization these becomes mandatory. In this vein, classification theories combined with web mining techniques can highlight...

Web mining is the use of data mining techniques to automatically discover and extract information from web documents This paper summarizes the different types of web mining, and their current states of the art. Keywords—Web Mining, World Wide Web, Web Content Mining, Web Structure Mining, Web Usage Mining.

Personalized recommenders have proved to be of use as a solution to reduce the information overload ‎problem. Especially in Adaptive Hypermedia System, a recommender is the main module that delivers ‎suitable learning objects to learners. Recommenders suffer from the cold-start and the sparsity problems. ‎Furthermore, obtaining learner’s preferences is cumbersome. Most studies have only focused...

Given that pairwise similarity computations are essential in ontology learning and data mining, we propose WebSim (Web-based term Similarity metric), whose feature extraction and similarity model is based on a conventional Web search engine. There are two main aspects that we can benefit from utilizing a Web search engine. First, we can obtain the freshest content for each term that represents ...

Measuring the similarity between documents is an essential operation in text mining, especially document clustering. The traditional method of finding the similarity between documents has always been based on extracting individual words from the documents, and using heuristics to give weights to those features. Standard methods in data mining are then used to find the similarity between documen...

Semantic Web Mining is the outcome of two new and fast developing domains: Semantic Web and Data Mining. The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Data Mining is the nontrivial process of identifying valid, previously unknown, potentially useful patterns in data. Semantic W...

Event extraction is a significant task in information extraction. This importance increases more and more with the explosion of textual data available on the Web, the appearance of Web 2.0 and the tendency towards the Semantic Web. Thus, we propose a generic approach to extract events from text and to analyze them. We propose an event extraction algorithm with a polynomial complexity O(n), and ...

As web is the largest collection of information and plenty of pages or documents, the World Wide Web has becoming one of the most valuable resources for information retrievals and knowledge discoveries. Web mining technologies are the right solutions for knowledge discovery on the Web. Web mining divides into web content, web structure and Web usage mining. In this paper, we focus on one of the...