In this paper we look at the deployment of web usage mining results within two key application areas of web measurement and knowledge generation for personalisation. We take a fresh look at the model of interaction between business and visitors to their web sites and the sources of data generated during these interactions. We then look at previous attempts at measuring the effectiveness of the ...

In this paper, we introduce a web mining solution to business intelligence to discover hidden patterns and business strategies from their customer and web data. We propose a new framework based on web mining technology. Web mining attempts to determine useful knowledge from secondary data obtained from the interactions of the users with the web. KeywordsData mining, Web Mining, Web Usage Mining,

In recent years, predicting the user's next request in web navigation has received much attention. An information source to be used for dealing with such problem is the left information by the previous web users stored at the web access log on the web servers. Purposed systems for this problem work based on this idea that if a large number of web users request specific pages of a website on a g...

-In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving content has become a very difficult task. One possible approach to solve problem is Web Usage Mining (WUM).Web mining is the application of data mining on web data and web usage mining is an important compo...

Massive amount of time series data are generated daily, in areas as diverse as astronomy, industry, sciences, and aerospace, to name just a few. One obvious problem of handling time series databases concerns with its typically massive size—gigabytes or even terabytes are common, with more and more databases reaching the petabyte scale. Most classic data mining algorithms do not perform or scale...

The Internet has unlimited resources of knowledge and is widely used in many applications. Web mining plays an important role in discovering such knowledge, it is roughly divided into three categories : Web Content Mining , Web Usage Mining and Web Structure Mining. The web consists of imprecise, incomplete and uncertain data and knowledge. Fuzzy Set Theory is often used to handle such data. Se...

Many practical applications are related to frequent sequential pattern mining, ranging from Web Usage Mining to Bioinformatics. To ensure an appropriate extraction cost for useful mining tasks, a key issue is to push the user-defined constraints deep inside the mining algorithms. In this paper, we study the search for frequent sequential patterns that are also similar to an user-defined referen...

Information retrieval is used to find a subset of relevant documents against a set of documents. Determining semantic similarity between two terms is a crucial problem in Web Mining for such applications as information retrieval systems and recommender systems. Semantic similarity refers to the sameness of two terms based on sameness of their meaning or their semantic contents. Recently many te...

Since the emergence in the popularity of XML for data representation and exchange over the Web, the distribution of XML documents has rapidly increased. Therefore it is a new challenge for the field of data mining to turn these documents into a more useful information utility. We present a novel clustering algorithm PCXSS that keeps the heterogeneous XML documents into various groups according ...