In Web personalization usage mining has been used in combination of standard methods to help predict user needs based on their transaction histories. Although information in usage logs of a Web server reflects the interests of users to the site, the users are potentially not aware of all information needs that can be addressed through the Web server. User data (content) is a valuable source for...

Data on the Web is noisy, huge, and dynamic. This poses enormous challenges to most data mining techniques that try to extract patterns from this data. While scalable data mining methods are expected to cope with the size challenge, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stoppages and reconfigurations is still an open challenge. This dynam...

Mining user patterns of log files can provide significant and useful informative knowledge. This paper present an approach for mining similarity of interest among web users from their past access behaviors. Unlike traditional clustering methods that focus on grouping objects with similar values on a set of dimensions, clustering by pattern similarity finds objects that exhibit a coherent patter...

Most of the document clustering techniques are based on statistical analysis of a term, either a word or phrase.The statistical analysis of a term frequency captures the importance of the term within the document only. Thus, the underlying mining model should indicate terms that capture the semantics of the text. In this case, The mining model can capture terms that present the concepts of the ...

Measures of similarity between two terms or concepts have been widely used in the domain of Natural Language Processing, Semantic Web, and so on. There are mainly two kinds of methods for measuring similarity. One is based on prior manually built taxonomy or Ontology; the other which is usually referred to as the statistical approaches is based on the corpus. However, the ontology-based method ...

Web itself contains a large amount of documents available in electronic form. The available documents are in various forms and the information in them is not in organized form. The lack of organization of materials in the WWW motivates people to automatically manage the huge amount of information. Textmining refers generally to the process of extracting interesting and non-trivial information a...

Nowadays high fuzzy utility based pattern mining is an emerging topic in data mining. It refers to discover all patterns having a high utility meeting a user-specified minimum high utility threshold. It comprises extracting patterns which are highly accessed in mobile web service sequences. Different from the traditional fuzzy approach, high fuzzy utility mining considers not only counts of mob...

Measuring structural similarity between XML documents has become a key component in various applications, including XML mining, schema matching, and web service discovery, among others. This paper presents a novel structural similarity measure incorporating kernel methods into XML documents. Results on preliminary simulations show that this approach outperforms conventional ones.

Mining the Social Web by Matthew Russell is a delightful reading which covers a wide array of very pertinent social media technologies. When working in the field of social media and web mining, one comes across a plethora of buzz words, tools and techniques to do various web data analysis tasks. This book does a great job at demystifying these topics. What I liked most about Mining the Social W...