Web Usage Mining is the application of data mining techniques to learn usage patterns from Web server log file in order to understand and better serve the requirements of web based applications. Web Usage Mining includes three most important steps namely Data Preprocessing, Pattern discovery and Analysis of the discovered patterns. One of the most important tasks in Web usage mining is to find ...

This paper presents a novel approach to improve the named entity translation by combining a transliteration approach with web mining, using web information as a source to complement transliteration, and using transliteration information to guide and enhance web mining. A Maximum Entropy model is employed to rank translation candidates by combining pronunciation similarity and bilingual contextu...

nowadays, world wide web has become a popular medium to search information, business, trading and so on. various organizations and companies are also employing the web in order to introduce their products or services around the world. therefore e-commerce or electronic commerce is formed. e-commerce is any type of business or commercial transaction that involves the transfer of information acro...

Similarity measurement between web services is a key solution to benefit from the reuse of the large number of web services freely available in the internet. This paper presents a practical approach that enables an effective measurement of web service similarity based on their interfaces descibed with WSDL. The approach relies on the use of multiple matching techniques and different semantic an...

Cloud computing are Internet-based services to increase the use and delivery models, usually involving the Internet to provide easy to dynamically scalable and often virtualized resources. To solve these problems, the proposed web data mining method based on cloud computing: the massive data mining tasks decomposed into parallel processing on multiple servers. Web fuzzy clustering of objects is...

<span lang="EN-US">The tremendous growth in the availability of enormous text data from a variety sources creates slew concerns and obstacles to discovering meaningful information. This advancement technology digital realm has resulted dispersion texts over millions web sites. Unstructured are densely packed with textual The discovery valuable intriguing relationships unstructured demands...

Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...

The rapid increase of web complexity and size makes web searched results far from satisfaction in many cases due to a huge amount of information returned by search engines. How to find intrinsic relationships among the web pages at a higher level to implement efficient web searched information management and retrieval is becoming a challenge problem. In this paper, we propose an approach to mea...

The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content. 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 a...

Nowadays, the management of sequential and temporal data is an increasing need in many data mining processes. Therefore, the development of new privacy preserving data mining techniques for sequential data is a crucial need to ensure that sequence data analysis is performed without disclosure sensitive information. Although data analysis and protection are very different processes, they share a...