A social network algorithm for detecting communities from weighted graph in Web Usage Mining system
نویسندگان
چکیده
Web Usage Mining is the process of discovering user’s navigation pattern and predicting user’s behavior. The quantity of the Web usage data to be analyzed and its low quality are the principal problems in WUM. Several algorithms of data mining have been applied in order to extract the behaviors of the Web sites' users. In this present work, we have implemented a community detection technique in WUM process that is based on the modularity function and we have organized the preprocessed data as a weighted graph. The obtained results illustrate the aptitude of the proposed algorithm to determine a pertinent design of the web site from the discovered communities. Keywords— Data Mining, Web Usage Mining, log files, community discovery, weighted graph, social network, modularity.
منابع مشابه
Mining Overlapping Communities in Real-world Networks Based on Extended Modularity Gain
Detecting communities plays a vital role in studying group level patterns of a social network and it can be helpful in developing several recommendation systems such as movie recommendation, book recommendation, friend recommendation and so on. Most of the community detection algorithms can detect disjoint communities only, but in the real time scenario, a node can be a member of more than one ...
متن کاملDetecting Overlapping Communities in Social Networks using Deep Learning
In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...
متن کاملDiscovery and Analysis of Usage Patterns for Web Personalization
In this paper, we present a community discovery method based on information extraction from user sessions in order to find usage patterns. We have characterized the overall access from each page in the web site and have detected the pertinent users within communities using the potentially useful information available in different user sessions. Then we compare the proposed method with the rando...
متن کاملStudying Community Dynamics with an Incremental Graph Mining Algorithm
The widespread usage of the Web and later of the Web 2.0 for social interactions has stimulated scholars of different disciplines in studying electronic communities. Traditionally, communities are observed as a static phenomenon. However, they are evolving constellations, which emerge, lose members and obtain new ones and potentially, grow, coerce, split or decline. Such dynamic phenomena requi...
متن کاملWeb Usage Mining in Online Social Network
The web content in present scenario is mainly comprised of Social media systems such as blogs, photo and link sharing sites and on-line forums. . Web Usage Mining is the application of data mining techniques in the field of social networks to discover exciting usage patterns from SNS data and to serve the needs of SNS applications in a better manner. The major use of web usage mining techniques...
متن کامل