Defining the Factors that Effect User Interest on Social Network News Feeds via Fuzzy Association Rule Mining

Defining the Factors that Effect User Interest on Social Network News Feeds via Fuzzy Association Rule Mining

Author: 
Öztaysi, Basar
Place: 
Hershey, PA
Publisher: 
IGI Global
Date published: 
2013
Responsibility: 
Onar, Sezi Çevik, jt. author
Editor: 
Bhatnagar, Vishal
Journal Title: 
Data Mining in Dynamic Social Networks and Fuzzy Systems
Source: 
Data Mining in Dynamic Social Networks and Fuzzy Systems
Subject: 
Abstract: 

Social networking became one of the main marketing tools in the recent years since it's a faster and cheaper way to reach the customers. Companies can use social networks for efficient communication with their current and potential customers but the value created through the usage of social networks depends on how well the organizations use these tools. Therefore a support system which will enhance the usage of these tools is necessary. Fuzzy Association rule mining (FARM) is a commonly used data mining technique which focuses on discovering the frequent items and association rules in a data set and can be a powerful tool for enhancing the usage of social networks. Therefore the aim of the chapter is to propose a fuzzy association rule mining based methodology which will present the potential of using the FARM techniques in the field of social network analysis. In order to reveal the applicability, an experimental evaluation of the proposed methodology in a sports portal will be presented.

Series: 
Advances in Data Mining and Database Management

CITATION: Öztaysi, Basar. Defining the Factors that Effect User Interest on Social Network News Feeds via Fuzzy Association Rule Mining edited by Bhatnagar, Vishal . Hershey, PA : IGI Global , 2013. Data Mining in Dynamic Social Networks and Fuzzy Systems - Available at: https://library.au.int/defining-factors-effect-user-interest-social-network-news-feeds-fuzzy-association-rule-mining