Online based Content Recommender System based on Consumer Behavior Modeling
Abstract: Online usages are growing in popularly. Nowadays Most of the peoples are purchasing the products in online shopping. There are various online websites are available in the Internet. This paper presents the study of Online Based Content Recommender System Based on Consumer Behavior Modeling. Web Surfing has become a popular activity for many consumers who not only make purchases online, but also seek relevant information on products and services before they commit to buy. The proposed system used a web recommender that models user habits and behaviors by constructing a knowledge base using temporal web access patterns as input. Fuzzy logic is applied to represent real-life temporal concepts and requested resources of periodic pattern-based web access activities. The fuzzy representation is used to construct a knowledge base of the user’s web access habits and behaviors, which is used to provide timely personalized recommendations to the user.
Keywords: Web recommender, Association Rule Mining, Fuzzy logic, Patterns, Personalized Recommendations
How to Cite?: K. Thenmozhi, D. Sridhar, "Online based Content Recommender System based on Consumer Behavior Modeling", Volume 2 Issue 3, March 2013, International Journal of Science and Research (IJSR), Pages: 9-11, https://www.ijsr.net/getabstract.php?paperid=IJSRON2013477, DOI: https://dx.doi.org/10.21275/IJSRON2013477