1. How to submit my research paper? What’s the process of publication of my paper?
The journal receives submitted manuscripts via email only. Please submit your research paper in .doc or .pdf format to the submission email: jetwi@etpub.com.
2.Can I submit an abstract?
The journal publishes full research papers. So only full paper submission should be considered for possible publication. Papers with insufficient content may be rejected as well, make sure your paper is sufficient enough to be published...[Read More]

Applying Clustering Approach in Blog Recommendation

Zeinab Borhani-Fard1, Behrouz Minaei2, and Hamid Alinejad-Rokny3
1. School of Computer Engineering, University of Qom, Qom, Iran
2. School of Computer Engineering, Iran University of Science and Technology Tehran, Iran
3. School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW, Australia
Abstract—The web has met a significant growth in using weblogs during the recent years. According to the large amount of information in the weblogs, bloggers are facing difficulties to find blogs with similar thoughts and orientations and their popular information. While there is a vast overload of information for blogs, it necessitates having a blog recommender system. Collaborative filtering is a well-known technique in recommender systems. This technique extracts the relations between users and items in according to its neighbor’s ratings, and since users have rated just a small part of data, sparsity makes problems for collaborative filtering. This problem leads to an inaccurate comparison among users, and consequently it decreases the accuracy of collaborative filtering algorithms. The use of clustering technique decreases data sparsity and it improves system scalability. We have used clustering to recommend the blog while the blog have reciprocal role, and each blog is both as a user and as an item in the network. In this paper, we use graph clustering based on users’ information about social network and we propose blog recommendation framework to get recommendations. Experiments on ParsiBlog 1 data indicated that application of clustering technique with collaborative filtering is better performed that traditional collaborative filtering algorithms, PageRank and etc. A comparison between PageRank algorithm and clustering application showed that graph clustering in recommender system could makes better results in terms of accuracy, quickness and scalability.

Index Terms—blog networks, collaborative filtering, hybrid recommendation system, graph clustering  

Cite: Zeinab Borhani-Fard, Behrouz Minaei, and Hamid Alinejad-Rokny, "Applying Clustering Approach in Blog Recommendation," Journal of Emerging Technologies in Web Intelligence, Vol. 5, No. 3, pp. 296-301, August 2013. doi:10.4304/jetwi.5.3.296-301
Copyright © 2013-2020 Journal of Emerging Technologies in Web Intelligence, All Rights Reserved
E-mail: jetwi@etpub.com