Have you read any paper published in the ACM Transactions on Internet Technology (TOIT) journal? This month, while I was browsing through the ACM DL, I came across a very interesting paper published in this journal, entitled "An online blog reading system by topic clustering and personalized ranking. This paper proposes an online Personalized Blog Reader (PBR) system that supports readers browsing the latest posts of blogs that match their interests by automatically clustering the most relevant stories. Even though the proposed reader is not directly related to accessibility, I guess you will agree with me that sometimes it becomes difficult to find interesting blog posts. Therefore such systems that learn people's personalized reading preferences and present a user with a final reading list would be useful. Furthermore, their algorithm could also be generalised and used for improving the browsing experience of disabled Web users.

An online blog reading system by topic clustering and personalized ranking

There is an increasing number of people reading, writing, and commenting on blogs. According to a recent survey made by Technorati, there are about 75,000 new blogs and 1.2 million new posts everyday. However, it is difficult and time consuming for a blog reader to find the most interesting posts in the huge and dynamic blog world. In this article, an online Personalized Blog Reader (PBR) system is proposed, which facilitates blog readers in browsing the coolest and newest blog posts of their interests by automatically clustering the most relevant stories. PBR aims to make a user's potential favorite topics always ranked higher than those nonfavorite ones. This is accomplished in the following steps. First, the system collects and provides a unified incremental index of posts coming from different blogs. Then, an incremental clustering algorithm with a flexible half-bounded window of observation is proposed to satisfy the requirements of online processing. It learns people's personalized reading preferences to present a user with a final reading list. The experimental results show that the proposed incremental clustering algorithm is effective and efficient, and the personalization of the PBR performs well.

Full Paper: http://doi.acm.org/10.1145/1552291.1552292 Full Proceedings: Li, X., Yan, J., Fan, W., Liu, N., Yan, S., and Chen, Z. 2009. An online blog reading system by topic clustering and personalized ranking. ACM Transactions on Internet Technology (TOIT), 9, 3, Article 9 (July 2009).

Labels: Blogging, Personalisation, TOIT