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Cluster Computing

Erschienen in:

01.03.2015

A blog ranking algorithm using analysis of both blog influence and characteristics of blog posts

verfasst von: Jiwon Kim, Unil Yun, Gwangbum Pyun, Heungmo Ryang, Gangin Lee, Eunchul Yoon, Keun Ho Ryu

Erschienen in: Cluster Computing | Ausgabe 1/2015

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Abstract

In recent years, with the increasing number of blogs to share information, the ratio of blogs on the World Wide Web has been raised. In this regard, the problem of information quality has come up due to the rapidly increasing amount of information in a blogosphere. Therefore, discovering good quality information is one of the significant issues in the blog space. In this paper, we propose an algorithm for efficient blog ranking, called WCT (a blog ranking algorithm using Weighted Comments and Trackbacks). This method performs a ranking process through not only interconnection analysis of blogs but also structural weights for contents in the blogs. Moreover, we conduct performance evaluation and discuss the performance between our algorithm and a previous algorithm by comparing their experimental results, which show that our approach has higher performance than that of the other blog retrieval method.

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Titel: A blog ranking algorithm using analysis of both blog influence and characteristics of blog posts
verfasst von: Jiwon Kim
Unil Yun
Gwangbum Pyun
Heungmo Ryang
Gangin Lee
Eunchul Yoon
Keun Ho Ryu
Publikationsdatum: 01.03.2015
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe 1/2015
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-013-0337-9

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