Abstract
Blog has received lots of attention since the revolution of Web 2.0 and has attracted millions of users to publish information on it. As time goes by, information seeking in this new media becomes an emergent issue. In our paper, we take multiple features unique in blogs into account and propose a novel algorithm to rank the blog posts in blog search. Coherence between the query type and blogger interest, document relevance and freshness are combined linearly to produce the final ranking score of a post. Specifically, we introduce a user modeling method to capture interests of bloggers. In our experiments, we invite volunteers to complete several tasks and their time cost in the tasks is taken as the primary criteria to evaluate the performance. The experimental results show that our algorithm outperforms traditional ones.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank Citation Ranking: Bringing Order to the Web. Stanford Digital Libraries Working Paper (1999), http://www-diglib.stanford.edu
Fujimura, K., Toda, H., Inoue, T., Hiroshima, N.: BLOGRANGER-A Multi-faceted Blog Search Engine. In: Proceedings of the WWW 2006 Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (2006)
Fujimura, K., Inoue, T., Sugizaki, M.: The EigenRumor Algorithm for Ranking Blogs. In: Proceedings of the WWW 2005 Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics (2005)
Bloglines, http://www.bloglines.com
Blogpulse, http://www.blogpulse.com
Beeferman, D., Berger, A.: Agglomerative Clustering of a Search Engine Query Log. In: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 407–416 (2000)
Gravano, L., Hatzivassiloglou, V., Lichtenstein, R.: Categorizing Web Queries According to Geographical Locality. In: Proceedings of the twelfth international conference on Information and knowledge management, pp. 325–333 (2003)
Shen, D., Pan, R., Sun, J.-T., Pan, J.J., Wu, K., Yin, J., Yang, Q.: Q2C@UST: Our Winning Solution to Query Classification in KDDCUP 2005. In: ACM SIGKDD Explorations Newsletter, pp.100–110 (2005)
Beitzel, S.M., Jensen, E.C., Frieder, O., Grossman, D., Lewis, D.D., Chowdhury, A., Kolcz, A.: Automatic web query classification using labeled and unlabeled training data. In: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 581–582 (2005)
Eirinaki, M., Vazirgiannis, M.: Web mining for web personalization. ACM Transaction on Internet Technology 3(1), 1–27 (2003)
Mulvenna, M.D, Anand, S.S., Buchner, A.G.: Personalization on the Net using Web mining: introduction. Communications of the ACM 43(8), 122–125 (2000)
Middleton, S.E., Shadbolt, N.R., De Roure, D.C.: Ontological User Profiling in Recommender Systems. ACM Transactions on Information Systems (TOIS) 22(1), 54–88 (2004)
Webb, G.I., Pazzani, M.J., Billsus, D.: Machine Learning for User Modeling. User Modeling and User-Adapted Interaction 11(1-2), 19–29 (2004)
Mishne, G.: Multiple Ranking Strategies for Opinion Retrieval in Blogs. In: TREC 2006. Proceedings of the fifteenth Text Retrieval Conference (2006)
Mishne, G., de Rijke, M.: A study of blog search. In: Proceedings of ECIR 2006, pp. 289–301 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, K., Qiu, G., Bu, J., Chen, C. (2007). Ranking Using Multi-features in Blog Search. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_87
Download citation
DOI: https://doi.org/10.1007/978-3-540-77255-2_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77254-5
Online ISBN: 978-3-540-77255-2
eBook Packages: Computer ScienceComputer Science (R0)