Abstract
As a novel information retrieval task, opinion retrieval has attracted considerable amount of attention in recent years. Current researches mainly first computed the topic relevant and opinion relevant scores of the documents and then combined these two scores as the final ranking score using some combination function. One major problem in existing works is that the score combination functions are defined in advance regardless of domains. However, there is no evidence that these two scores should be combined in a unique way. In this paper, we propose to learn the combination functions automatically for retrieval tasks of different domains. We employ the popular Genetic Programming framework for the learning tasks. To perform the whole opinion retrieval task, we also design a novel opinion retrieval system to compute the topic and opinion relevant scores and then learn the optimal combination function to integrate the topic and opinion relevant scores. In the experiments, we compare our system with other state-of-the-art work on a public dataset and the experimental results show that our system performs comparatively with others.
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.
Similar content being viewed by others
References
Zhang, M., Ye, X.: A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval. In: Proceedings of SIGIR 2008, pp. 411–418 (2008)
Eguchi, K., Lavrenko, V.: Sentiment Retrieval using Generative Models. In: Proceedings of EMNLP 2006, pp. 345–354 (2006)
Mishne, G.: Multiple Ranking Strategies for Opinion Retrieval in Blogs. Online Proceedings of TREC (2006)
Yang, K., Yu, N., Valerio, A., Zhang, H.: WIDIT in TREC2006 Blog track. Online Proceedings of TREC (2006)
Liao, X., Cao, D., et al.: Combing Language Model with Sentiment Analysis for Opinoin Retreival of Blog-Post. Online Proceedings of TREC (2006)
Zhang, W., Yu, C.: UIC at TREC 2006 Blog Track. Online Proceedings of TREC (2006)
Mishne, G.: Using blog properties to improve retrieval. In: Proceedings of the International Conference on Weblogs and Social Media, ICSWM (2007)
He, B., Macdonald, C., He, J., Ounis, I.: An effective statistical approach to blog post opinion retrieval. In: Proceedings of CIKM 2008 (2008)
He, B., Macdonald, C., Ounis, I.: Ranking opinionated blog posts using OpinionFinder. In: Proceedings of SIGIR 2008 (2008)
Zhang, W., Yu, C., Meng, W.: Opinion retrieval from blogs. In: Proceedings of CIKM 2007 (2007)
Zhang, W., Jia, L., Yu, C., Meng, W.: Improve the effectiveness of the opinion retrieval and opinion polarity classification. In: Proceeding of CIKM 2008 (2008)
Ounis, I., de Rijke, M., Macdonald, C., Mishne, G., Soboroff, I.: Overview of the TREC 2006 Blog Track. Online Proceedings of TREC (2006)
Macdonald, C., Ounis, I.: Overview of the TREC 2007 Blog Track. Online Proceedings of TREC (2007)
Turney, P.D.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Proceedings of ACL 2002, pp. 417–424 (2002)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)
Shen, D., Pan, R., et al.: Q2C@UST: our winning solution to query classification in KDDCUP 2005. SIGKDD Explorations 7(2), 100–110 (2005)
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. The Journal of Machine Learning Research 3, 993–1022 (2003)
Hofmann, T.: Probabilistic Latent Semantic Analysis. In: Proceedings of UAI 1999 (1999)
Stone, P., Dunphy, D., Smith, M., Ogilvie, D.: The General Inquirer: A Computer Approach to Content Anaysis. MIT Press, Cambridge (1966)
Esuli, A., Sebastiani, F.: Determining the semantic orientation of terms through gloss classification. In: Proceedings of CIKM 2005, pp. 617–624 (2005)
Kullback, S., Leibler, R.A.: On Information and Sufficiency. The Annals of Mathematical Statistics 22(1), 79–86 (1951)
Hu, M., Liu, B.: Mining and Summarizing Customer Reviews. In: Proceedings of SIGKDD 2004 (2004)
Fan, W., Gordon, M.D., Pathak, P., Xi, W., Fox, E.A.: Ranking function optimization for effective web search by genetic programming: An empirical study. In: Proc. of HICSS 2004, Hawaii, pp. 105–112 (2004)
Lacerda, A., Cristo, M., Goncalves, M.A., Fan, W., Ziviani, N., Neto, B.R.: “Learning to advertise”. In: SIGIR 2006: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, New York, NY, USA, pp. 549–556 (2006)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Qiu, G., Zhang, F., Bu, J., Chen, C.: Domain Specific Opinion Retrieval. In: Proceedings of the Fifth Asia Information Retrieval Symposium, Japan (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, F., Qiu, G., Bu, J., Qu, M., Chen, C. (2009). Learning to Retrieve Opinions. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_57
Download citation
DOI: https://doi.org/10.1007/978-3-642-10467-1_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10466-4
Online ISBN: 978-3-642-10467-1
eBook Packages: Computer ScienceComputer Science (R0)