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Making intelligent business decisions by mining the implicit relation from bloggers’ posts

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Abstract

More and more people use blogs to write down their ideas, opinions and individual thoughts. Mining blogs will obtain useful information, which can support business policy and decision-making, especially in analyzing product popularity. In this study, we mine the features of persons as implicit relations between the content of the bloggers’ posts and the bloggers. These kinds of implicit relations, which are also semantic relations, is called the Blogger Role. To mine this semantic relation, Wordnet is used to extract the Blogger Role and the features of Blogger Role. To get an appropriate Blogger Role, we cluster all bloggers’ posts and use the clustering result to revise the Blogger Role obtained by single document analysis. To get more relevant retrieval results, we combine this implicit relation with the classical retrieval model by the Blogger Role-based model. The combination is performed by the explicit model and implicit model. Results of experiments on TREC corpus show that Blogger Role reveals bloggers’ characters and mining Blogger Roles is useful in analyzing the popularity of products.

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Acknowledgments

The work is supported by the National Natural Science Foundation of China (60873179 and 60803078) and the Technology Research Program of Fujian Province(2006H0037).

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Authors and Affiliations

  1. Department of Cognitive Science, Xiamen University, 361005, Xiamen, China

    Dazhen Lin, Shaozi Li & Donglin Cao

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  1. Dazhen Lin
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  2. Shaozi Li
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  3. Donglin Cao
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Correspondence to Shaozi Li.

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Lin, D., Li, S. & Cao, D. Making intelligent business decisions by mining the implicit relation from bloggers’ posts. Soft Comput 14, 1317–1327 (2010). https://doi.org/10.1007/s00500-009-0499-9

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