| [1] Li D, Shuai X, Sun G, Tang J, Ding Y, Luo Z. Mining topiclevel opinion influence in microblog. In Proc. the 21st ACM International Conference on Information and Knowledge Management, Oct. 29-Nov. 2, 2012, pp.1562-1566.[2] Socher R, Perelygin A, Wu J Y, Chuang J, Manning C D, Ng A Y, Potts C. Recursive deep models for semantic compositionality over a sentiment treebank. In Proc. the 2013 Conference on Empirical Methods in Natural Language Processing, Oct. 2013, pp.1631-1642.[3] Poria S, Cambria E, Winterstein G, Huang G B. Sentic patterns:Dependency-based rules for concept-level sentiment analysis. Knowledge-Based Systems, 2014, 69:45-63.[4] Zhai Z, Liu B, Xu H, Jia P. Constrained LDA for grouping product features in opinion mining. In Proc. the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Part 1, May 2011, pp.448-459.[5] Cambria E, Mazzocco T, Hussain A, Eckl C. Sentic medoids:Organizing affective common sense knowledge in a multi-dimensional vector space. In Proc. the 8th International Symposium on Neural Networks, Part 3, May 29-Jun. 1, 2011, pp.601-610.[6] Cambria E, Hussain A, Havasi C, Eckl C, Munro J. Towards crowd validation of the UK national health service. In Proc. the Web Science Conference 2010, Apr. 2010.[7] Deshpande B. How to use clustering for product categorization or segmentation. Feb. 2013. http://www.simafore.com-/blog/bid/113689/How-to-use-clustering-for-product-categorization-or-segmentation, Aug. 2015.[8] Agirre E, Alfonseca E, Hall K, Kravalova J, Pasca M, Soroa A. A study on similarity and relatedness using distributional and WordNet-based approaches. In Proc. the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, May 31-Jun. 5, 2009, pp.19-27.[9] Carenini G, Ng R T, Zwart E. Extracting knowledge from evaluative text. In Proc. the 3rd International Conference on Knowledge Capture, Oct. 2005, pp.11-18.[10] Wagstaff K, Cardie C, Rogers S, Schrödl S. Constrained kmeans clustering with background knowledge. In Proc. the 18th International Conference on Machine Learning, Jun. 28-Jul. 1, 2001, pp.577-584.[11] Zhai Z, Liu B, Xu H, Jia P. Clustering product features for opinion mining. In Proc. the 4th International Conference on Web Search and Data Mining, Feb. 2011, pp.347-354.[12] Lin D, Wu X. Phrase clustering for discriminative learning. In Proc. the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Aug. 2009, pp.1030-1038.[13] Deerwester S, Dumais S T, Furnas G W, Landauer T K, Harshman R. Indexing by latent semantic analysis. Journal of the American Society for Information Science, 1990, 41(6):391-407.[14] Sahami M, Heilman T D. A web-based kernel function for measuring the similarity of short text snippets. In Proc. the 15th International Conference on World Wide Web, May 2006, pp.377-386.[15] Bu F, Zhu X, Li M. Measuring the non-compositionality of multiword expressions. In Proc. the 23rd International Conference on Computational Linguistics, Aug. 2010, pp.116-124.[16] Pantel P, Crestan E, Borkovsky A, Popescu A M, Vyas V. Web-scale distributional similarity and entity set expansion. In Proc. the 2009 Conference on Empirical Methods in Natural Language Processing, Aug. 2009, pp.938-947.[17] Andrzejewski D, Zhu X, Craven M. Incorporating domain knowledge into topic modeling via Dirichlet Forest priors. In Proc. the 26th Annual International Conference on Machine Learning, Jun. 2009, pp.25-32.[18] Zhao S, Liu T, Li S. A topical document clustering method. Journal of Chinese Information Processing, 2007, 21(2):58-62. (in Chinese)[19] Elsner M, Charniak E, Johnson M. Structured generative models for unsupervised named-entity clustering. In Proc. the 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, May 31-Jun. 5, 2009, pp.164- 172.[20] Andrews N, Eisner J, Dredze M. Robust entity clustering via phylogenetic inference. In Proc. the 52nd Annual Meeting of the Association for Computational Linguistics, Vol. 1:Long Papers, Jun. 2014, pp.775-785.[21] Green S, Andrewst N, Gormleyt M R, Dredzet M, Manning C D. Entity clustering across languages. In Proc. the 2012 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, Jun. 2012, pp.60-69.[22] Chen J, Zhao Z, Ye J, Liu H. Nonlinear adaptive distance metric learning for clustering. In Proc. the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2007, pp.123-132.[23] Li F, Han C, Huang M, Zhu X, Xia Y, Zhang S, Yu H. Structure-aware review mining and summarization. In Proc. the 23rd International Conference on Computational Linguistics, Aug. 2010, pp.653-661.[24] Zhang Y, Zhu W. Extracting implicit features in online customer reviews. In Proc. the 22nd International Conference on World Wide Web Companion, May 2013, pp.103-104. |