emnlp emnlp2011 emnlp2011-29 emnlp2011-29-reference knowledge-graph by maker-knowledge-mining
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Author: Zheng Chen ; Heng Ji
Abstract: In this paper, we present a new ranking scheme, collaborative ranking (CR). In contrast to traditional non-collaborative ranking scheme which solely relies on the strengths of isolated queries and one stand-alone ranking algorithm, the new scheme integrates the strengths from multiple collaborators of a query and the strengths from multiple ranking algorithms. We elaborate three specific forms of collaborative ranking, namely, micro collaborative ranking (MiCR), macro collaborative ranking (MaCR) and micro-macro collab- orative ranking (MiMaCR). Experiments on entity linking task show that our proposed scheme is indeed effective and promising.
P. L. Bartlett, M. I. Jordan and J. D. McAuliffe. 2003. Convexity, classification, and risk bounds. Technical Report 638, Statistics Department, University of California, Berkeley. C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender. 2005. Learning to Rank Using Gradient Descent. In Proceedings of the 22th International Conference on Machine Learning (ICML 2005). Z. Cao, T. Qin, T.-Y. Liu, M.-F. Tsai and H. Li. 2007. Learning to rank: from pairwise approach to listwise approach In Proceedings of the 24th International Conference on Machine Learning (ICML 2007), pages 129-136. E. Charniak and M. Johnson. 2005. Coarseto-finegrained n-best parsing and discriminative reranking. In ACL-05, pages 173-180. W. Chen, T.-Y. Liu, Y. Lan, Z. Ma, and H. Li. 2009. Ranking measures and loss functions in learning to rank. In Advances in Neural Information Processing Systems 22 (NIPS 2009), pages 315-323. Z. Chen, S. Tamang, A. Lee, X. Li, W.-P. Lin, M. Snover, J. Artiles, M. Passantino and H. Ji. 2010. CUNYBLENDER TAC-KBP2010 Entity Linking and Slot Filling System Description. In Proceedings ofTextAn- alytics Conference (TAC2010). Z. Chen, S. Tamang, A. Lee and H. Ji. 2011. A Toolkit for Knowledge Base Population. In SIGIR. M. Collins. 2000. Discriminative reranking for natural language parsing. In Proceedings of the 17th International Conference on Machine Learning (ICML 2000), pages 175-182. M. Dredze, P. McNamee, D. Rao, A. Gerber and T. Finin. 2010. Entity Disambiguation for Knowledge Base Population. In Proc. COLING 2010. Y. Freund, R. Iyer, R. Schapire, and Y. Singer. 2003. An efficient boosting algorithm for combining preferences. In Journal of Machine Learning Research, 4:933-969. S. Hoi and R. Jin. 2008. Semi-supervised ensemble ranking. In Proc. of the 23rd AAAI Conf. on Artificial Intelligence. L. Huang. 2008. Forest Reranking: Discriminative Parsing with Non-Local Features. In ACL-HLT-08, pages 586-594. H. Ji, R. Grishman, H. T. Dang and K. Griffit. 2010. An Overview of the TAC2010 Knowledge Base Population Track. In Proceedings of Text Analytics Conference (TAC2010). T. Joachims. 1999. Making large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning, B. Sch o¨lkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999. T. Joachims. 2002. Optimizing search engines using clickthrough data. In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD 2002). T. Joachims. 2006. Training Linear SVMs in Linear Time. In Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD). Y. Lan, T.-Y. Liu, T. Qin, Z. Ma, and H. Li. 2008. Querylevel stability and generalization in learning to rank. In Proceedings of the 25th International Conference on Machine Learning (ICML 2008), pages 5 12-5 19. P. Li, C. Burges, and Q. Wu. 2007. Mcrank: Learning to rank using multiple classification and gradient boosting In Advances in Neural Information Processing Systems 20 (NIPS2007). Y. Lin. 2002. Support vector machines and the bayes rule in classification. In Data Mining and Knowledge Discovery, pages 259-275. C. D. Manning, P. Raghavan and H. Sch u¨tze. 2008 . Introduction to Information Retrieval. Cambridge University Press. P. McNamee and H. Dang. 2009. Overview of the TAC 2009 Knowledge Base Population Track. In Proceedings of TAC. R. Nallapati. 2004. Discriminative models for information retrieval. In SIGIR. F. J. Och. 2002. Statistical Machine Translation: From Single-Word Models to Alignment Templates. Ph.D. thesis, Computer Science Department, RWTH Aachen, Germany, October. L. Page, S. Brin, R. Motwani, and T. Winograd. 1998. The PageRank Citation Ranking: Bringing Order to the Web. Technical report, Stanford Digital Library Technologies Project. T. Qin, X.-D. Zhang, M.-F. Tsai, D.-S. Wang, T.-Y. Liu and H. Li. 2007. Query-level loss functions for information retrieval. In Information Processing and Management. T. Qin, T.-Y. Liu, X.-D. Zhang,D.-S. Wang, and H. Li. 2008. Global Ranking Using Continuous Conditional Random Fields. In Advances in Neural Information Processing Systems 21 (NIPS 2008). D. Ravichandran, E. Hovy and F. J. Och. 2003. Statistical QA - Classifier vs. Re-ranker: What’s the difference? In Proceedings of the ACL Workshop on Multilingual Summarization and Question Answering. 781 S. Riezler, A. Vasserman, I. Tsochantaridis, V. Mittal and Y. Liu. 2007. Statistical Machine Translation for Query Expansion in Answer Retrieval. In Proceedings of ACL. L. Rokach. 2009. Ensemble-based classifiers. Artif Intell Rev DOI 10.1007/s10462-009-9124-7. L. Shen, A. Sarkar, and F. J. Och. 2005. Discriminative reranking for machine translation. In Proceedings of HLT-NAACL. J. Shi and J. Malik. 2000. Normalized Cuts and Image Segmentation. In Machine Intelligence, vol. 22, no. 8, pages 888-905. F. Wei, W. Li and S. Liu. 2010. iRANK: A rank-learncombine framework for unsupervised ensemble ranking. In Journal of the American Society for Information Science and Technology,61 : 1232C1243. doi: 10.1002/asi.21296. X. Yang and J. Su and C.L. Tan 2008. A Twin-Candidate Model for Learning-based Anaphora Resolution. In Computational Linguistics, vol. 34, no. 3, pages 327356. M. Yoshida, M. Ikeda, S. Ono, I. Sato, and H. Nakagawa. 2010. Person name disambiguation by boostrapping. In SIGIR. T. Zhang. 2004. Statistical analysis of some multicategory large margin classification methods. In Journal of Machine Learning Research, 5, 1225-125 1. W. Zhang, J. Su, C. L. Tan and W.T. Wang. 2010. Entity Linking Leveraging Automatically Generated Annotation. In Proc. COLING 2010. Z. Zheng, F. Li, M. Huang, X. Zhu. 2010. Learning to Link Entities with Knowledge Base. In Proc. HLTNAACL2010.