Abstract
In this paper we present our work on semantic analysis of FBI News reports. In the paper we have considered the News which are of the immense significance for the analyst who want to analyze the News of specific area. With this definite analysis we are able to extract critical events or concepts described in News along with entities involved in the event. These entities include important actors of the event or concept, with location and temporal information. This information will help News analyzers to retrieve the information of interest efficiently.
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References
Shen, D., Lapata, M.: Using Semantic Roles to Improve Question Answering. In: Proceedings of Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 12–21. Association for Computational Linguistics (2007)
Avramidis, E., Koehn, P.: Enriching Morphologically Poor Languages for Statistical Machine Translation. In: Proceedings of ACL 2008, pp. 763–770. Association of Computational Linguistics (2008)
Surdeanu, M., Harabagiu, S., Williams, J., Aarseth, P.: Using Predicate-Argument Structures for Information Extraction. In: Proceedings of 41st Meeting on Association of Computational Linguistics, pp. 8–15 (2008)
Kulick, S., Bies, A., Liberman, M., Mandeland, M., McDonald, R., Palmer, M., Schein, A., Ungar, L.: Integrated Annotation for Biomedical Information Extraction. In: HLT-NAACL 2004 Workshop: Biolink 2004, pp. 61–68 (2004)
Carreras, X., Márquez, L.: Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling. In: Proceedings Conference on Computational Natural Language Learning (CoNLL 2005), pp. 152–164. Association for Computational Linguistics (2005)
Gildea, D., Jurafsky, D.: Automatic Labeling of Semantic Roles. Computational Linguistics 28(3), 245–288 (2008)
Björkelund, A., Bohnet, B., Hafdell, L., Nugues, P.: A High-performance Syntactic and Semantic Dependency Parser. In: Coling 2010: Demonstration Volume, pp. 33–36 (2010)
Tsai, R.T.H., Chou, Y.C., Su, Y.S., Lin, Y.C., Sung, C.L., Dai, H.J., Yeh, I.T.H., Ku, W.: S.T.Y., Hsu, W.L.: BIOSMILE: A Semantic Role Labeling System for Biomedical Verbs Using a Maximum-entropy Model with Automatically Generated Template Features. BMC 8(1) (2007)
Haji, J., Ciaramita, M., Johansson, R., et al.: The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages (2009)
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Nizamani, S., Memon, N. (2012). Semantic Analysis of FBI News Reports. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_40
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DOI: https://doi.org/10.1007/978-3-642-34478-7_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34477-0
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