Abstract
We propose a conceptual graph-based framework for abstractive text summarization. While syntactic or partial semantic representations of texts have been used in literature, complete semantic representations have not been explored for this purpose. We use a complete semantic representation, namely, conceptual graph structures, composed of concepts and conceptual relations. To summarize a conceptual graph, we remove the nodes that represent less important content, and apply certain operations on the resulting smaller conceptual graphs. We measure the importance of nodes on weighted conceptual graphs by the HITS algorithm, augmented with some heuristics based on VerbNet semantic patterns. Our experimental results are promising.
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References
Spärck Jones, K.: Automatic summarising: The state of the art. Information Processing & Management 43(6), 1449–1481 (2007)
Erkan, G., Radev, D.: LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. Journal of Artificial Intelligence Research 22(1), 457–479 (2004)
Mihalcea, R., Tarau, P.: TextRank: Bringing Order into Texts. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2004), Barcelona, Spain, pp. 404–411 (2004)
Leskovec, J., Grobelnik, M., Milic-Frayling, N.: Learning Semantic Graph Mapping for Document Summarization. In: Proceedings of ECML/PKDD 2004, Workshop on Knowledge Discovery and Ontologies, Pisa, Italy, pp. 1–6 (2004)
Kleinberg, J.: Authoritative Sources in a Hyperlinked Environment. Journal of the ACM 46(5), 604–632 (1999)
Litvak, M., Last, M.: Graph-based keyword extraction for single-document summarization. In: Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization, Manchester, United Kingdom, pp. 17–24 (2008)
Tsatsaronis, G., Varlamis, I., Nørvåg, K.: SemanticRank: ranking keywords and sentences using semantic graphs. In: Proceedings of the 23rd International Conference on Computational Linguistics, Beijing, China, pp. 1074–1082 (2010)
Sowa, J.F.: Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, Reading (1984)
DUC. Document Understanding Conference (2003), http://duc.nist.gov/pubs.html#2003
Hensman, S., Dunnion, J.: Automatically Building Conceptual Graphs Using VerbNet and WordNet. In: Proceedings of the 3rd International Symposium on Information and Communication Technologies, Las Vegas, USA, pp. 115–120 (2004)
Jackendoff, R.: Semantic Interpretation in Generative Grammar. MIT Press, Cambridge (1972)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Kipper, K., Trang Dang, H., Palmer, M.: Class-Based Construction of a Verb Lexicon. In: Proceedings of Seventeenth National Conference on Artificial Intelligence (AAAI 2000), Austin, TX, pp. 691–696 (2000)
Hovy, E., Chin-Yew, L.: Automating Text Summarization in SUMMARIST. In: Mani, I., Maybury, M.T. (eds.) Advances in Automatic Text Summarization, pp. 81–94. MIT Press, Cambridge (1999)
Chein, M., Mugnier, M.-L.: Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs. Springer, London (2009)
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Miranda-Jiménez, S., Gelbukh, A., Sidorov, G. (2013). Summarizing Conceptual Graphs for Automatic Summarization Task. In: Pfeiffer, H.D., Ignatov, D.I., Poelmans, J., Gadiraju, N. (eds) Conceptual Structures for STEM Research and Education. ICCS 2013. Lecture Notes in Computer Science(), vol 7735. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35786-2_18
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DOI: https://doi.org/10.1007/978-3-642-35786-2_18
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