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Graph-Based Complex Representation in Inter-Sentence Relation Recognition in Polish Texts


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1. Aleixo, P., T. A. S. Pardo. Finding Related Sentences in Multiple Documents for Multidocument Discourse Parsing of Brazilian Portuguese Texts. – In: Companion Proc. of XIV Brazilian Symposium on Multimedia and the Web, WebMedia’08, New York, USA, 2008, ACM, pp. 298-303.10.1145/1809980.1810055Search in Google Scholar

2. Broda, B., M. Marcińczuk, M. Maziarz, A. Radziszewski, A. Wardyński. KPWr: Towards a Free Corpus of Polish. – In: Proc. of 8th International Conference on Language Resources and Evaluation (LREC’12), Istanbul, Turkey, May 2012, European Language Resources Association (ELRA), Nicoletta Calzolari (Conference Chair), Khalid Choukri, Thierry Declerck, Mehmet Uğur Doğan, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Eds.Search in Google Scholar

3. Broda, B., P. Kędzia, M. Marcińczuk, A. Radziszewski, R. Ramocki, A. Wardyński. Fextor: A Feature Extraction Framework for Natural Language Processing: A Case Study in Word Sense Disambiguation, Relation Recognition and Anaphora Resolution. – In: Computational Linguistics: Applications. Adam Przepiórkowski, Maciej Piasecki, Krzysztof Jassem, Piotr Fuglewicz, Eds. Berlin, Heidelberg, Springer, 2013, pp. 41-62.10.1007/978-3-642-34399-5_3Open DOISearch in Google Scholar

4. Bunke, H. On a Relation between Graph Edit Distance and Maximum Common Subgraph. – Pattern Recogn. Lett., Vol. 18, August 1997, No 9, pp. 689-694.10.1016/S0167-8655(97)00060-3Open DOISearch in Google Scholar

5. Bunke, H., K. Shearer. A Graph Distance Metric Based on the Maximal Common Subgraph. – Pattern Recogn. Lett., Vol. 19, March 1998, No 3-4, pp. 255-259.10.1016/S0167-8655(97)00179-7Open DOISearch in Google Scholar

6. Cardoso, P. C. F., E. G. Maziero, M. L. C. Jorge, E. R. M. Seno, A. Di Felippo, L. H. M. Rino, M. das G. V. Nunes, T. A. S. Pardo. CSTNews – A Discourseannotated Corpus for Single and Multi-Document Summarization of News Texts in Brazilian Portuguese. – In: Proc. of 3rd RST Brazilian Meeting, Cuiabá, Brazil, 2011, pp. 88-105.Search in Google Scholar

7. Fernández, M.-L., G. Valiente. A Graph Distance Metric Combining Maximum Common Subgraph and Minimum Common Supergraph. – Pattern Recogn. Lett., Vol. 22, May 2001, No 6-7, pp. 753-758.10.1016/S0167-8655(01)00017-4Open DOISearch in Google Scholar

8. Harary, F., R. C. Read. Is the Null-Graph a Pointless Concept? – In: Lecture Notes in Mathematics. Vol. 406. 1974, pp. 37-44.10.1007/BFb0066433Search in Google Scholar

9. Jaccard, P. The Distribution of the Flora in the Alpine Zone. – New Phytologist, Vol. 11, February 1912, No 2, pp. 37-50.10.1111/j.1469-8137.1912.tb05611.xOpen DOISearch in Google Scholar

10. Kędzia, P., M. Maziarz. Recognizing Semantic Relations within Polish Noun Phrase: A Rule-Based Approach. – In: RANLP, 2013.Search in Google Scholar

11. Kohavi, R. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. – In: Proc. of 14th International Joint Conference on Artificial Intelligence IJCAI’95, San Francisco, CA, USA, 1995. Morgan Kaufmann Publishers, Inc., Vol. 2, pp. 1137-1143.Search in Google Scholar

12. Kumar, Y. J., N. Salim, A. Hamza, A. Abuobieda. Automatic Identification of Cross-Document. – Structural Relationships, Vol. 7, 2012, pp. 26-29.10.1109/InfRKM.2012.6204977Search in Google Scholar

13. Kumar, Y. J., N. Salim, B. Raza. Cross-Document Structural Relationship Identification Using Supervised Machine Learning. – Appl. Soft Comput., Vol. 12, October 2012, No 10, pp. 3124-3131.10.1016/j.asoc.2012.06.017Search in Google Scholar

14. Kumar, Y. J., N. Salim, A. Abuobieda, A. T. Albaham. Multi Document Summarization Based on News Components Using Fuzzy Cross-Document Relations. – Applied Soft Computing, Vol. 21, 2014, pp. 265-279.10.1016/j.asoc.2014.03.041Open DOISearch in Google Scholar

15. Kędzia, P., M. Piasecki. Ruled-Based, Interlingual Motivated Mapping of plWordNet onto SUMO Ontology. – In: Proc. of 9th International Conference on Language Resources and Evaluation (LREC’14), Reykjavik, Iceland, 26-31 May 2014, Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asunción Moreno, Jan Odijk, Stelios Piperidis, Eds., pp. 4351-4358.Search in Google Scholar

16. Kędzia, P., M. Piasecki, J. Kocoń, A. Indyka-Piasecka. Distributionally Extended Network-Based Word Sense Disambiguation in Semantic Clustering of Polish Texts. – IERI Procedia, Vol. 10 (Complete), 2014, pp. 38-44.10.1016/j.ieri.2014.09.073Search in Google Scholar

17. Kędzia, P., M. Piasecki, M. Orlińska. Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources. – Cognitive Studies/Études Cognitives, Vol. 15, 2015, pp. 269-292. URL: https://ispan.waw.pl/journals/index.php/cs-ec/article/download/cs.2015.019/176510.11649/cs.2015.019Search in Google Scholar

18. Landwehr, N., M. Hall, E. Frank. Logistic Model Trees. – Machine Learning, Vol. 59, 2005, No 1, pp. 161-205. ISSN 1573-0565.10.1007/s10994-005-0466-3Search in Google Scholar

19. Marcińczuk, M. Automatic Construction of Complex Features in Conditional Random Fields for Named Entities Recognition. – In: RANLP, 2015.Search in Google Scholar

20. Marcińczuk, M., J. Kocoń, M. Janicki. Liner2 – A Customizable Framework for Proper Names Recognition for Polish. – In: Intelligent Tools for Building a Scientific Information Platform, Robert Bembenik, Łukasz Skonieczny, Henryk Rybiński, Marzena Kryszkiewicz, Marek Niezgódka, Eds., 2013, pp. 231-253.10.1007/978-3-642-35647-6_17Search in Google Scholar

21. Maziarz, M., M. Piasecki, E. Rudnicka, S. Szpakowicz, P. Kędzia. plWordNet 3.0 – A Comprehensive Lexical-Semantic Resource. – In: Proc. of 26th International Conference on Computational Linguistics, COLING 2016, Technical Papers, 11-16 December 2016, Osaka, Japan, pp. 2259-2268.Search in Google Scholar

22. Maziero, E. G., M. L. D.-R. C. Jorge, T. A. S. Pardo. Revisiting Cross-Document Structure Theory for Multidocument Discourse Parsing. – Inf. Process. Manage, Vol. 50, March 2014, No 2, pp. 297-314.10.1016/j.ipm.2013.12.003Search in Google Scholar

23. Nivre, J., J. Hall, J. Nilsson, A. Chanev, G. Eryigit, S. Kübler, S. Marinov, E. Marsi. MaltParser: A Language-Independent System for Data-Driven Dependency Parsing. – Natural Language Engineering, Vol. 13, 2007, No 2, pp. 95-135.10.1017/S1351324906004505Search in Google Scholar

24. Pease, A. Ontology: A Practical Guide. Angwin, CA, Articulate Software Press, 2011.Search in Google Scholar

25. Piasecki, M., S. Szpakowicz, B. Broda. A Wordnet from the Ground Up. – Oficyna Wydawnicza Politechniki Wroclawskiej, Wrocław, 2009.Search in Google Scholar

26. Piasecki, M., P. Kędzia, M. Orlińska. plWordNet in Word Sense Disambiguation Task. – In: Proc. of 8th Global Wordnet Conference (GWC’16), Bucharest, 27-30 January 2016, Osaka, Japan, pp. 280-290.Search in Google Scholar

27. Radev, D. R. A Common Theory of Information Fusion from Multiple Text Sources Step One: Cross-Document Structure. – In: Proc. of 1st SIGdial Workshop on Discourse and Dialogue, SIGDIAL’00, Association for Computational Linguistics, Stroudsburg, PA, USA, Vol. 10, 2000, pp. 74-83.10.3115/1117736.1117745Search in Google Scholar

28. Radev, D. R., J. Otterbacher, Z. Zhang. Cst Bank: A Corpus for the Study of Cross-Document Structural Relationships. – In: European Language Resources Association, LREC, 2004.Search in Google Scholar

29. Radziszewski, A. A Tiered CRF Tagger for Polish. Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, pp. 215-230. https://doi.org/10.1007/978-3-642-35647-6_1610.1007/978-3-642-35647-6_16Open DOISearch in Google Scholar

30. Radziszewski, A., A. Pawlaczek. Language Processing and Intelligent Information Systems. – In: Proc. of 20th International Conference, IIS 2013, Warsaw, Poland, 17-18 June 2013. Chapter Incorporating Head Recognition into a CRF Chunker, Berlin, Heidelberg, Springer, 2013, pp. 22-27.10.1007/978-3-642-38634-3_3Open DOISearch in Google Scholar

31. Radziszewski, A., A. Wardyński, T. Śniatowski. WCCL: A Morpho-Syntactic Feature Toolkit. – In: Proc. of Balto-Slavonic Natural Language Processing Workshop (BSNLP’11), Springer, 2011.10.1007/978-3-642-23538-2_55Search in Google Scholar

32. Steinwart, I., A. Christmann. Support Vector Machines. First Edition. Springer Publishing Company, Inc., 2008.Search in Google Scholar

33. Wallis, W. D., P. Shoubridge, M. Kraetz, D. Ray. Graph Distances Using Graph Union. – Pattern Recogn. Lett., Vol. 22, May 2001, No 6-7, pp. 701-704.10.1016/S0167-8655(01)00022-8Open DOISearch in Google Scholar

34. Woliński, M. Morfeusz – A Practical Tool for the Morphological Analysis of Polish. – In: Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Krzysztof Trojanowski, Eds. Intelligent Information Processing and Web Mining, Advances in Soft Computing, Berlin, Springer, 2006, pp. 503-512.Search in Google Scholar

35. Wróblewska, A., M. Woliński. Preliminary Experiments in Polish Dependency Parsing. Berlin, Heidelberg, Springer, 2012, pp. 279-292.10.1007/978-3-642-25261-7_22Search in Google Scholar

36. Wróblewska, A. Polish Dependency Parser Trained on an Automatically Induced Dependency Bank. Ph.D. Dissertation, Institute of Computer Science, Polish Academy of Sciences, Warsaw, 2014.Search in Google Scholar

37. Zahri, N. A. H. B., F. Fukumoto. Multi-Document Summarization Using Link Analysis Based on Rhetorical Relations between Sentences, Berlin, Heidelberg, Springer, 2011, pp. 328-338.10.1007/978-3-642-19437-5_27Search in Google Scholar

38. Zhang, Z., D. Radev. Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships. – In: Proc. of 1st International Joint Conference on Natural Language Processing, Berlin, Heidelberg, Springer, 2005, pp. 32-41.10.1007/978-3-540-30211-7_4Search in Google Scholar

39. Zhang, Z., J. Otterbacher, D. Radev. Learning Cross-Document Structural Relationships Using Boosting. – In: Proc. of 12th International Conference on Information and Knowledge Management (CIKM’03), ACM, New York, USA, 2003, pp. 124-130.10.1145/956863.956887Search in Google Scholar

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