skip to main content
research-article

Tempo-HindiWordNet: A Lexical Knowledge-base for Temporal Information Processing

Authors Info & Claims
Published:14 December 2018Publication History
Skip Abstract Section

Abstract

Temporality has significantly contributed to various Natural Language Processing and Information Retrieval applications. In this article, we first create a lexical knowledge-base in Hindi by identifying the temporal orientation of word senses based on their definition and then use this resource to detect underlying temporal orientation of the sentences. To create the resource, we propose a semi-supervised learning framework, where each synset of the Hindi WordNet is classified into one of the five categories, namely, past, present, future, neutral, and atemporal. The algorithm initiates learning with a set of seed synsets and then iterates following different expansion strategies, viz. probabilistic expansion based on classifier’s confidence and semantic distance based measures. We manifest the usefulness of the resource that we build on an external task, viz. sentence-level temporal classification. The underlying idea is that a temporal knowledge-base can help in classifying the sentences according to their inherent temporal properties. Experiments on two different domains, viz. general and Twitter, show interesting results.

References

  1. Jean Adams and Daniel Nettle. 2009. Time perspective, personality and smoking, body mass, and physical activity: An empirical study. Brit. J. Health Psychol. 14, 1 (2009), 83--105.Google ScholarGoogle ScholarCross RefCross Ref
  2. Omar Alonso, Jannik Strötgen, Ricardo A. Baeza-Yates, and Michael Gertz. 2011. Temporal information retrieval: Challenges and opportunities. In Proceedings of the 1st International Temporal Web Analytics Workshop (TWAW’11). 1--8.Google ScholarGoogle Scholar
  3. Avishek Anand, Srikanta J. Bedathur, Klaus Berberich, and Ralf Schenkel. 2012. Index maintenance for time-travel text search. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval. 235--244. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Pushpak Bhattacharyya. 2010. IndoWordNet. In Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC’10). 3785--3792.Google ScholarGoogle Scholar
  5. Sudha Bhingardive, Dhirendra Singh, Rudramurthy V. Hanumant Harichandra Redkar, and Pushpak Bhattacharyya. 2015. Unsupervised most frequent sense detection using word embeddings. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 1238--1243.Google ScholarGoogle Scholar
  6. Ondrej Bojar, Vojtech Diatka, Pavel Rychlỳ, Pavel Stranák, Vít Suchomel, Ales Tamchyna, and Daniel Zeman. 2014. HindEnCorp-Hindi-English and Hindi-only corpus for machine translation. In Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC’14). 3550--3555.Google ScholarGoogle Scholar
  7. Ricardo Campos, Gaël Dias, Alípio M. Jorge, and Adam Jatowt. 2014. Survey of temporal information retrieval and related applications. ACM Comput. Survey 47, 2 (2014), 15:1--15:41. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Angel X. Chang and Christopher D. Manning. 2012. SUTime: A library for recognizing and normalizing time expressions. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC’12). 3735--3740.Google ScholarGoogle Scholar
  9. Leon Derczynski. 2017. Automatically Ordering Events and Times in Text. Studies in Computational Intelligence, Vol. 677. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Gaël Dias, Mohammed Hasanuzzaman, Stéphane Ferrari, and Yann Mathet. 2014. TempoWordNet for sentence time tagging. In Proceedings of the 23rd International Conference on World Wide Web (WWW’14). Geneva, Switzerland, 833--838. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Joseph L. Fleiss. 1971. Measuring nominal scale agreement among many raters. Psychol. Bull. 76, 5 (1971), 378--382.Google ScholarGoogle ScholarCross RefCross Ref
  12. Mohammed Hasanuzzaman, Gaël Dias, Stéphane Ferrari, and Yann Mathet. 2014. Propagation strategies for building temporal ontologies. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL’14). Gothenburg, Sweden, 6--11.Google ScholarGoogle ScholarCross RefCross Ref
  13. Mohammed Hasanuzzaman, Sabyasachi Kamila, Mandeep Kaur, Sriparna Saha, and Asif Ekbal. 2017. Temporal orientation of tweets for predicting income of users. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017. Vancouver, Canada, 659--665.Google ScholarGoogle ScholarCross RefCross Ref
  14. Ruihong Huang, Ignacio Cases, Dan Jurafsky, Cleo Condoravdi, and Ellen Riloff. 2016. Distinguishing past, on-going, and future events: The eventstatus corpus. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP’16). 44--54.Google ScholarGoogle ScholarCross RefCross Ref
  15. Thorsten Joachims. 2002. Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms.Kluwer Academic Publisher, Dordrecht, Netherlands. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. George H. John and Pat Langley. 1995. Estimating continuous distributions in Bayesian classifiers. In Proceedings of the 11th Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann, 338--345. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Hideo Joho, Adam Jatowt, Roi Blanco, Hajime Naka, and Shuhei Yamamoto. 2014. Overview of NTCIR-11 temporal information access (temporalia) task. In Proceedings of the 11th NTCIR Conference on Evaluation of Information Access Technologies (NTCIR’14). 429--437.Google ScholarGoogle Scholar
  18. Hideo Joho, Adam Jatowt, and Blanco Roi. 2013. A survey of temporal web search experience. In Proceedings of the 22nd International Conference on World Wide Web Companion. International World Wide Web Conferences Steering Committee, 1101--1108. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Sabyasachi Kamila, Asif Ekbal, and Pushpak Bhattacharyya. 2018. Sentence-level temporality detection using an implicit time-sensed resource. In Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC’18). 325--331.Google ScholarGoogle Scholar
  20. Nattiya Kanhabua, Roi Blanco, and Michael Matthews. 2011. Ranking related news predictions. In Proceedings of the 34th International ACM Conference on Research and Development in Information Retrieval (SIGIR’11). 755--764. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Anagha Kulkarni, Jaime Teevan, Krysta M. Svore, and Susan T. Dumais. 2011. Understanding temporal query dynamics. In Proceedings of the 4th ACM International Conference on Web Search and Data Mining (WSDM’11). 167--176. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Erdal Kuzey, Jannik Strötgen, Vinay Setty, and Gerhard Weikum. 2016. Temponym tagging: Temporal scopes for textual phrases. In Proceedings of the 25th International Conference Companion on World Wide Web. International World Wide Web Conferences Steering Committee, 841--842. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Inderjeet Mani, James Pustejovsky, and Robert Gaizauskas. 2005. The Language of Time: A Reader. Vol. 126. Oxford University Press.Google ScholarGoogle Scholar
  24. Miriam J. Metzger. 2007. Making sense of credibility on the web: Models for evaluating online information and recommendations for future research. J. Amer. Soc. Info. Sci. Technol. 58, 13 (2007), 2078--2091. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Donald Metzler, Rosie Jones, Fuchun Peng, and Ruiqiang Zhang. 2009. Improving search relevance for implicitly temporal queries. In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 700--701. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems. Curran Associates, Inc., 3111--3119. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Georges A. Miller. 1995. WordNet: A lexical database for English. Commun. ACM 38, 11 (1995), 39--41. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Dipawesh Pawar, Mohammed Hasanuzzaman, and Asif Ekbal. 2016. Building tempo-HindiWordNet: A resource for effective temporal information access in Hindi. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC’16). 3752--3759.Google ScholarGoogle Scholar
  29. Ross Quinlan. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. H. Andrew Schwartz, Johannes C. Eichstaedt, Margaret L. Kern, Lukasz Dziurzynski, Stephanie M. Ramones, Megha Agrawal, Achal Shah, Michal Kosinski, David Stillwell, Martin E. P. Seligman et al. 2013. Personality, gender, and age in the language of social media: The open-vocabulary approach. PloS One 8, 9 (2013), 1--16.Google ScholarGoogle Scholar
  31. H. Andrew Schwartz, Greg Park, Maarten Sap, Evan Weingarten, Johannes Eichstaedt, Margaret Kern, Jonah Berger, Martin Seligman, and Lyle Ungar. 2015. Extracting human temporal orientation in facebook language. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics-Human Language Technologies (NAACL’15). 409--419.Google ScholarGoogle ScholarCross RefCross Ref
  32. Jannik Strötgen and Michael Gertz. 2015. A baseline temporal tagger for all languages. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP’15), Vol. 15. 541--547.Google ScholarGoogle ScholarCross RefCross Ref
  33. Jannik Strötgen and Michael Gertz. 2016. Domain-sensitive temporal tagging. Synth. Lect. Hum. Lang. Technol. 9, 3 (2016), 1--151.Google ScholarGoogle ScholarCross RefCross Ref
  34. Lars Sthle and Svante Wold. 1989. Analysis of variance (ANOVA). Chemometr. Intell. Lab. Syst. 6, 4 (1989), 259--272.Google ScholarGoogle ScholarCross RefCross Ref
  35. Naushad UzZaman, Hector Llorens, Leon Derczynski, James Allen, Marc Verhagen, and James Pustejovsky. 2013. SemEval-2013 task 1: TempEval-3: Evaluating time expressions, events, and temporal relations. In Proceedings of the 2nd Joint Conference on Lexical and Computational Semantics. 1--9.Google ScholarGoogle Scholar
  36. Marc Verhagen, Robert Gaizauskas, Frank Schilder, Mark Hepple, Jessica Moszkowicz, and James Pustejovsky. 2009. The tempeval challenge: Identifying temporal relations in text. Lang. Res. Eval. 43, 2 (2009), 161--179.Google ScholarGoogle ScholarCross RefCross Ref
  37. Marc Verhagen, Roser Saurí, Tommaso Caselli, and James Pustejovsky. 2010. SemEval-2010 task 13: TempEval-2. In Proceedings of the 5th International Workshop on Semantic Evaluation ([email protected]’10). 57--62. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Paul Webley and Ellen K. Nyhus. 2006. Parents’ influence on children’s future orientation and saving. J. Econ. Psychol. 27, 1 (2006), 140--164.Google ScholarGoogle ScholarCross RefCross Ref
  39. Ruiqiang Zhang, Yuki Konda, Anlei Dong, Pranam Kolari, Yi Chang, and Zhaohui Zheng. 2010. Learning recurrent event queries for web search. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, Cambridge, MA, 1129--1139. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Philip G. Zimbardo and John N. Boyd. 2015. Putting time in perspective: A valid, reliable individual-differences metric. In Time Perspective Theory; Review, Research and Application. Springer, Berlin, 17--55.Google ScholarGoogle Scholar

Index Terms

  1. Tempo-HindiWordNet: A Lexical Knowledge-base for Temporal Information Processing

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      HTML Format

      View this article in HTML Format .

      View HTML Format
      About Cookies On This Site

      We use cookies to ensure that we give you the best experience on our website.

      Learn more

      Got it!