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Locational relativity and domain constraints in spatial questions

Published: 06 November 2012 Publication History

Abstract

Spatial queries in the form of natural language questions have typically been assumed to have unconstrained geographic answers. However, analysis of prototypical spatial questions reveals two important types of constraints that must be considered by spatial question answering systems. First, locational relativity constraints limit answers to a particular location or the user's implied location. Second, domain constraints specify non-geographic locations such as web pages or anatomical sites. In order to detect these constraints, we have conducted a crowd-sourced annotation effort for a set of over 1,200 questions gathered from a community question answering website. We utilize machine learning techniques trained on this data to automatically classify these two types of constraints. We report results nearing 90% accuracy at locational relativity detection and 76% accuracy at domain classification using this approach.

References

[1]
F. Bu, X. Zhu, Y. Hao, and X. Zhu. Function-based question classification for general QA. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1119--1128, 2010.
[2]
N. Cardoso, I. Dornescu, S. Hartrumpf, and J. Leveling. Revamping Question Answering with a Semantic Approach over World Knowledge. In M. Braschler, D. Harman, and E. Pianta, editors, CLEF 2010 LABs and Workshops, Notebook Papers. 2010.
[3]
R. Collobert and J. Weston. Deep Learning in Natural Language Processing. Tutorial at NIPS, 2009.
[4]
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. LIBLINEAR: A Library for Large Linear Classification. Journal of Machine Learning Research, 9:1871--1874, 2008.
[5]
C. Fellbaum, editor. WordNet: An Electronic Lexical Database. MIT Press, 1998.
[6]
A. Finn, N. Kushmerick, and B. Smyth. Genre Classification and Domain Transfer for Information Filtering. Advances in Information Retrieval, 2291:349--352, 2002.
[7]
S. Harabagiu, D. Moldovan, M. Pasca, R. Mihalcea, M. Surdeanu, R. Bunescu, R. Girju, V. Rus, and P. Morarescu. Falcon: Boosting Knowledge for Answer Engines. In Proceedings of the Ninth Text Retrieval Conference, 2000.
[8]
C. B. Jones and R. S. Purves. Geographical information retrieval. International Journal of Geographical Information Science, 22(3):219--228, 2008.
[9]
D. Klein and C. D. Manning. Accurate Unlexicalized Parsing. In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics, pages 423--430, 2003.
[10]
V. Krishnan, S. Das, and S. Chakrabarti. Enhanced answer type inference from questions using sequential models. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, 2005.
[11]
J. R. Landis and G. G. Koch. The Measurement of Observer Agreement for Categorical Data. Biometrics, 33:159--174, 1977.
[12]
R. R. Larson. Geographic Information Retrieval and Spatial Browsing. In L. C. Smith and M. Gluck, editors, Geographic Information Systems and Libraries: Patrons, Maps, and Spatial Information, pages 84--124. 1996.
[13]
X. Li and D. Roth. Learning question classifiers. In Proceedings of the 19th International Conference on Computational Linguistics, 2002.
[14]
T. Mandl, P. Carvalho, F. Gey, R. Larson, D. Santos, C. Womser-Hacker, G. D. Nunzio, and N. Ferro. GeoCLEF 2008: The CLEF 2008 Cross-Language Geographic Information Retrieval Track Overview. In C. Peters, T. Deselaers, N. Ferro, J. Gonzalo, G. J. Jones, M. Kurimo, T. Mandl, A. Penas, and V. Petras, editors, Evaluating Systems for Multilingual and Multimodal Information Access, 9th Workshop of the Cross-Language Evaluation Forum. 2009.
[15]
R. Navigli. Word sense disambiguation: A survey. In ACM Computing Surveys, volume 41, pages 1--69, 2009.
[16]
P. Petrenz. Cross-lingual genre classification. In Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics, pages 11--21, 2012.
[17]
C. Pinchak, D. Lin, and D. Rafiei. Flexible Answer Typing with Discriminative Preference Ranking. In Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, pages 666--674, 2009.
[18]
C. Pinchak and D. Lin. A Probabilistic Answer Type Model. In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, pages 393--400, 2006.
[19]
P. Pudil, J. Novovičová, and J. Kittler. Floating search methods in feature selection. Pattern Recognition Letters, 15:1119--1125, 1994.
[20]
D. Santos and L. M. Cabral. GikiCLEF: Expectations and Lessons Learned. Multilingual Information Access Evaluation I. Text Retrieval Experiments, 6241:212--222, 2010.
[21]
D. Santos, N. Cardoso, P. Carvalho, I. Dornescu, S. Hartrumpf, J. Leveling, and Y. Skalban. Getting geographical answers from Wikipedia: the GikiP pilot at CLEF. In F. Borri, A. Nardi, and C. Peters, editors, CLEF 2008 Working notes. 2008.
[22]
D. Santos, N. Cardoso, P. Carvalho, I. Dornescu, S. Hartrumpf, J. Leveling, and Y. Skalban. GikiP at GeoCLEF 2008: Joining GIR and QA forces for querying Wikipedia. In C. Peters, T. Deselaers, and N. F. et al., editors, Evaluating Systems for Multilingual and Multimodal Information Access, volume 5706, pages 894--905. 2009.
[23]
R. Snow, B. O'Connor, D. Jurafsky, and A. Y. Ng. Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 254--263, 2008.
[24]
E. M. Voorhees. Overview of TREC 2004. In Proceedings of the Thirteenth Text Retrieval Conference, 2004.
[25]
M. Wolters and M. Kirsten. Exploring the Use of Linguistic Features in Domain and Genre Classification. In Proceedings of the 9th Conference of the European Chapter of the Association for Computational Linguistics, pages 142--149, 1999.

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cover image ACM Conferences
SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems
November 2012
642 pages
ISBN:9781450316910
DOI:10.1145/2424321
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 November 2012

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Author Tags

  1. locational relativity
  2. query constraints
  3. spatial question answering

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