Acquisition of Know-How Information from Web
A variety of know-how such as recipes and solutions for troubles have been stored on the Web. However, it is not so easy to appropriately find certain know-how information. If know-how could be appropriately detected, it would be much easier for us to know how to tackle unforeseen situations such as accidents and disasters. This paper proposes a promising method for acquiring know-how information from the Web. First, we extract passages containing at least one target object and then extract candidates for know-how from them. Then, passages containing the know-how are discriminated from non-know-how information considering each object and its typical usage.
Keywordsknow-how how-to type question answering object usage information procedural question
Unable to display preview. Download preview PDF.
- 1.Aouladomar, F.: Towards answering procedural questions. In: Proceedings of the IJCAI Workshop on Knowledge and Reasoning for Answering Questions, pp. 21–31 (2005)Google Scholar
- 2.Delpech, E., Saint-Dizier, P.: Investigating the structure of procedural texts for answering how-to questions. In: Proceedings of the 6th International Conference on Language Resources and Evaluation, pp. 46–51 (2008)Google Scholar
- 3.Fontan, L., Saint-Dizier, P.: Analyzing the explanation structure of procedural texts: dealing with advice and warnings. In: Proceedings of the 2008 Conference on Semantics in Text Processing, pp. 115–127 (2008)Google Scholar
- 4.Hearst, M.A.: TextTiling: Segmenting text into multi-paragraph subtopic passages. Computational Linguistics 23(1), 33–64 (1997)Google Scholar
- 5.Kawahara, D., Kurohashi, S.: A fully-lexicalized probabilistic model for Japanese syntactic and case structure analysis. In: Proceedings of the 7th Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, pp. 176–183 (2006)Google Scholar
- 6.Kobayashi, N., Inui, K., Matsumoto, Y., Tateishi, K., Fukushima, T.: Collecting evaluative expressions for opinion extraction. In: Proceedings of the 2nd International Joint Conference on Natural Language Processing, pp. 584–589 (2004)Google Scholar
- 7.Takechi, M., Tokunaga, T., Matsumoto, Y., Tanaka, H.: Feature selection in categorizing procedural expressions. In: Proceedings of the 6th International Workshop on Information Retrieval with Asian Languages, pp. 49–56 (2003)Google Scholar
- 8.Tamura, A., Takamura, H., Okumura, M.: Classification of multiple-sentence questions. In: Proceedings of the 2nd International Joint Conference on Natural Language Processing, pp. 426–437 (2005)Google Scholar
- 9.Torisawa, K.: Automatic acquisition of expressions representing preparation and utilization of an object. In: Proceedings of the 5th Recent Advances in Natural Language Processing, pp. 556–560 (2005)Google Scholar