Paper:
Language: English:

Dynamic Interaction of Syntactic and Semantic Analyses Based on the Equivalent Transformation Computation Model

Hidekatsu Koike^, Kiyoshi Akama^, and Hiroshi Mabuchi^

^Faculty of Social Information, Sapporo Gakuin University, 11-banchi Bunkyodai, Ebetsu, Hokkaido 060-8555, Japan
^Division of Large-Scale Computational Systems, Information Initiative Center, Hokkaido University, Kita 11 Nishi 5, Kita-ku, Sapporo, Hokkaido 060-0811, Japan
^Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0193, Japan

Received: February 22, 2005

Accepted: December 21, 2005

Keywords: equivalent transformation, natural language processing, Japanese sentence

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.10, No.3 pp. 302-311, 2006

Abstract

In much conventional natural language processing, syntactic and semantic analyses are executed sequentially, which is inefficient due to computation sequence inflexibility. In this paper, we present system design based on the equivalent transformation computation model to construct natural language understanding that executes integrated syntactic and semantic analyses and generates all correct answers with adequate efficiency. The advantages of using the equivalent transformation include speed, provable correctness, and rule-based intuitive design. Equivalent transformation changes declarative descriptions, each of which represents constraints, one step at a time. Each step is proven to preserve the semantic meaning of a declarative description. We use numerous constraints for formalization and processing sequence is decided dynamically at runtime based on context. We demonstrate flexible processing that reduces the amount of computation by explaining the analysis of a sample Japanese sentence describing a chess move on a chessboard.

Reference

[1] K. Akama, H. Koike, and H. Mabuchi, “Equivalent Transformation by Safe Extension of Data Structures,” Perspectives of System Informatics, Lecture Notes in Computer Science, 2244, pp. 140-148, 2001.

[2] K. Akama, E. Nantajeewarawat, and H. Koike, “A Class of Rewriting Rules and Reverse Transformation for Rule-Based Equivalent Transformation,” Electronic Notes in Theoretical Computer Science, 59(4), pp. 1-16, 2001.

[3] K. Akama, E. Nantajeewarawat, and H. Koike, “Program Synthesis Based on the Equivalent Transformation Computation Model,” In Proceedings of the 12th International Workshop on Logic Based Program Synthesis and Transformation, pp. 285-304, Madrid, Spain, 2002.

[4] K. Akama, T. Simizu, and E. Miyamoto, “Solving Problems by Equivalent Transformation of Declarative Programs,” Journal of the Japanese Society for Artificial Intelligence, 13, pp. 944-952, 1998.

[5] C. Anutariya, V. Wuwongse, K. Akama, and E. Nantajeewarawat, “RDF Declarative Description (RDD): A Language for Metadata,” Journal of Digital Information, 2, Issue 2, No.60, 2001.

[6] H. Koike, K. Akama, and E. Boyd, “Program Synthesis by Generating Equivalent Transformation Rules,” In Proceedings of the Second International Conference on Intelligent Technologies (In-Tech’01), pp. 250-259, 2001.

[7] J. W. Lloyd, “Foundations of logic programming; (2nd extended ed.),” Springer-Verlag New York, Inc., 1987.

[8] C. S. Mellish, “Computer Interpretation of Natural Language Descriptions,” Ellis Horwood, 1985.

[9] E. Nantajeewarawat, K. Akama, and H. Koike, “Expanding Transformation as a Basis for Correctness of Rewriting Rules,” In Proceedings of the Second International Conference on Intelligent Technologies (InTech’01), pp. 392-401, 2001.

[10] E. Nantajeewarawat, V. Wuwongse, C. Anutariya, K. Akama, and S. Thiemjarus, “Toward Reasoning with Unified Modeling Language Diagrams Based-on Extensible Markup Language Declarative Description Theory,” International Journal of Intelligent Systems, 19(1-2), pp. 89-98, 2004.

[11] K. Suita, K. Akama, and E. Miyamoto, “Constructing Natural Language Understanding Systems Based on Equivalent Transformation,” Electronic Information Communication Conference Technology Research Report, SS97-35, pp. 23-30, 1997 (in Japanese).

[12] K. Suita, K. Akama, and E. Miyamoto, “Understanding Unknown Words Using Domain Knowledge and Context,” Electronic Information Communication Conference Technology Research Report, SS97-52, pp. 17-24, 1998.

[13] V. Wuwongse, E. Nantajeewarawat, K. Akama, and C. Anutariya, “A Data Model for XML Databases,” International Journal of Intelligent Systems, 20(1), pp. 63-80, 2003.