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JACIII Vol.10 No.6 pp. 771-772
doi: 10.20965/jaciii.2006.p0771
(2006)

Editorial:

Special Issue on Language-Based Human Intelligence and Personalization

Ichiro Kobayashi

Associate Professor, Department of Information Sciences, Faculty of Science, Ochanomizu University, 2-1-1 Ootsuka, Bunkyo-ku, Tokyo 112-8610, Japan

Published:
November 20, 2006

At the annual conference of the Japan Society for Artificial Intelligence (JSAI), a special survival session called “Challenge for Realizing Early Profits (CREP)” is organized to support and promote excellent ideas in new AI technologies expected to be realized and contributed to society within five years. Every year at the session, researchers propose their ideas and compete in being evaluated by conference participants. The Everyday Language Computing (ELC) project, started in 2000 at the Brain Science Institute, RIKEN, and ended in 2005, participated in the CREP program in 2001 to have their project evaluated by third parties and held an organized session every year in which those interested in language-based intelligence and personalization participate. They competed with other candidates, survived the session, and achieved the session’s final goal to survive for five years. Papers in this special issue selected for presentation at the session include the following: The first article, “Everyday-Language Computing Project Overview,” by Ichiro Kobayashi et al., gives an overview and the basic technologies of the ELC Project. The second to sixth papers are related to the ELC Project. The second article, “Computational Models of Language Within Context and Context-Sensitive Language Understanding,” by Noriko Ito et al., proposes a new database, called the “semiotic base,” that compiles linguistic resources with contextual information and an algorithm for achieving natural language understanding with the semiotic base. The third article, “Systemic-Functional Context-Sensitive Text Generation in the Framework of Everyday Language Computing,” by Yusuke Takahashi et al., proposes an algorithm to generate texts with the semiotic base. The fourth article, “Natural Language-Mediated Software Agentification,” by Michiaki Iwazume et al., proposes a method for agentifying and verbalizing existing software applications, together with a scheme for operating/running them. The fifth article, “Smart Help for Novice Users Based on Application Software Manuals,” by Shino Iwashita et al., proposes a new framework for reusing electronic software manuals equipped with application software to provide tailor-made operation instructions to users. The sixth article, “Programming in Everyday Language: A Case for Email Management,” by Toru Sugimoto et al., making a computer program written in natural language. Rhetorical structure analysis is used to translate the natural language command structure into the program structure. The seventh article, “Application of Paraphrasing to Programming with Linguistic Expressions,” by Nozomu Kaneko et al., proposes a method for translating natural language commands into a computer program through a natural language paraphrasing mechanism. The eighth article, “A Human Interface Based on Linguistic Metaphor and Intention Reasoning,” by Koichi Yamada et al., proposes a new human interface paradigm called Push Like Talking (PLT), which enables people to operate machines as they talk. The ninth article, “Automatic Metadata Annotation Based on User Preference Evaluation Patterns,” by Mari Saito proposes effective automatic metadata annotation for content recommendations matched to user preference. The tenth article, “Dynamic Sense Representation Using Conceptual Fuzzy Sets,” by Hiroshi Sekiya et al., proposes a method to represent word senses, which vary dynamically depending on context, using conceptual fuzzy sets. The eleventh article, “Common Sense from the Web? Naturalness of Everyday Knowledge Retrieved from WWW,” by Rafal Rzepka et al., is a challenging work to acquire common-sense knowledge from information on the Web. The twelfth article, “Semantic Representation for Understanding Meaning Based on Correspondence Between Meanings,” by Akira Takagi et al., proposes a new semantic representation to deal with Japanese language in natural language processing. I thank the reviewers and contributors for their time and effort in making this special issue possible, and I wish to thank the JACIII editorial board, especially Professors Kaoru Hirota and Toshio Fukuda, the Editors-in-Chief, for inviting me to serve as Guest Editor of this Journal. Thanks also go to Kazuki Ohmori and Kenta Uchino of Fuji Technology Press for their sincere support.

Cite this article as:
Ichiro Kobayashi, “Special Issue on Language-Based Human Intelligence and Personalization,” J. Adv. Comput. Intell. Intell. Inform., Vol.10, No.6, pp. 771-772, 2006.
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