コンピューティング科学研究領域のRACHARAK講師がタイ国立研究評議会の「National Research Awards 2023」において学位論文賞を受賞

 コンピューティング科学研究領域のRACHARAK, Teeradaj講師の論文が、タイ国立研究評議会(NRCT)の「National Research Awards 2023」において学位論文賞を受賞しました。
 この論文は、RACHARAK講師がJAIST博士後期課程に在学中の2018年に、東条 敏教授の指導を受けて学位論文として発表したものです。



Concept Similarity in Description Logics: Computations and Applications

Racharak, Teeradaj

Concept similarity measure, as investigated in this dissertation, aims at identifying a degree of commonality of two given concepts and is often regarded as a generalization of the classical reasoning problem of equivalence. That is, any two concepts are equivalent if and only if their similarity degree is one. We formally investigate this notion in Description Logics (DLs). Its results provide a basis for computational methods of identifying the commonalities and the discrepancies between two concepts. Our methods of concept similarity measure are proven to be tractable. To this end, they are thereby restricted to the DLs which do not provide all Boolean operators such as FL0 and ELH to avoid inheriting NP-hardness from propositional logic.

Similarity judgment used by human beings often involve preferences and needs in practice. More specifically, when two concepts are not logically equivalent or totally similar, they may rely on subjective factors e.g. the agent's preferences. Here, we formally define a formal notion of concept similarity under such subjective factors called concept similarity measure under preference profile and identify a set of its desirable properties. These properties relate to the question "what could be good preference-based similarity measures?". To exemplify the developments, we suggest computational techniques for FL0 and ELH, and also, prove their inherited properties. Two algorithmic procedures for our developed measure simπ are introduced for the top-down and bottom-up implementations, respectively, and their computational complexities are intensively studied. We also discuss the usefulness of our proposed developments to potential use cases.

Analogical reasoning is a complex process based on a comparison between two pairs of concepts or states of affairs (a.k.a. the source and the target) for characterizing certain features from the source to the target. To exploit our results of concept similarity measure, we investigate such kind of reasoning that analogical conclusions can be derived from the similarity between DL concepts. Two approaches for the implementation of analogical reasoning are explored. Each is formulated from the study of philosophical understanding called argumentation schemes where patterns of non-deductive reasoning are analyzed. Finally, we demonstrate that the analogical argument used in the case of Silkwood v. Kerr-McGee Corporation is re-constructible from the proposed formalisms.

It is a great honor for me to receive the awards from Her Royal Highness Princess Maha Chakri Sirindhorn of Thailand and the National Research Council. The bestowed award certificates and award plate give me a great motivation to do better research that can benefit the public in future.

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タイのMaha Chakri Sirindhorn女王殿下