A Sense Retrieving Method from a Noun for the Commonsense Feeling Judgment System

Abstract

keywords: commonsense judgment, sense, unknown word processing, concept base, degree of association SummaryWhen we humans receive uncertain information, we interpret it properly, so we can expand the conversation, and take proper actions. This is possible because we have "commonsense" concerning the word, which is built up from knowledge that is stored through long time experience. Among the commonsense we use in our every day lives it is thought that there are the commonsense concerning; quantity such as size, weight, speed, time, or place; sense or feeling such as hot, beautiful, or loud; and moreover emotion such as happy or sad. In order for computers to understand the meaning and become closer to human beings, it is thought that the construction of a "Commonsense Judgment System" which deals with these "commonsense" is necessary.A subsystem needed for the "Commonsense Judgment System" is the system that judges the commonsense concerning the characteristics of words, namely the "Commonsense Feeling Judgment System." This paper proposes a mechanism to associate the characteristics of a word based on our five senses, such as an apple is red, with a knowledge base consisting of basic words.When aiming to realize this "Commonsense Feeling Judgment System" and trying to make a computer have the same commonsense and judgment ability as human beings, a very important factor is the handling of unknown words. Judgment concerning words, which are given to the computer as knowledge before hand, is not a problem since it can refer to that knowledge. But when an unknown word, non-registered knowledge, is inputted, how to process that word is a very difficult problem.In this paper, a method of unknown word processing, which connects an inputted unknown word to a word that is registered in the judgment knowledge base, is proposed. By using a concept base, which is made from several electric dictionaries, the closeness of meaning is put into consideration. With this process, it is possible to understand a word that does not exist in the knowledge base. This study aims to retrieve the meaning concerning sense, and deepen semantic understanding.

Humanistic Next-Generation Artificial Intelligence Capable of Association

“…When categorizing objective words and verb and normal and nominal adjective words, the ambiguity is judged from the relationships between words (Figure 4). To effectively use this knowledge database where a small amount of knowledge is registered to judge processing and emotions, I developed a proprietary "concept base" that automatically interprets limited knowledge broadly to respond to diverse expressions [6][7][8][9] (Figure 5). One result showed that this proposed method is capable of reproducing 74.2% of the emotion judgment ability.…”