Hirokazu Watabe

An association method using concept-base

This paper proposes an association method using Concept-base. Concept-base is a large-scale relational database constructed by some electronic dictionaries and some newspapers. Each concept which is defined in Concept-base has attributes which characterize the concept and weights which show each attributes importance. Concept-base enables to calculate the depth of relationship (Degree of Association) of two any concepts using attributes and weights. This paper proposes One Word Association Method which associates one word (concept) with some relative words (concepts). Also, a threshold of Degree of Association is defined using the evaluation result of One Word Association Method. Finally, Two Words Association Method is proposed based on the threshold of Degree of Association.

A sensuous association method using an association mechanism for natural machine conversation

Humans manipulate smooth communications by retrieving, understanding and judging the sensuous characteristics from conversations consciously or unconsciously. This paper presents sensuous association methods to judge noun association from combinations of nouns (or adjectives) and adjectives/adjectival equivalents expressing senses as a means of achieving sense judgment similar to the common-sense judgment made by humans. The propose method is based on a mechanism that makes it possible to associate various concepts from a given concept. The precision rate and recall rate for nouns associated from combinations of nouns (or adjectives) and adjectives/adjectival equivalents were approximately 96.3% and 63.6% in reference to human judgment.

A time judgement system based on an association mechanism

Common sense and judgement ability, in the same way as humans, are necessary to realize a computer that communicates directly with humans. Such a thing needs the ability to recall a concept from a particular word and to associate the concept with others. A Time Judgement System that can understand everyday time expressions is important for natural communication, and the system was based on the aforesaid Association Mechanism. The purpose of this research is to construct the system that can treat regular time expressions with adaptability to unknown expressions. The resultant Time Judgement System achieves a correct response rate of 75.9% with accuracy of 85.8%, comparable to that of human subjects.

Application of multi-step GA to the traveling salesman problem

Although GAs are widely used for optimization problems and often produce good results, there are also problems, such as premature convergence and evolutionary stagnation. The premature convergence caused by a reduction of the diversity and evolutionary stagnation in GAs are observed, and a new genetic algorithm, named multi-step GA (MSGA) is proposed. MSGA narrows the search space to avoid evolutionary stagnation and restarts from the initial population, keeping past results to avoid premature convergence. To evaluate MSGA, traveling salesman problems are considered. As a result, MSGA can avoid premature convergence and evolutionary stagnation and shows higher performance than other conventional GAs.

Emotion judgment method from an utterance sentence

Authors focus on the emotion of such common sense and attempt to establish a method to judge the users emotions based on utterances. A speakers utterance sentence includes a linguistic proposition and a linguistic modality. The linguistic modality is an important factor to represent emotions for an utterance sentence. Therefore, in this paper, a method is proposed which judges speakers emotions from the linguistic proposition and modality included in the utterance sentence. The proposed method uses knowledge base and an Association Mechanism. As a result, the accuracy of the proposed emotion judgment method processing the linguistic modality is improved approximately 30% compared with an existing method.

A Semantic Information Retrieval Technique and an Evaluation for a Narrow Display Based on an Association Mechanism

The purpose of this study is to output information which users hope as high ranking results on narrow display of mobile information terminals. The concept of the proposed algorithm is to understand the meanings and the contents expressed by keywords and to retrieve appropriately related information. Concretely, we propose an information retrieval technique to evaluate the relationships between words using an association mechanism. A new test collection was made by 100 examinees who judged the retrieval results according to text meanings. Retrieval performance was objectively confirmed with the experiment based on the test collection.

Autonomous action generation of humanoid robot from natural language

Communication between human and robot is necessary for an intelligent robot to be active in daily life. Conversation is the basis of communication. Most of the instructions given to a robot are related to some actions. This paper reports the method to generate the action of the humanoid robot by conversation. For this purpose, comprehension of action instruction written by natural language is necessary. The system to understand natural language for generating action is proposed. This system consists of a semantic understanding method to arrange input information, the knowledge base of vocabulary related to actions, the knowledge base of the parameter for robots to act, and association mechanism to handle a word, which is not known. The system is capable of understanding many input sentences by the association mechanism using Concept-Base and a degree of association.

Evolutional shape modeling by extended genetic algorithm: multi-step GA

In a computer aided design (CAD) system, shape design or shape modeling is one often a bottleneck because shape design is a trial and error process often depending on a designers intuition and experience. Authors have already presented a method, named evolutional shape modeling (ESM), to generate suitable shapes automatically using genetic algorithm (GA) and free-form deformation (FFD). This ESM method, however, has a limitation on its ability of shape generation because of the limitation on FFDs shape deformation ability and the limitation on standard GAs ability. This paper proposes a new evolutional shape modeling method. It includes new genetic algorithm, named multistep GA, which can avoid premature convergence, and new constructing method of FFD by which shape deformation ability is highly improved.

Judging Emotion from EEGs Based on an Association Mechanism

Abstract Authors focus on the emotion of which common sense and attempt to compose a method that judge the users emotion, based on EEGs. Emotion is judged from EEG features by an Association Mechanism. The Association Mechanism consists of the Concept Base and the Degree of Association. The methods of a Concept Base and a Degree of Association were proposed in the field of the natural language processing. In this paper, the research results are applied to EEGs. As a result, accuracy of emotion judgment from EEGs using the Association Mechanism was 57.6%. As a comparison, accuracy of emotion judgment at random was 25.0%, and accuracy of emotion judgment using SVM was 43.6%.

Method of Embodying the Meaning of Headlines Using News Articles

Abstract In recent years, various studies have investigated intelligent robots that can smoothly communicate with humans. Communication between humans is often achieved through conversation, so it is likely that robots will need to be able to perform human-like conversation. There are various types of human conversation. Intelligent robots will be expected to perform conversations a lot as human. In order to realize such conversation in robots, resourses for making new topics is required. We herein focus on the news website headlines because headlines are a more appropriate format for initiating conversation than the text of articles. However, there is a problem in that specific information is lacking from headlines. Therefore, this paper present a method of embodying the meaning of headlines using news articles for using headlines as a resource of the robot conversation. The proposed method embodies the meanings of news headlines by adding or replacing words in the headline with words from the articles. As a result, the proposed method was able to embody the meanings of Japanese headlines in a natural manner for approximately 58.3% of the 120 headlines belonging to the test set.