Catálogo de publicaciones - libros

We present a new model of knowledge, belief, desire and intention, called the interpreted KBDI-system model (or KBDI-model for short). The key point of the interpreted KBDI-system model is that we express an agent’s knowledge, belief, desire and intention as a set of runs (computing paths), which is exactly a in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our KBDI-model is in that we are able to associate a KBDI-model with a computer program, and formulas, involving agents’ knowledge, belief, desire (goal) and intention, can be understood as properties of program computations. With KBDI-model, we have two different semantics to interpret our logic of knowledge, belief, desire and intention. Moreover, with respect to each semantics, we present a sound and complete proof system.

XML document may contain inconsistencies that violate predefined integrity constraints, and there are two basic concepts for this problem: is the data consistent with the integrity constraints, and also minimally differs from the original one. is the data common for every possible repair. In this paper, first we give a general constraint model for XML, which can express functional dependencies, keys and multivalued dependencies. Next we provide a repair framework for inconsistent XML document with three basic update operations: node insertion, node deletion and value modification. Following this approach, we introduce the concept of repair for inconsistent XML document, discuss the chase process to generate repairs, and prove some important properties of the chase process. Finally we give a method to obtain the greatest lower bound of all possible repairs, which is sufficient for consistent data.

Intelligent tutoring systems have being extensively researched, and are viewed as cost-effective alternatives to traditional education. However, it has been long recognized that development of such systems is labor-intensive and time-consuming, and that a certain degree of automation in the development process is necessary. This paper proposes a framework for automating test generation – one of the key components in an intelligent tutoring system. The core of the framework is a domain conceptual model, a collection of testing goals, and a collection of test-generation rules, and the latter two are formulated from an analysis of various modes of error and on the basis of the domain conceptual model.

With the knowledge civilization development, the creation of knowledge and technology attracts an increasing interest in scientific research and practice. Universities and research institutes play a vital role in creating and transmitting scientific knowledge. Thus, enhancing the scientific knowledge creation in academia is a significant issue. In the paper, we investigate what aspects of knowledge creation processes in academic research we should support in particular. A questionnaire-based survey was conducted in a Japanese research institute (JAIST). By using a multiple criteria formulation and reference point method, we extract useful information and knowledge from the data base of survey results. Most critical and important problems are discovered by the negative and positive evaluations with respect to the conditions of scientific creativity. The results of the investigation give also valuable information for research and development management in universities and research organizations.

The role of ontologies is to provide a well-defined structure of domain knowledge that acts as the heart of any system of knowledge representation on that domain for the purposes of reasoning, knowledge sharing, and integration. Thus, it is essential to clarify the structure of knowledge in ontologies. In this paper, we discuss how ontology developers can define the identity conditions of classes explicitly, and can utilize them to develop structured taxonomies with adequate consistency. The background of this paper is OntoClean which is a domain independent methodology for ontology modeling using some philosophical notions. We exemplify the classification of sorts with necessary conceptual constraints. Then, we provide an explicit, simplified, and practical ontological analysis system regarding our subsumption constraints.

Through the interrelated concept of the job shop production, this paper constructs a dynamic scheduling decision system based on knowledge, and gives five attributes of resource agent and corresponding task, time, cost, quality, load and priority. Using the fuzzy set and rough set, the classified knowledge of the attribute is generated, and is used as the states criteria in the Q-learning. To initialize Q value of the decision attribute, we collect the knowledge from experts. The Q-learning algorithm and initial parameter values are presented in knowledge based scheduling decision model. By the algorithmic analysis, we demonstrate its convergence and credibility. Applying this algorithm, the system will update the knowledge itself continuously, and it will be more intelligent in the changeful environment, also it will avoid the subjectivity and invariance of the expert knowledge.

With the popularization of the Internet, virtual communities offer a new way for knowledge exchange. Previous research focused on the individuals’ motivation to knowledge contribution. However, the exchange of knowledge is facilitated not only when individuals are motivated but also when individuals have the ability to engage in it. This study examines the influence of capability to the knowledge contribution in the virtual community as compared to individual motivation. An online questionnaire survey and partial least squares (PLS) were used to analyze and verify the proposed hypotheses. The results indicated that perceived self-efficacy and professional experience positively influence knowledge contribution in the online virtual community. However, individual motivations, which often are regarded as important influential factors in the real world, did not significantly influence knowledge contribution in the online virtual community.

Ontology mapping is the key point to reach interoperability over ontologies. It can identify the elements corresponding to each other. With the rapid development of ontology applications, domain ontologies became very large in scale. Dealing with the large scale ontology mapping problems is beyond the reach of the existing algorithms. To improve this situation a modularization-oriented approach (called MOM) was proposed in this paper. This approach tries to decompose a large mapping problem into several smaller ones and use a method to reduce the complexity dramatically. Several large and complex ontologies have been chosen and tested to verify this approach. Experimental results indicate that the MOM method can significantly reduce the time cost while keeping the high mapping accuracy.

Words and n-grams are commonly used Chinese text representing units and are proved to be good features for Chinese Text Categorization and Information Retrieval. But the effectiveness of applying these representing units for Chinese Text Clustering is still uncovered. This paper is a comparative study of representing units in Chinese Text Clustering. With K-means algorithm, several representing units were evaluated including Chinese character N-gram features, word features and their combinations. We found Chinese word features, Chinese character unigram features and bi-gram features most effective in our experiments. The combination of features didn’t improve the results. Detailed experimental results on several public Chinese Text Categorization datasets are provided in the paper.

In an open and dynamic environment, due to the changes in the application’s domain or the user’s requirements, the domain knowledge changes over time and ontology evolves continually. Pi-calculus is a kind of mobile process algebra which can be used for modeling concurrent and dynamic systems. Based on the pi-calculus, this paper proposes a kind of ontology process model used for solving the change implementation and propagation problems in ontology evolution process. This solution is discussed at three levels: the change implementation of single ontology evolution, the push-based synchronization realization for the change propagation in the evolution of multiple dependent ontologies within a single node, and the pull-based synchronization realization for the change propagation of the distributed ontologies evolution.