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The following topics are discussed: distributed artificial intelligence; knowledge-based systems; ontologies; natural language processing; machine learning and data mining; pattern recognition; neural networks; genetic and hybrid intelligent systems; computer vision and image processing; robotics, planning and scheduling; uncertainty, probabilistic reasoning and fuzzy logic; multiagent systems; and...
This paper suggests a method that breaks a long sentence into simple sentences using not only syntactical information but also a sense of a word. Unlike uniformed sentences, common sentences are often ambiguous and frequently omit particles thus they should be divided into simple sentences at semantic level. This study shows the method that analyzes the dependency structure between predicate and complement...
With the increase in the number of Web services and the value they are taking, discovery of services that meet the criteria of users becomes a major challenge. Currently the discovery process lacks of well-defined semantics, therefore it is difficult to obtain the non explicit meaning of services, such as functionality. In order to provide an accurate solution to the problem described above, in this...
In this paper, we propose a practical question answering system for the "Analects of Confucius" based on the pragmatics information. The "Analects of Confucius" is a classic Chinese literature by the Confucian during the Warring States Period (476 B.C-221 B.C ). But the literature can not be categorized by topics and it has comprehensive meanings, not only the literal meanings...
In natural language processing, quotes are an important grammatical category which needs consideration. In this paper, we propose a Japanese language model that includes quotes as a category. The quotes are recognized by using surface information and dependencies between the words. Then, they are divided into direct and indirect speech. Finally, we extract the quotes and create a relation between...
Inductive method of model self-organization (IMMSO) developed in 80s by A. Ivakhnenko is an evolutionary machine learning algorithm, which allows selecting a model of optimal complexity that describes or explains a limited number of observation data when any a priori information is absent or is highly insufficient. In this paper, we study the performance of IMMSO to reveal a model in a given class...
Quantification of the similarity between data sequences is important in different database and data mining tasks such as indexing, retrieving, clustering and classification, many similarity metrics (Euclidean, DTW, among others) operate directly in the raw representation of the sequences, but this implies when the sequences are compared, not take into account information about the collective behavior...
The goal of this research is to provide an alternative for business processes evaluation and tracking, based on the analysis of non-structured information generated by such processes within the organization areas. In this article we introduce a method to determine the occurrence probability of a business process within the enterprisepsilas text documents. The proposed method introduces the use of...
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