Young-Tack Park

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In this paper, a novel feature selection method based on the normalization of the well-known mutual information measurement is presented. Our method is derived from an existing approach, the max-relevance and min-redundancy (mRMR) approach. We, however, propose to normalize the mutual information used in the method so that the domination of the relevance or(More)
This paper introduces an accurate and robust facial expression recognition (FER) system. For feature extraction, the proposed FER system employs stepwise linear discriminant analysis (SWLDA). SWLDA focuses on selecting the localized features from the expression frames using the partial F-test values, thereby reducing the within class variance and increasing(More)
Activity recognition is an emerging field of research that enables a large number of human-centric applications in the u-healthcare domain. Currently, there are major challenges facing this field, including creating devices that are unobtrusive and handling uncertainties associated with dynamic activities. In this paper, we propose a novel Evolutionary(More)
The power of knowledge acquisition systems that employ failure-driven learning derives from two main sources: an effective global credit assignment process that determines when to acquire new knowledge by watching an expert’s behavior, and an efficient local credit assignment process that determines what new knowledge will be created for completing a failed(More)
In this paper, we present an approach to perform reasoning for scalable OWL ontologies in a Hadoop-based distributed computing cluster. Rule-based reasoning is typically used for a scalable OWL-Horst reasoning; typically, the system repeatedly performs many operations involving semantic axioms for big ontology triples until no further inferred data exists.(More)
Geunbae Lee, Jong-Hyeok Lee, Hyunchul Rho Department of Computer Science and Engineering Pohang University of Science and Technology (Postech) San 31, Hyoja-dong, Pohang, 790-784, South Korea Tel: +82-562-279-2254 Fax: +82-562-279-2299 Young-Tack Park Department of Arti cial Intelligence Soongsil University Seoul, South Korea(More)
An ontology-based multi-layered robot knowledge framework (OMRKF) is proposed to implement robot intelligence to be useful in a robot environment. OMRKF consists of four classes of knowledge (KClass), axioms and two types of rules. Four KClasses including perception, model, activity and context class are organized in a hierarchy of three knowledge levels(More)
Individuals tend to follow their own preferred paths when traveling to specific places. Information on these routes could be utilized to build various intelligent LBSs . In order to predict a current user’s route, various approaches have been researched. In this paper, we suggest a practical approach to learning users' route patterns from their histories(More)
Author name disambiguation is essential for improving performance of document indexing, retrieval, and web search. Author name disambiguation resolves the conflict when multiple authors share the same name label. This paper introduces a novel approach which exploits ontologies and ontology-based category utility for author name disambiguation. Author name(More)
A number of reasoning studies on big ontology have been carried out in the recent years. However, most of the existing studies have focused heavily on Hadoop MapReduce. In this paper, we propose a reasoning approach for Resource Description Framework Schema (RDFS) that employs optimized methods based on Spark. Spark is a general distributed inmemory(More)