• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.12
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• pp.10-17
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• 1993

In this paper, CCF(Call Control Function), functional entity for basic call processing in SSP(Service Switching Point), is designed and implemented. This functional entity can provide the IN(Intelligent Network) services which are included in CCITT CS-1(Capability Set-1), near-term process for IN Architecture. UIO(Unique Input Output) method, one of the thest sequence generation methods for the finite state machine, is used for the implementation test of this functional entity.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.111-118
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• 2015

Entity linking is to link entity's name mentions occurring in text to corresponding entities within knowledge bases. Since the same entity mention may refer to different entities according to their context, entity linking needs to deal with entity disambiguation. Most recent works on entity disambiguation focus on semantic relatedness between entities and attempt to integrate semantic relatedness with entity prior probabilities and term co-occurrence. To the best of my knowledge, however, it is hard to find studies that analyze and present the pure effects of semantic relatedness on entity disambiguation. From the experimentation on Korean Wikipedia data set, this article empirically evaluates entity disambiguation approaches using semantic relatedness in terms of the following aspects: (1) the difference among semantic relatedness measures such as NGD, PMI, Jaccard, Dice, Simpson, (2) the influence of ambiguities in co-occurring entity mentions' set, and (3) the difference between individual and collective disambiguation approaches.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.111-120
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• 2015

Protein named entity identification is one of the most essential and fundamental predecessor for extracting information about protein-protein interactions from biomedical literature. In this paper, we explore the use of abstracts of biomedical literature in MEDLINE for protein name identification and present the results of the conducted experiments. We present a robust and effective approach to classify biomedical named entities into protein and non-protein classes, based on a rich set of features: orthographic, keyword, morphological and newly introduced Protein-Score features. Our procedure shows significant performance in the experiments on GENIA corpus using Random Forest, achieving the highest values of precision 92.7%, recall 91.7%, and F-measure 92.2% for protein identification, while reducing the training and testing time significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1759-1772
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• 2023

Chinese named entity recognition (NER) is a challenging work that seeks to find, recognize and classify various types of information elements in unstructured text. Due to the Chinese text has no natural boundary like the spaces in the English text, Chinese named entity identification is much more difficult. At present, most deep learning based NER models are developed using a bidirectional long short-term memory network (BiLSTM), yet the performance still has some space to improve. To further improve their performance in Chinese NER tasks, we propose a new NER model, IDCNN-BiLSTM-Highway, which is a combination of the BiLSTM, the iterated dilated convolutional neural network (IDCNN) and the highway network. In our model, IDCNN is used to achieve multiscale context aggregation from a long sequence of words. Highway network is used to effectively connect different layers of networks, allowing information to pass through network layers smoothly without attenuation. Finally, the global optimum tag result is obtained by introducing conditional random field (CRF). The experimental results show that compared with other popular deep learning-based NER models, our model shows superior performance on two Chinese NER data sets: Resume and Yidu-S4k, The F1-scores are 94.98 and 77.59, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.347-351
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• 1998

Dynamic programming is applicable to any situation where items from several groups must be combined to form an entity, such as a composite investment or a transportation route connecting several districts. The most desirable entity is constructed in stages by forming sub-entities that are candidates for inclusion in the most desirable entity are retained, and all other sub-entities are discarded. In the paper, the fuzzy dynamic programming is applied to the situation where each investment in the set has the following characteristics : the amount to be invested has several possible values, and the rte of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment , and the investment therefore has multiple levels. A numeric example constructing a combination of multilevel investments is given in the paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.129-134
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• 2004

XML is the new universal format for structured documents and data on the World Wide Web. As the Web becomes a major means of disseminating and sharing information and as the amount of XML data increases substantially, there are increased needs to manage and design such XML document in a novel yet efficient way. Moreover a demand of XML Schema(W3C XML Schema Spec.) that verifies XML document becomes increasing recently. However, XML Schema has a weak point for design because of its complication despite of various data and abundant expressiveness. Thus, it is difficult to design a complex document reflecting the usability, global and local facility and ability of expansion. This paper shows a simple way of modeling for XML document using a fundamental means for database design, the Entity-Relationship model. The design from the Entity-Relationship model to XML Schema can not be directly on account of discordance between the two models. So we present some algorithms to generate XML Schema from the Entity-Relationship model. The algorithms produce XML Schema codes using a hierarchical view representation. An important objective of this modeling is to preserve XML Schema's object-oriented concepts such as reusability, global and local ability. In addition to, implementation procedure and evaluation of the proposed design method are described.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.277-284
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• 2012

Named entity recognition (NER) technique can play a crucial role in extracting information from the web. While NER systems with relatively high performances have been developed based on careful manipulation of terms with a statistical model, term mismatches often degrade the performance of such systems because the strings of all the candidate entities are not known a priori. Despite the importance of lexical-level term mismatches for NER systems, however, most NER approaches developed to date utilize only the term string itself and simple term-level features, and do not exploit the semantic features of terms which can handle the variations of terms effectively. As a solution to this problem, here we propose to match the semantic concepts of term units in restaurant named entities (NEs), where these units are automatically generated from multiple resolutions of a semantic tree. As a test experiment, we applied our restaurant NER scheme to 49,153 nouns in Korean restaurant web pages. Our scheme achieved an average accuracy of 87.89% when applied to test data, which was considerably better than the 78.70% accuracy obtained using the baseline system.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.61-65
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• 2006

This paper is concerned with a quantitative computational trust model which lakes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust value for entities. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the outcome probability distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper presents in detail how the trust model works.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.667-673
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• 2004

The XML is emerging as standard language for data exchange on the Web. Therefore the demand of XML Schema(W3C XML Schema Spec.) that verifies XML document becomes increasing. However, XML Schema has a weak point for design because of its complication despite of various data and abundant expressiveness. This paper shows a simple way of design for XML Schema using a fundamental means for database design, the Entity-Relationship model. The conversion from the Entity-Relationship model to XML Schema can not be directly on account of discordance between the two models. So we present some algorithms to generate XML Schema from the Entity-Relationship model. The algorithms produce XML Schema codes using a hierarchical view representation. An important objective of this automatic generation is to preserve XML Schema's characteristics such as reusability, global and local ability, ability of expansion and various type changes.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.