• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.659-665
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• 2001

Relevance feedback is the most popular query reformulation strategy in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.9-14
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• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.745-751
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• 2004

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM(Max and Min Model), Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly In this paper we propose a new soft evaluation method for web Information retrieval using local context analysis feedback model. We also show through performance comparison that local contort analysis feedback is more efficient and effective than MMM, Paice and P-norm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.768-773
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• 2010

This paper presents the performance verification of the optimal state feedback controller via inverted pendulum systems. The proposed method generates the optimal control inputs satisfying both the constrained input and the performance specification. In addition, it reduces the steady-state error by adopting the integral control technique. In order to verify the performance of the proposed method, we apply both the proposed method and the general state feedback control to an inverted pendulum, CEM-IP-01 in the experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.335-340
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• 2008

In this paper, a decentralized fuzzy output feedback controller for nonlinear interconnected systems with time delay is proposed. The nonlinear interconnected system is represented to fuzzy system using Takagi-Sugeno (T-S) fuzzy model. The decentralized output feedback controller is designed(or stability of subsystems of the fuzzy interconnected system. The stable condition of the closed-loop subsystem is represented to the linear matrix inequality (LMI) form and control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.38-42
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• 2002

Conditions are discussed for operating a dissymmetric human master-small (or micro) slave system in best (large position gain-small velocity gain) conditions allowing higher operator dexterity when real effects (joint compliance, link flexion delay and transmission distortion) are taken into account. It is shown that position PD feedback law advantage for ideal case no longer holds, and that more complicated feedback law depending on real effects has to be implemented with adapted transmission line. Drawback is slowdown of master slave interaction, suggesting to use more advanced predictive methods for the master and more intelligent control law for the slave.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.587-590
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• 2003

In this paper, the control of the differential drive wheeled mobile robot (DDWMR) is studied. Because the DDWMR have non-holonomic constraints, it cannot be stabilized by smooth feedback. The T-S fuzzy model for the DDWMR is presented and a control algorithm Is developed by well known PID control and LMI based regional pole-placement.

• Journal of the Korean Mathematical Society
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• v.48 no.4
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• pp.775-795
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• 2011

The disturbance attenuation problem for a class of discretetime switched linear systems with exponential uncertainties via switched state feedback and switched dynamic output feedback is investigated, respectively. By using Taylor series approximation and convex polytope technique, exponentially uncertain discrete-time switched linear system is transformed into an equivalent switched polytopic model with additive norm bounded uncertainty. For such equivalent switched model, one designs its switching strategy and associated state feedback controllers and dynamic output feedback controllers so that whole switched model is asymptotical stabilization with H-in nity disturbance attenuation base on switched Lyapunov function and LMI approach. Finally, two numerical examples are presented to illustrate our results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.754-759
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• 2007

The information recommendation system offers selected documents according to information needs of dynamic users. User's needs are expressed as profiles consisting of one or more words and may be changed into some specifics through relevance feedback made by users during the recommendation process. In previous research, users have entered relevance information by taking part in explicit relevance feedbacks and learned user profiles using the positive relevance feedbacks. In this paper, we learn user profiles using not only positive relevance feedback but negative relevance feedback and reinforcement learning. To compare the proposed with previous method, we performed experiments to evaluate recommendation performance of the same topic. As a result, the former shows the improved performance than the latter does.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.443-446
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• 2004

This paper discusses an intelligent digital redesign technique for designing a fuzzy pulse-width-modulated (PWM) control. First when we are given a well-designed fuzzy analog control, the equivalent digital control is intelligently redesigned. Using the similar technique we intelligently redesign the fuzzy PWM control from the intelligently redesigned fuzzy digital control. A stabilizability of the intelligently redesigned PWM control is rigorously analyzed.