• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1517-1524
• /
• 2011

In this paper, a new document summarization method, which uses the semantic features and the pseudo relevance feedback (PRF) by using WordNet, is introduced to extract meaningful sentences relevant to a user query. The proposed method can improve the quality of document summaries because the inherent semantic of the documents are well reflected by the semantic feature from NMF. In addition, it uses the PRF by the semantic features and WordNet to reduce the semantic gap between the high level user's requirement and the low level vector representation. The experimental results demonstrate that the proposed method achieves better performance that the other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.2
• /
• pp.137-142
• /
• 2012

Snippet is a summaries information of representing web pages which search engine provides user. Snippet and page rank in search engine abundantly influence user for visiting web pages. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy association and pseudo relevance feedback. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.3
• /
• pp.533-540
• /
• 2012

In this paper, we propose a document summarization method using the pseudo relevance feedback and the term weighting based on semantic features. The proposed method can minimize the user intervention to use the pseudo relevance feedback. It also can improve the quality of document summaries because the inherent semantic of the sentence set are well reflected by term weighting derived from semantic feature. In addition, it uses the semantic feature of term weighting and the expanded query to reduce the semantic gap between the user's requirement and the result of proposed method. The experimental results demonstrate that the proposed method achieves better performant than other methods without term weighting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.387-388
• /
• 2012

In order to solve problem which User sometime visits the wrong page with respect to user intention when uses snippet. this paper proposes a new snippet extraction method using fuzzy. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.04a
• /
• pp.1403-1405
• /
• 2012

검색엔진은 사용자에 사이트의 우선순위와 함께 웹 페이지의 요약된 정보인 스니핏(snippet)을 제공한다. 스니핏은 사용자의 검색 사이트 방문에 많은 영향을 주고 있으나, 스니핏의 요약 정보와 사용자가 원하는 사이트 간에 의미 차이가 발생하여서 실제 사용자의 의도와는 다르게 잘못된 사이트에 방문할 수 있다. 본 논문은 의사연관 피드백과 퍼지 관련 곱(fuzzy relational product)를 이용한 새로운 스니핏 추출 방법을 제안한다. 제안방법은 의사연관 피드백을 이용하여 사용자의 질의를 확장학고, 확장된 질의와 웹 페이지 사이에 퍼지 관련 곱을 이용함으로써 사용자의 의도가 의미적으로 더 잘 포함되는 스니핏을 추출할 수 있다. 실험결과 제안방법이 다른 방법에 비하여서 스니핏 추출에 더 좋은 성능을 보인다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2374-2381
• /
• 2012

This paper proposes a new enhancing snippet extraction method using fuzzy and semantic features. The proposed method creates a delegate of sentence by using semantic features. It extracts snippet using fuzzy association between a delegate sentence and sentence set which well represents query. In addition, the method uses pseudo relevance feedback to expand query which extracts snippet to be well reflected semantic user's intention. The experimental results demonstrate the proposed method can achieve better snippet extraction performance than the previous methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.704-706
• /
• 2012

In this paper, we proposes a document summarization method using the term weighting. The proposed method can minimize the user intervention to use the pseudo relevance feedback. It also can improve the quality of document summaries because the inherent semantic of the sentence set are well reflected by term weighting derived from semantic feature.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.6
• /
• pp.7-17
• /
• 2009

The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.5
• /
• pp.906-912
• /
• 2009

Offline-based study is proceeding effectively for directly teaching and communication between a learner and a professor. In general virtual education system have been solve this problem using provides search of particular learning domain and auto feedback of relative learning domain after examination. But the learner needs personally select the right document among search result set and interconnected precedence study domain. Therefore, the unskilled learner is difficult of learning progress over against offline-based study. This paper suggests a index mechanism of varied views for helps to learner understand the flow and direction of learning and correlation between units.

• Korean Journal of Construction Engineering and Management
• /
• v.9 no.5
• /
• pp.159-167
• /
• 2008

This study provides a effective approach to the construction management problem with the limited number or amount of available resources using the analytic hierarchy process. Construction management is a series of decision making processes for planning and controling of cost, time and quality as main objectives in construction works. When several activities need the limited same resource at the same time, it is very hard to decide the priority of the activities in the real situations. For that the scientific decision making method and procedure for resource allocation are required. This study solves the resource allocation problem by dealing with the decision making problem which the activities are distributed to multiple projects and under multiple criteria. The analytic hierarchy process is a method devised to solve complex multi-criteria decision problems. The result shows that this study can be effectively used to make decisions in situations involving multiple objectives by evaluating the prioritized ranking and degree of the activity alternatives based on the overall preferences.