• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.183-193
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• 1999

The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In this paper, we propose an efficient algorithm for mining quantitative association rules with item constraints. For categorical attributes, we map the values of the attribute to a set of consecutive integers. For quantitative attributes, we can partition the attribute into values or ranges. While such constraints can be applied as a post-processing step, integrating them into the mining algorithm can reduce the execution time. We consider the problem of integrating constraints that are boolean expressions over the presence or absence of items containing quantitative attributes into the association discovery algorithm using Apriori concept.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.767-776
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• 2009

The purpose of this paper is to design, implement and test the automatic marking system for programming languages using key-words and boolean operations to solve the processing problems of natural languages. There are accurate grammar systems and key-words in programming languages. Using these characteristics, We have designed, programmed, and tested automatic marking system for programming languages through key-words and boolean operations in this paper. We have categorized programming languages into 7 types as the type of answer and when a professor input any key-words, the system make him put conjunction with the special character. It can be logical expressions instantly so that the system easily operates. We asked 10 students who are majoring in computer engineering to take a test on the paper and web to show how well automatic marking system that we have programmed works. Then We requested 3 professors if the subject problems marked objectively. As a result, automatic marking system proved to be appropriate. We have proposed the way of using key-words and boolean operation for prohibiting huge natural language processing in marking of subjective question. It promotes efficiency rate of programming, objectivity and speed through the transferal to the web for marking since the system prohibits marker to include personal opinion on marking and gives feedback quickly

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.43-49
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• 2012

Personalized message syndication is an important process for maximizing the effect of mobile marketing. This paper proposes an algorithm for determining clients satisfying target conditions in real-time. The proxy server as an intermediate node stores client profiles (gender, age, location, etc) and their respective summaries into a database. When a company syndicates messages at run time, the proxy server maps target conditions expressed by boolean expressions to integer value and determines target clients by comparing target value with profile summary. Thus, this approach provides efficient personalized message syndication in very large systems with millions of clients because it can determine target clients in real-time and work with a traditional database easily.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11A
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• pp.936-944
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• 2003

In this paper, we propose an AND/XOR-based technology mapping method for field programmable gate arrays (FPGAs). Due to the fixed size of the programmable blocks in an FPGA, decomposing a circuit into sub-circuits with appropriate number of inputs can achieve excellent implementation efficiency. Specifically, the proposed technology mapping method is based on Davio expansion theorem to decompose a given Boolean circuit. The AND/XOR nature of the proposed method allows it to operate on XOR intensive circuits, such as error detecting/correcting, data encryption/decryption, and arithmetic circuits, efficiently. We conduct experiments using MCNC benchmark circuits. When using the proposed approach, the number of CLBs (configurable logic blocks) is reduced by 67.6% (compared to speed-optimized results) and 57.7% (compared to area-optimized results), total equivalent gate counts are reduced by 65.5 %, maximum combinational path delay is reduced by 56.7 %, and maximum net delay is reduced by 80.5 % compared to conventional methods.