• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.625-632
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• 2006

Collaborative filtering is a technology that aims at teaming predictive models of user preferences. Collaborative filtering systems have succeeded in Ecommerce market but they have shortcomings of high dimensionality and sparsity. In this paper we propose the nearest neighbor collaborative filtering method using non-negative matrix factorization(NNMF). We replace the missing values in the user-item matrix by using the user variance coefficient method as preprocessing for matrix decomposition and apply non-negative factorization to the matrix. The positive decomposition method using the non-negative decomposition represents users as semantic vectors and classifies the users into groups based on semantic relations. We compute the similarity between users by using vector similarity and selects the nearest neighbors based on the similarity. We predict the missing values of items that didn't rate by a new user based on the values that the nearest neighbors rated items.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.115-123
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• 1997

이산기간 H/sub .inf./ 제어에 의한 최적 예견제어기를 제안한다. 기존의 H/sub .inf./ 제어기는 미지의 외란만 고려한 것이고, LQ 에 의한 예견제어기는 예견 가능한 외란과 미지의 외란이 동시에 가해지는 동적 시스템의 전달함수 행렬의 infinity 놈의 최소화하는 피드백제어기가 동시에 설계된다. 제어기의 설계는 full-information H/sub .inf./ 제어 이론을 따르나, 그 유도 과정은 LQ 에 기초한 예견제어기와 유사하게 이루어진다. 설계된 H/sub .inf./ 예견 게인 행렬은 LQ 예견 게인 행렬과 유사한 구조를 갖는다. 전달함수 행렬의 infinity 놈이 .inf.로 갈수록 H/sub .inf./ 예견 게인 행렬은 LQ에 의한 것에 접근한다. LQ 예견 게인 행렬은 H/sub .inf./ 예견 게인 행렬의 부분 집합임이 입증한다.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.109-114
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• 2018

Collaborative filtering has been widely utilized in recommender systems as typical algorithm for outstanding performance. Since it depends on item rating history structurally, The more sparse rating matrix is, the lower its recommendation accuracy is, and sometimes it is totally useless. Variety of hybrid approaches have tried to combine collaborative filtering and content-based method for improving the sparsity issue in rating matrix. In this study, a new method is suggested for the same purpose, but with different perspective, it deals with no-match situation in person-person similarity evaluation. This method is called the transitive similarity model because it is based on relation graph of people, and it compares recommendation accuracy by applying to Movielens open dataset.

• Korean Journal of Cognitive Science
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• v.30 no.3
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• pp.133-156
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• 2019

To investigate how personality test items are understood by participants, their semantic representations were explored by Latent Semantic Analysis, In this thesis, Semantic Similarity Matrix was proposed, which contains cosine similarity of semantic representations between test items and personality traits. The matrix was compared to traditional factor loading matrix. In preliminary study, semantic space was constructed from the passages describing the five traits, collected from 154 undergraduate participants. In study 1, positive correlation was observed between the factor loading matrix of Korean shorten BFI and its semantic similarity matrix. In study 2, short personality test was constructed from semantic similarity matrix, and observed that its factor loading matrix was positively correlated with the semantic similarity matrix as well. In conclusion, the results implies that the factor structure of personality test can be inferred from semantic similarity between the items and factors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1623-1629
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• 2022

Matrix multiplication is a fundamental operation widely used in science and engineering. There is an approximate matrix multiplication method as a way to reduce the amount of computation of matrix multiplication. Approximate matrix multiplication determines an appropriate probability distribution for selecting columns and rows of matrices, and performs approximate matrix multiplication by selecting columns and rows of matrices according to this distribution. Probability distributions are generated by considering both matrices A and B participating in matrix multiplication. In this paper, we propose a method to generate a probability distribution that selects columns and rows of matrices to be used for approximate matrix multiplication, targeting only matrix A. Approximate matrix multiplication was performed on 1000×1000 ~ 5000×5000 matrices using existing and proposed methods. The approximate matrix multiplication applying the proposed method compared to the conventional method has been shown to be closer to the original matrix multiplication result, averaging 0.02% to 2.34%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.13-16
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• 2008

Dynamic Programming (DP)을 이용한 서열 비교 알고리즘은 DNA, RNA, 단백질 서열의 비교와 프로그래밍 소스 코드 유사도를 측정하는 곳 등에 널리 사용되어 왔다. 이 알고리즘은 DP를 이용하여 행렬을 구성한 후, 행렬의 가장 마지막 생성 값을 이용해 두 서열의 유사도를 측정하는 방법이다. 그러나 이 알고리즘에서 사용하는 마지막 생성 값은 비교 서열이 길이에 따라 크게 좌우되기 때문에 다양한 서열들의 유사도를 알아내기에는 부적합하다. 본 논문에서는 서열의 길이에 무관한 유사도 측정 (S2) 알고리즘을 제안한다. 제안된 알고리즘을 이용하면 비교 서열의 길이에 영향을 받지 않고 정당한 서열 비교를 할 수 있다. 제안된 알고리즘의 검증을 위해 본 논문에서는 프로그램 소스 코드의 유사도 측정을 수행한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.73-87
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• 1999

본 연구에서는 다양한 종류의 공정을 수행할 수 있는 가공장비와 자동화된 물류 운반시스템으로 구성된 FMS의 효율적 운영을 위해 셀 제조방식의 개념을 도입한 다수의 유연셀 형성 방법을 제시하고 있다. 서로 독립적인 유연셀의 형성을 위해 FMS의 장점인 공정유연성을 최대한 활용할 수 있도록 기계-공정 행렬과 부품-공정 행렬에 기초한 2 종류의 새로운 유사도 계수와 예외적 요소의 수를 최소화하기 위한 셀 형성 알고리즘을 개발하였다. 두 행렬들은 다공정 수행가능기계간 유사도와 기계셀과 부품간 비처리 능력지수 산출의 기초자료로 사용된다. 알고리즘은 예외적 요소의 수를 최소로 하면서 셀의 수를 최대로 하는 정리에 기초하여 공정을 기계에 할당하며, 다수의 대체경로가 유연셀내에서 형성될 수 있도록 크게 2 단계로 구성되어 있다. 마지막으로 수치예제와 함께 예외적 요소의 발생수를 척도로 하여 기존의 방법들과 비교, 평가하고 있다.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.34-43
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• 2012

Determining the similarity between two strings can be applied various area such as information retrieval, spell checker and spam filtering. Similarity calculation between Korean strings based on dynamic programming methods firstly requires a definition of the similarity between phonemes. However, existing methods have a limitation that they use manually set similarity scores. In this paper, we propose a method to automatically calculate inter-phoneme similarity from a given set of variant words using a PAM-like probabilistic model. Our proposed method first finds the pairs of similar words from a given word set, and derives derivation rules from text alignment results among the similar word pairs. Then, similarity scores are calculated from the frequencies of variations between different phonemes. As an experimental result, we show an improvement of 10.1%~14.1% and 8.1%~11.8% in terms of sensitivity compared with the simple match-mismatch scoring scheme and the manually set inter-phoneme similarity scheme, respectively, with a specificity of 77.2%~80.4%.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.546-550
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• 2010

In this paper, we propose a method for the postprocessing of cursive script recognition in Wine Label Images. The proposed method mainly consists of three steps: combination matrix generation, character combination filtering, string matching. Firstly, the combination matrix generation step detects all possible combinations from a recognition result for each of the pieces. Secondly, the unnecessary information in the combination matrix is removed by comparing with bigram of word in the lexicon. Finally, string matching step decides the identity of result as a best matched word in the lexicon based on the levenshtein distance. An experimental result shows that the recognition accuracy is 85.8%.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.587-598
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• 2003

This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.