• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.768-774
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• 2016

This paper deals with a method to recommend the combination of items as a group according to similarity to handle application area such as fashion and cooking, while the previous methods recommend single item such as a book, music or movie. Collaborative filtering is a method to recommend an item selected by users with similar tendency based on similarity between users. In this paper, the proposed method generates a set of frequent items based on collaborative filtering and association rules and recommends a group by similarity between groups. To show the validity of the proposed method, experiments are performed with purchase data collected from e-commerce for four months.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1025-1031
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• 2000

Pre-existing pattern recognition techniques, in the case of character recognition, have limited on the application field. But CAI character learning system and writer's recognition system are very important parts. The application field of pre-existing system can be expanded in the content that the learning of characters and the recognition of writers in the proposed paper. In order to achieve these goals, the development contents are the following: Firstly, pre-processing method by understanding the image structure is proposed, secondly, recognition of characters are accomplished b the histogram distribution characteristics. Finally, similarity measure functions are defined from standard character pattern for matching of the input character pattern. Also the effectiveness of this system is demonstrated by experimenting the standard primitive image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.875-885
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• 2010

CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.

• Design & Manufacturing
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• v.17 no.3
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• pp.34-40
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• 2023

In this study, real-time collection of mold vibration signals during injection molding processes was achieved through IoT devices installed on the mold surface. To analyze changes in the collected vibration signals, injection molding was performed under six different process conditions. Analysis of the mold vibration signals according to process conditions revealed distinct trends and patterns. Based on this result, cosine similarity was applied to compare pattern changes in the mold vibration signals. The similarity in time and acceleration vector space between the collected data was analyzed. The results showed that under identical conditions for all six process settings, the cosine similarity remained around 0.92±0.07. However, when different process conditions were applied, the cosine similarity decreased to the range of 0.47±0.07. Based on these results, a cosine similarity threshold of 0.60~0.70 was established. When applied to the analysis of mold vibration signals, it was possible to determine whether the molding process was stable or whether variations had occurred due to changes in process conditions. This establishes the potential use of cosine similarity based on mold vibration signals in future applications for real-time monitoring of molding process changes and anomaly detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.12
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• pp.954-961
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• 2013

In this paper, we propose a new learning method using a variable learning to improve pattern recognition in the FCSR(Fast Commit Slow Recode) learning method of the Fuzzy ART. Traditional learning methods have used a fixed learning rate in updating weight vector(representative pattern). In the traditional method, the weight vector will be updated with a fixed learning rate regardless of the degree of similarity of the input pattern and the representative pattern in the category. In this case, the updated weight vector is greatly influenced from the input pattern where it is on the boundary of the category. Thus, in noisy environments, this method has a problem in increasing unnecessary categories and reducing pattern recognition capacity. In the proposed method, the lower similarity between the representative pattern and input pattern is, the lower input pattern contributes for updating weight vector. As a result, this results in suppressing the unnecessary category proliferation and improving pattern recognition capacity of the Fuzzy ART in noisy environments.

• The Korean Journal of Mycology
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• v.26 no.1 s.84
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• pp.1-7
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• 1998

In order to find relationship within and between entomopathogenic species, analysis of protein band pattern in mycelia of 25 isolates was conducted by UPGMA. The results allowed differentiation of three groups on 85% similarity coefficient. Similarity coefficient within C. militaris was $0.787{\sim}1.000$, C. kyushuensis was 0.958-1.000 and C. pruinosa was 0.993-1.000. C210 and C298 isolates which had somewhat immersed perithecia, comparable to other C. militaris isolates, had 91% similarity. C108, C225-1 and C228 isolates pathogenic on Lepidopterous larvae had 89% similarity. Closely related species to C. militaris were C. kyushuensis and C. pruinosa. And similarity between C. pruinosa and C. kyushuensis was 88%. Similarity between C. bifusispora formed conidia on media and Paecilomyces tenuipes was 89%. C. scarabaeicola pathogenic specifically on adult Scarabaeidae had 82% similarity with above two species. C118 identified as C. militaris showed different protein banding patterns.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.1-17
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• 2008

Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.105-112
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• 2012

Most methods for detecting PVC and APC require the measurement of accurate QRS complex, P wave and T wave. In this study, we propose new algorithm for detecting PVC and APC without using complex parameter and algorithms. Proposed algorithm have wide applicability to abnormal waveform by personal distinction and difference as well as all sorts of normal waveform on ECG. To achieve this, we separate ECG signal into each unit patterns and made a standard unit pattern by just using unit patterns which have normal R-R internal. After that, we detect PVC and APC by using similarity analysis for pattern matching between standard unit pattern and each unit patterns.

• Korean Journal of Pharmacognosy
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• v.39 no.3
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• pp.179-185
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• 2008

Three species, such as Rheum palmatum L., R. tanguticum Maxim. and R. officinale Baillon are recognized as the source plants of Rhei Rhizoma in Korean Pharmacopeia. However, other herbal sources such as R. undulatum L. and Rumex crispus L. have been often misused as Rhei Rhizoma. A pattern analysis method to discriminate Rhei Rhizoma in Korean Pharmacopeia from other herbal plants using HPLC and TLC chromatograms was developed. The multivariate peak data of the chromatograms of methanol extracts of Rhei Rhizoma were used for hierarchical clustering analysis, principal components analysis and similarity calculation. Besides of the statistic analysis, TLC patterns of samples could be used as criteria of the discrimination. The developed pattern analysis method was specific and could be readily utilized for comprehensive evaluation of Rhei Rhizoma.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.802-809
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• 2013

In this paper, we propose the similarity measurement method between two program codes by counting the frequency and length of continuous patterns of specifiers and keywords, which exist in two program codes. In addition, we propose the visualization method of this analysis result by formal concept analysis. Proposed method considers adjacencies of specifiers or keywords, which have not been considered in the previous similarity measurements. Proposed method can detect the plagiarism by analyzing the pattern in each function regardless of the order of function call and execution. In addition, the result of the similarity measurement is visualized by the lattice of formal concept analysis to increase the user understanding about the relations between program codes. Experimental results showed that proposed method succeeded in 96% plagiarism detections. Our method could be applied into the analysis of general documents.