• Title/Summary/Keyword: Cosine Similarity Analysis

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A Study on Detecting Changes in Injection Molding Process through Similarity Analysis of Mold Vibration Signal Patterns (금형 기반 진동 신호 패턴의 유사도 분석을 통한 사출성형공정 변화 감지에 대한 연구)

  • Jong-Sun Kim
    • 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.

Sentence Similarity Analysis using Ontology Based on Cosine Similarity (코사인 유사도를 기반의 온톨로지를 이용한 문장유사도 분석)

  • Hwang, Chi-gon;Yoon, Chang-Pyo;Yun, Dai Yeol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.441-443
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    • 2021
  • Sentence or text similarity is a measure of the degree of similarity between two sentences. Techniques for measuring text similarity include Jacquard similarity, cosine similarity, Euclidean similarity, and Manhattan similarity. Currently, the cosine similarity technique is most often used, but since this is an analysis according to the occurrence or frequency of a word in a sentence, the analysis on the semantic relationship is insufficient. Therefore, we try to improve the efficiency of analysis on the similarity of sentences by giving relations between words using ontology and including semantic similarity when extracting words that are commonly included in two sentences.

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The Analysis of the Conferences for the Computer Network Using the Miner and the Cosine Similarity based upon Keywords (키워드를 기반으로 마이너와 코사인 유사도를 이용한 컴퓨터 네트워크 관련 컨퍼런스 분석)

  • Kwon, Young-Bin;Lee, Seoung-Do;Yang, Hyun;Joo, Yo-Han
    • Journal of Information Technology Services
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    • v.11 no.1
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    • pp.223-238
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    • 2012
  • We have been provided with a plenty of information about IT through the conferences. However, it is hard to find enough information or the latest trends from conferences because there are too many conferences. In this situation, we analyzed the latest trends related to the field of IT by exploiting the Netminer which is one of the software for analysis of social networks and measuring the Cosine Similarity between conferences, based upon keywords which are included in the conferences. We analyzed keywords of 24 conferences related to the computer network part of the IEEE (Institute of Electrical and Electronics Engineers) in the case of foreign conferences. We also analyze keywords of the KIISE (Korean Institute of Information Scientists and Engineers) conferences in the case of domestic conferences, during 2009-2010. We identified the trends through the frequency of keywords, the change of top 10 keywords ranking and the similarity between conferences.

Target Classification in Sparse Sampling Acoustic Sensor Networks using DTW-Cosine Algorithm (저비율 샘플링 음향 센서네트워크에서 DTW-Cosine 알고리즘을 이용한 목표물 식별기법)

  • Kim, Young-Soo;Kang, Jong-Gu;Kim, Dae-Young
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.2
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    • pp.221-225
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    • 2008
  • In this paper, to avoid the frequency analysis requiring a high sampling rate, time-warped similarity measure algorithms, which are able to classify objects even with a low-rate sampling rate as time- series methods, are presented and proposed the DTW-Cosine algorithm, as the best classifier among them in wireless sensor networks. Two problems, local time shifting and spatial signal variation, should be solved to apply the time-warped similarity measure algorithms to wireless sensor networks. We find that our proposed algorithm can overcome those problems very efficiently and outperforms the other algorithms by at least 10.3% accuracy.

A Framework to Evaluate Communication Quality of Operators in Nuclear Power Plants Using Cosine Similarity (코사인 유사도를 이용한 원자력발전소 운전원 커뮤니케이션 품질 평가 프레임워크)

  • Kim, Seung-Hwan;Park, Jin-Kyun;Han, Sang-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.9
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    • pp.165-172
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    • 2010
  • Communication problems have been regarded as one of the biggest causes in trouble in many industries. This led to extensive research on communication as a part of human error analysis. The results of existing researches have revealed that maintaining a good quality of communication is essential to secure the safety of a large and complex process system. In this paper, we suggested a method to measure the quality of communication during off-normal situation in main control room of nuclear power plants. It evaluates the cosine similarity that is a measure of sentence similarity between two operators by finding the cosine of the angle between them. To check the applicability of the method to evaluate communication quality, we compared the result of communication quality analysis with the result of operation performance that was performed by operators under simulated environment.

The proposition of cosine net confidence in association rule mining (연관 규칙 마이닝에서의 코사인 순수 신뢰도의 제안)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.1
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    • pp.97-106
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    • 2014
  • The development of big data technology was to more accurately predict diversified contemporary society and to more efficiently operate it, and to enable impossible technique in the past. This technology can be utilized in various fields such as the social science, economics, politics, cultural sector, and science technology at the national level. It is a prerequisite to find valuable information by data mining techniques in order to analyze big data. Data mining techniques associated with big data involve text mining, opinion mining, cluster analysis, association rule mining, and so on. The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between each set of items based on the association thresholds such as support, confidence, lift, similarity measures, etc.This paper proposed cosine net confidence as association thresholds, and checked the conditions of interestingness measure proposed by Piatetsky-Shapiro, and examined various characteristics. The comparative studies with basic confidence and cosine similarity, and cosine net confidence were shown by numerical example. The results showed that cosine net confidence are better than basic confidence and cosine similarity because of the relevant direction.

The Identification of Emerging Technologies of Automotive Semiconductor

  • Daekyeong Nam;Gyunghyun Choi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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    • pp.663-677
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    • 2023
  • As the paradigm of future vehicles changes, the interest in automotive semiconductor, which plays a key role in realizing this, is increasing. Automotive semiconductors are the technology with very high entry barriers that require a lot of effort and time because it must secure technology readiness level and also consider safety and reliability. In this technology field, it is very important to develop new businesses and create opportunities through technology trend analysis. However, systematic analysis and application of automotive semiconductor technology trends are currently lacking. In this paper, U.S. registered patent documents related to automotive semiconductor were collected and investigated based on the patent's IPC. The main technology of automotive semiconductor was analyzed through topic modeling, and the technology path such as emerging technology was investigated through cosine similarity. We identified that those emerging technologies such as driving control for vehicle and AI service appeared. We observed that as time passed, both convergence and independence of automotive semiconductor technology proceeded simultaneously.

Similarity-based Damage Detection in Offshore Jacket Structures (유사도 기반 해양 자켓 구조물 손상추정)

  • Min, Cheon-Hong;Kim, Hyung-Woo;Park, Sanghyun;Oh, Jae-Won;Nam, Bo-Woo
    • Journal of Ocean Engineering and Technology
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    • v.30 no.4
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    • pp.287-293
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    • 2016
  • This paper presents an effective damage detection method for offshore jackets using natural frequency change ratios. Two parameters, cosine similarity and magnitude index, are considered to estimate the location and severity of the damage in the structure. A numerical jacket structure model is considered to verify the performance of the proposed method. As observed through analysis, the damages in the structure are detected accurately.

Case Study on Public Document Classification System That Utilizes Text-Mining Technique in BigData Environment (빅데이터 환경에서 텍스트마이닝 기법을 활용한 공공문서 분류체계의 적용사례 연구)

  • Shim, Jang-sup;Lee, Kang-wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.1085-1089
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    • 2015
  • Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

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An Analysis Scheme Design of Customer Spending Pattern using Text Mining (텍스트 마이닝을 이용한 소비자 소비패턴 분석 기법 설계)

  • Jeong, Eun-Hee;Lee, Byung-Kwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.2
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    • pp.181-188
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    • 2018
  • In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.