• Title/Summary/Keyword: Similarity evaluation

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A Study on the Effect of Original Brand on the Extension of Clothing Product Brand (의류(衣類) 제품(製品)브랜드 확장시(擴張時) 모(母)브랜드의 영향(影響)에 관(關)한 연구(硏究))

  • Cho, Sung-Hun;Kim, Il
    • Journal of Fashion Business
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    • v.7 no.2
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    • pp.37-54
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    • 2003
  • This study is about the effect of original brand on the evaluation of extended brand in the policy of an enterprise's extending its brand. More specifically, this study investigated to see whether the customers' attitude toward original brand has effect on an extended brand and the width and similarity extent of the brand extension affect a brand which is not similar when another brand is extended. The summary of the demonstrative analysis results are as follows: 1. If the attitude toward original brand becomes more positive, the evaluation of the extended brand will become more positive as well. 2. If the attitude toward original brand becomes more positive, the width of a brand extension will become wider. 3. If customers' attitude toward a original brand is positive, their attitude toward an extended brand will be positive as well although the extended brand is not similar to the original brand. This study proved it is possible for brands to be extended from a original brand under the influence of the original brand even though they are weak in their similarity to their original brand unlike the existing theory which was skeptical about the extension of a brand which is low in its similarity to its original brand and that the success of the extension of a brand does not depend upon its similarity to its original brand.

Air Similarity Test for the Evaluation of Aerodynamic Performance of Steam Turbine (스팀터빈의 공력성능 평가를 위한 공기 상사실험)

  • Lim, Byeung-Jun;Lee, Eun-Seok;Yang, Soo-Seok;Lee, Ik-Hyoung;Kim, Young-Sang;Kwon, Gee-Bum
    • The KSFM Journal of Fluid Machinery
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    • v.7 no.5 s.26
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    • pp.29-35
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    • 2004
  • The turbine efficiency is an important factor in power plant, and accurate evaluation of steam turbine performance is the key issue in turbo machinery industry. The difficulty of evaluating the steam turbine performance due to its high steam temperature and pressure environment makes the most steam turbine tests to be replaced by air similarity test. This paper presents how to decide the similarity conditions of the steam turbine test and describes its limitations and assumptions. The test facility was developed and arranged to conduct an air similarity turbine performance test with various inlet pressure, temperature and mass flow rate. The eddy-current type dynamometer measures the turbine-generated shaft power and controls the rotating speed. Pressure ratio of turbine can be controled by back pressure control valve. To verify its test results, uncertainty analysis was performed and relative uncertainty of turbine efficiency was obtained.

A Dispersion Mean Algorithm based on Similarity Measure for Evaluation of Port Competitiveness (항만 경쟁력 평가를 위한 유사도 기반의 이산형 평균 알고리즘)

  • Chw, Bong-Sung;Lee, Cheol-Yeong
    • Journal of Navigation and Port Research
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    • v.28 no.3
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    • pp.185-191
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    • 2004
  • The mean and Clustering are important methods of data mining, which is now widely applied to various multi-attributes problem However, feature weighting and feature selection are important in those methods bemuse features may differ in importance and such differences need to be considered in data mining with various multiful-attributes problem. In addition, in the event of arithmetic mean, which is inadequate to figure out the most fitted result for structure of evaluation with attributes that there are weighted and ranked. Moreover, it is hard to catch hold of a specific character for assume the form of user's group. In this paper. we propose a dispersion mean algorithm for evaluation of similarity measure based on the geometrical figure. In addition, it is applied to mean classified by user's group. One of the key issues to be considered in evaluation of the similarity measure is how to achieve objectiveness that it is not change over an item ranking in evaluation process.

A Text Similarity Measurement Method Based on Singular Value Decomposition and Semantic Relevance

  • Li, Xu;Yao, Chunlong;Fan, Fenglong;Yu, Xiaoqiang
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.863-875
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    • 2017
  • The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

Community Discovery in Weighted Networks Based on the Similarity of Common Neighbors

  • Liu, Miaomiao;Guo, Jingfeng;Chen, Jing
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1055-1067
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    • 2019
  • In view of the deficiencies of existing weighted similarity indexes, a hierarchical clustering method initialize-expand-merge (IEM) is proposed based on the similarity of common neighbors for community discovery in weighted networks. Firstly, the similarity of the node pair is defined based on the attributes of their common neighbors. Secondly, the most closely related nodes are fast clustered according to their similarity to form initial communities and expand the communities. Finally, communities are merged through maximizing the modularity so as to optimize division results. Experiments are carried out on many weighted networks, which have verified the effectiveness of the proposed algorithm. And results show that IEM is superior to weighted common neighbor (CN), weighted Adamic-Adar (AA) and weighted resources allocation (RA) when using the weighted modularity as evaluation index. Moreover, the proposed algorithm can achieve more reasonable community division for weighted networks compared with cluster-recluster-merge-algorithm (CRMA) algorithm.

Evaluation of Positioning Effectiveness Based on the Preference and Similarity Data Derived from Consumers' Choice from Different Choice Sets (선택집합의 변화를 통하여 도출된 선호도 및 유사성 정보를 활용한 포지셔닝 우위 평가)

  • Won, Jee-Sung
    • Korean Management Science Review
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    • v.28 no.1
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    • pp.61-74
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    • 2011
  • Not only the preference data but also the similarity data can be used for developing effective marketing strategies. Hahn et al.[10] proposes a methodology of representing a brand(focal brand)'s competitors in a single map called the Preference-Similarity Map, according to their relative preference to and similarity with the focal brand. They also proposes a way to derive the relative preference and similarity values from the survey collecting the choice data from differing choice sets. This study identifies the limitations of the preference and similarity measures proposed by Hahn et al.[10] and shows how these measures can be revised. This study also proposes how to implement the revised measures and analyze brands' positioning strategies. Based on the results of the previous studies on the effect of inter brand similarity on brand evaluations, this study assumes that it is important to analyze how much a specific brand is preferred to its close competitors when evaluating the effectiveness of the brand's positioning in the market. This study applies the proposed measures to the data used in Hahn et al.[10] and also show how the proposed measures are related to the parameters of the choice model proposed by Batsell and Polking[1].

A Sampling-based Algorithm for Top-${\kappa}$ Similarity Joins (Top-${\kappa}$ 유사도 조인을 위한 샘플링 기반 알고리즘)

  • Park, Jong Soo
    • Journal of KIISE:Databases
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    • v.41 no.4
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    • pp.256-261
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    • 2014
  • The problem of top-${\kappa}$ set similarity joins finds the top-${\kappa}$ pairs of records ranked by their similarities between two sets of input records. We propose an efficient algorithm to return top-${\kappa}$ similarity join pairs using a sampling technique. From a sample of the input records, we construct a histogram of set similarity joins, and then compute an estimated similarity threshold in the histogram for top-${\kappa}$ join pairs within the error bound of 95% confidence level based on statistical inference. Finally, the estimated threshold is applied to the traditional similarity join algorithm which uses the min-heap structure to get top-${\kappa}$ similarity joins. The experimental results show the good performance of the proposed algorithm on large real datasets.

Influence of Product Similarity between Parent Brand and Extended Brand on Extended Product Evaluation - Focus on Franchise Brand - (모브랜드 제품-확장브랜드 제품간 유사성이 확장제품평가에 미치는 영향 - 프랜차이즈 브랜드를 중심으로 -)

  • Kim, Ki-Suk;Shin, Bong-Sup
    • The Journal of the Korea Contents Association
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    • v.11 no.11
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    • pp.378-389
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    • 2011
  • This study scrutinizes the similarity difference between parent brand product and extended brand product of franchise business and its effect on the attitude toward extended brand product. Results showed that the similarity difference is appeared according to product extended. The cognitive attitude and the behavioral attitude toward similarity difference are also appeared to be different as high in product similarity leads to high in both cognitive and behavioral attitude. The result also showed that the food similarity compare to the technological similarity has higher impact on attitude. These study results provided a significant insights in brand extension strategy of franchise business.

Retrieval of Scholarly Articles with Similar Core Contents

  • Liu, Rey-Long
    • International Journal of Knowledge Content Development & Technology
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    • v.7 no.3
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    • pp.5-27
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    • 2017
  • Retrieval of scholarly articles about a specific research issue is a routine job of researchers to cross-validate the evidence about the issue. Two articles that focus on a research issue should share similar terms in their core contents, including their goals, backgrounds, and conclusions. In this paper, we present a technique CCSE ($\underline{C}ore$ $\underline{C}ontent$ $\underline{S}imilarity$ $\underline{E}stimation$) that, given an article a, recommends those articles that share similar core content terms with a. CCSE works on titles and abstracts of articles, which are publicly available. It estimates and integrates three kinds of similarity: goal similarity, background similarity, and conclusion similarity. Empirical evaluation shows that CCSE performs significantly better than several state-of-the-art techniques in recommending those biomedical articles that are judged (by domain experts) to be the ones whose core contents focus on the same research issues. CCSE works for those articles that present research background followed by main results and discussion, and hence it may be used to support the identification of the closely related evidence already published in these articles, even when only titles and abstracts of the articles are available.

Tag Search System Using the Keyword Extraction and Similarity Evaluation (키워드 추출 및 유사도 평가를 통한 태그 검색 시스템)

  • Jung, Jaein;Yoo, Myungsik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.12
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    • pp.2485-2487
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    • 2015
  • Recently, Hashtag is widely used in SNS like Facebook, Twitter and personal blogs. However, the efficiency of tag search system is poor due to the indiscriminate use of hashtags. To enhance the accuracy of tag search system, we proposed a tag search system using the keyword extraction and similarity evaluation. The experimental results show that the proposed system provides the higher accuracy on tag search results.