• International Journal of Knowledge Content Development & Technology
• /
• v.7 no.3
• /
• pp.5-27
• /
• 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.

• Smart Structures and Systems
• /
• v.23 no.3
• /
• pp.279-293
• /
• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Asia-Pacific Journal of Business
• /
• v.13 no.3
• /
• pp.245-259
• /
• 2022

Purpose - Studies have been continuously carried out by researchers so far to clarify the factors influencing employee's incivility at work. However, the behavior of employees who are the target of incivility not much has been revealed which behavior affects the experience of incivility. Among them, it is interesting that the effect of OCB, a representative of employees' positive behavior in the workplace, on their experienced incivility has not been investigated. Therefore, this study attempted to clarify the relationship between OCB and experienced incivility that previous studies have not yet discovered. Design/methodology/approach - In the process, the concept of profile similarity was introduced and based on this, it was assumed that the OCB profile similarity between individual and colleagues, not the absolute level of OCB, would affect the experienced incivility and demonstrated this. The analysis was conducted by applying the survey data obtained from 205 employees to hierarchical regression analysis. Findings - As a result of the analysis, it was examined that the absolute OCB value used in previous studies did not significantly affect the experienced incivility, but the higher the similarity level, the less experienced incivility. The implications obtained based on this and future research directions are discussed together in the conclusion. Research implications or Originality - This study is the first one that considers OCB's profile similarity as a antecedent of experienced incivility. OCB profile similarity concept was only treated as a theoretical issue even in very early stage of OCB research stream, but this study examines the significant effect of OCB profile similarity. Moreover, behavioral antecedents of experienced incivility has not been identified well, but this study finds out that OCB can be a behavioral antecedent of experienced incivility.

• Journal of Families and Better Life
• /
• v.18 no.3 s.47
• /
• pp.129-146
• /
• 2000

The purpose of this study was to investigation the variables that affected the generational transmission of household work form mothers to their married daughter. The subjects were 415 married daughters and their mothers living in Seoul and metropolitan areas. Statistical techniques used for this study included descriptive statistics and multiple regression analysis. The results of this study were as follows : First, married daughters; value of household work was significantly affected by total periods of marriage of daughters, daughter's perceived similarity to their mothers' household work. Second, married daughters' preference for household work was significantly affected by mother's occupation (managerialㆍprofessional), mother's perceived similarity, daughter's experience of living with mother-in-law, daughter's sex-role attitude, and daughter's perceived similarity. Third, married daughters' ability to do household work was significantly affected by total periods of marriage for mothers, mother's perceived similarity, and daughter's perceived similarity. Fourth, married daughters' standard of household work was significantly affected by mother's perceived similarity, daughter's occupation (techniciansㆍclerk), daughter's monthly income, and daughter's perceived similarity. Fifth, married daughters' usage level of home equipments was significantly affected by mother's birth order, mother's education, mother's occupation (managerialㆍprofessional), daughter's birth order, daughter's education, and daughter's monthly income. Sixth, Mother related variables had greater power than daughter related ones in explaining daughters' values and preference for household work value and preferences and usage of home equipments. In conclusion, married daughter's consciousness and performance of household work were significantly influenced by their mothers. It was especially so in daughter's usage level of hoe equipments. Accordingly, the results of this study support the existence of generational transmission of household work from mothers to their married daughters with regard to its consciousness and performance. Findings of this study have implications for counsellors, practitioners and educators.

• Journal of Korean Society for Quality Management
• /
• v.49 no.2
• /
• pp.145-159
• /
• 2021

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.

• Journal of Internet Computing and Services
• /
• v.25 no.2
• /
• pp.39-47
• /
• 2024

Time series analysis is widely employed by many organizations to solve business problems, as it extracts various information and insights from chronologically ordered data. Among its applications, measuring time series similarity is a step to identify time series with similar patterns, which is very important in time series analysis applications such as time series search and clustering. In this study, we propose an efficient method for measuring time series similarity that focuses on anomalies rather than the entire series. In this regard, we validate the proposed method by measuring and analyzing the rank correlation between the similarity measure for the set of subsets extracted by anomaly detection and the similarity measure for the whole time series. Experimental results, especially with stock time series data and an anomaly proportion of 10%, demonstrate a Spearman's rank correlation coefficient of up to 0.9. In conclusion, the proposed method can significantly reduce computation cost of measuring time series similarity, while providing reliable time series search and clustering results.

• Journal of Educational Research in Mathematics
• /
• v.16 no.2
• /
• pp.115-138
• /
• 2006

The purpose of this paper is to investigate students' constructing similarities in the understanding the problem phase and the devising a plan phase of problem solving. the relation between similarities that students construct and how students construct similarities is researched through case study. Based on the results from the research, authors reached a conclusion as following. All of two students constructed surface similarities in the beginning of the problem solving process and responded to the context of the problem information sensitively. Specially student who constructed the similarities and the difference in terms of a specific dimension by using diagram for herself could translate the equation which used to solve the base problem or the experienced problem into the equation of the target problem solution. However student who understood globally the target problem being based on the surface similarity could not translate the equation that she used to solve the base problem into the equation of target problem solution.

• Korean Journal of Cognitive Science
• /
• v.30 no.3
• /
• pp.133-156
• /
• 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 Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.67-84
• /
• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Biomedical Science Letters
• /
• v.13 no.4
• /
• pp.293-304
• /
• 2007

The emergence of extended spectrum $\beta$-lactamase (ESBL) producing bacteria is worldwide concern. Until recently, the most frequently identified strains in the Republic of Korea were E. coli and Klebsiella spp. The incidence of resistance to extended spectrum $\beta$-lactam antibiotics is increasing in Wonju city, Korea. Total 57 strains of ESBL producing E. coli and Klebsiella species were isolated from Wonju Christian Hospital during a 9 month-period from April to December, 2003. To determine the prevalence and genotypes of the ESBL producing clinical isolates, antibiotic susceptibility and ESBL activity test by VITEK system and double disk synergy (DDS) test, and PCR based genotyping were performed. Fourteen (82%) isolates of 17 ESBL producing E. coli were found to have $bla_{TEM}$ gene and 5 (29%) isolates were found to have $bla_{CTX-M}$ gene by polymerase chain reaction (PCR). Thirty (75%) isolates of 40 ESBL producing Klebsiella species with $bla_{TEM}$ gene, 38 (95%) isolates with $bla_{SHV}$ gene, and 7 (20%) isolates with $bla_{CTX-M}$ type gene were also identified. Enterobacterial repetitive intergenic consensus (ERIC) PCR and similarity index by dendrogram for genetical similarity to band pattern of each clinical isolates were examined. ESBL producing E. coli were grouped into 6 clusters up to 84% of similarity index and Klebsiella species were grouped into 12 clusters up to 76% of similarity index. In conclusion, ESBL producing clinical isolates were characterized with the results from antimicrobial resistance pattern and genetical similarity using ERiC PCR.