• 제목/요약/키워드: Ranking patterns

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Change in Trend in Various Clinico-Pathological Factors and Treatment Profile of Breast Cancer Patients: a Tertiary Cancer Centre Experience

  • Shankar, Abhishek;Roy, Shubham;Rath, GK;Kamal, Vineet Kumar;Bhandari, Menal;Kulshrestha, Rashi;Prasad, Neelam;Sachdev, Jaineet;Jeyaraj, Pamela
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.8
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    • pp.3897-3901
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    • 2016
  • Background: Breast cancer is by far the most frequent cancer of women (23% of all cancers), ranking second overall when both sexes are considered together. Since there has been change in clinico-pathological factors and treatment profiles for breast cancer patients over the years, the present study to evaluate the change trends in India. Materials and Methods: A detailed analysis was carried out with respect to age, menopausal status, family history, disease stage, surgery performed, histopathology, hormone receptor status, and use of chemotherapy or hormonal therapy. Change in various clinico-pathological factors and treatments of breast cancer cases was recorded and analysed. Results: Mean age at presentation was found to be earlier in 2005-2006 compared with 1997-98 (p value: 0.046). More premenopausal women were diagnosed with breast cancer in 2005-2006 when this was compared with initial years of assessment (p value ${\leq}0.001$). When change in the receptor status was evaluated, we observed that there was a decrease in cases of ER and PR receptor positivity which was significant (p value: 0.007). Over the period of time, more f patients were not offered surgery initially in view of advanced disease when the two time periods were compared (p value: ${\leq}0.001$). There was a significant increase in patients who were initially offered neo-adjuvant chemotherapy in view of advanced disease at presentation (p value: ${\leq}0.001$). There was increasing number of patients who received palliative treatment for symptoms in 2005-2006 when compared to patients treated in 1997-98((p value: ${\leq}0.001$). Conclusions: Changes in mean age at presentation, premenopausal status, and stage at presentation have occurred over the years. More aggressive patterns of disease have become more common with early age at presentation and aggressive biological behaviour with receptor negative tumours.

Phytosociological Study of Weed Vegetation around the Climbing Paths on Mt. Chungyeong (경기도 축령산 등산로 주변 잡초 식생의 식물사회학적 연구)

  • 안영희;송종석
    • Korean Journal of Environment and Ecology
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    • v.17 no.3
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    • pp.232-241
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    • 2003
  • Mountain Chungyeong, 879m in altitude, is located in the northeast of the middle area in Korea. Around Mt. Chungyeong, many Korean endemic and rare plants are populated, so it is considered a very important biogeographical area where the temperature zones of northern and southern plants are crossed. Because it is close to Seoul, a capital of Korea, it is a common mountain where many tourists visit frequently. Continuous tourist's visit may cause a bad influence on vegetation around the climbing paths. Therefor, weed community around the climbing paths on Mt. Chungyeong, where visitors exert a bad influence directly on its community by coming in and out, was surveyed phytosocialogically. Our surveys have been accomplished from August, 2001 to September, 2002. weed communities formed around the climbing paths on Mt. Chungyeong were divided into several patterns and analysed. They have been divided into 5 communities and 5 subcommunities. Community A: Plantago asiatica community, A-a: Erigeron annuus subcommunity, A-b: Carex. lanceolata subcommunity, B: Pseudostellaria palibiniana community, B-a: Carex siderosticta subcommunity, B-b: Galium trachyspermum subcommunity, C: Pueraria thunbergiana community, D: Lespedeza maximowiczii community, E: Rubus crataegifolius community, F: Oplismenus undulatifolius community, The flora surveyed in these communities was constituted of 47 families, 101 genera, 17 varieties, and 149 species. Wild plants such as Plantago asiatica, Erigeron annuus, Erigeron strigosus, Pueraria thunbergiana, Lespedeza maximowiezii, Rubus crataegifolius, Artemisia princeps var. orientalis, Artemisia japonica and Lysimachia clethroides were mostly light loving plants and higher resistant plants against the stamping pressure. Our result from the ranking all surveyed areas by the Bray-Curtis ordination method was very similar to the results from phytosocialogical table analysis.

Development and assessment of framework for selecting multi-GCMs considering Asia monsoon characteristics (아시아 몬순특성을 고려한 다중 GCMs 선정방법 개발 및 평가)

  • Kim, Jeong-Bae;Kim, Jin-Hoon;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.53 no.9
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    • pp.647-660
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    • 2020
  • The objectives of this study are to develop a framework for selecting multi-GCMs considering Asia monsoon characteristics and assess it's applicability. 12 climate variables related to monsoon climates are selected for GCM selection. The framework for selecting multi-GCMs includes the evaluation matrix of GCM performance based on their capability to simulate historical climate features. The climatological patterns of 12 variables derived from individual GCM over the summer monsoon season during the past period (1976-2005) and they are compared against observations to evaluate GCM performance. For objective evaluation, a rigorous scoring rule is implemented by comparing the GCM performance based on the results of statistics between historical simulation derived from individual GCM and observations. Finally, appropriate 5 GCMs (NorESM1-M, bcc-csm1-m, CNRM-CM5, CMCC-CMS, and CanESM2) are selected in consideration of the ranking of GCM and precipitation performance of each GCM. The selected 5 GCMs are compared with the historical observations in terms of monsoon season and monthly mean to validate their applicability. The 5 GCMs well capture the observational climate characteristics of Asia for the 12 climate variables also they reduce the bias between the entire GCM simulations and the observational data. This study demonstrates that it is necessary to consider various climate variables for GCM selection and, the method introduced in this study can be used to select more reliable climate change scenarios for climate change assessment in the Asia region.

Information technology and changes in firm activities:A case of the service industry in the United States (정보기술과 기업활동의 변화:미국의 서비스산업을 사례로)

  • Lee, Jeong Rock
    • Journal of the Korean Geographical Society
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    • v.29 no.4
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    • pp.402-419
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    • 1994
  • Telecommunication and intormation technology have been conceived as crucial as well as revolutionary elements for recent and future social and economic development, and their development have led to a spatial reorganization and locational change of economic activities. Information technology has resulted in important changes in the organization structure and location of firm. This study draws attention to the understanding of the relationship between the diffusion of information technology and changes in firm activities with the special reference to the service industry of the United States. Information technology has had a significant impact on the growth and changes of the service industry of the United States through changes in the organizational and employment structure, market structure, and locational changes. The impact of information technology on location changes of the service industry shows two opposite patterns, concentration and decentralization. Among these patterns, the location change in the service industry of the United States reveals predominantly the decentralization tendency such as suburbanization and transfer to lower ranking cities rather than concentration. In case of Korea, however, it is anticipated that the rapid development of information technology may lead to the concentration of the service industry in Seoul and Capital region.

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Effect of Some Factors on the Variation of Nutrient Level in Pinus rigida × taeda Needle (Pinus rigida × taeda 침엽내(針葉內) 양료수준(養料水準)의 변이(変異)에 관(関)한 몇가지 요인(要因)의 영향(影響))

  • Kim, Chi Moon;Kwon, Ki Won;Song, Ho Kyung;Kim, Chung Suk
    • Journal of Korean Society of Forest Science
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    • v.53 no.1
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    • pp.27-36
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    • 1981
  • Foliar nutrient concentrations of N, P, K, Ca, Mg, total sugar, starch, ether extracts were determined for three Pinus spp., that is, P. rigida, P. taeda, P. rigida${\times}$taeda, divided by tree age (16~19-year old, 6-year old), leaf age (current, over-winter, one-year old), planting location(Kyonggi-Do, Chungnam-Do, Junbuk-Do). Foliar compositions of inorganic nutrients were generally put in order of N(0.764~1.502%)>K((0.130~0.491%) $$\geq_-$$Ca(0.165~0.442%)>Mg(0.054~0.121%)${\fallingdotseq}$P(0.041~0.129%) in all the species. The concentrations of total sugar and ether extracts respectively ranged from 5 to 15% of the needles in dry weight base. The concentrations of N, P and K were similarly high in the over-winter needles (sampled in February), but those of Ca were generally high in one-year old needles. As a whole, inorganic nutrient levels in the needles showed different patterns with species, three age, leaf age and location. There were generally positive correlations between nitrogen and phosphorus in foliar concentrations. Foliar concentrations of total sugar showed the ranking of P. rigida > P. rigida${\times}$taeda > P. taeda and the lowest levels in February. Starch in the needles were contained about 10% of total sugar, and the variations of starch level were not regular with the studied factors. Ether extracts contents increased more of less with leaf age but changed irregularly with the other factors.

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Issue tracking and voting rate prediction for 19th Korean president election candidates (댓글 분석을 통한 19대 한국 대선 후보 이슈 파악 및 득표율 예측)

  • Seo, Dae-Ho;Kim, Ji-Ho;Kim, Chang-Ki
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.199-219
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    • 2018
  • With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

The Influence of Food Habits on Body Stature of Children (어린이의 식습관(食習慣)이 체위(體位)에 미치는 영향(影響)에 관한 연구(硏究))

  • Lee, Mi-Suk;Mo, Su-Mi
    • Journal of Nutrition and Health
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    • v.9 no.1
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    • pp.7-15
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    • 1976
  • The Purpose of this study was to determine every possible correlation between food habits and body statures of primary school children, aged ten years old. This study was conducted from July to October of 1975. In July, prepared questionaires concerning life style, anthropometry, food preference, and food behavior were distributed through school teachers to 425 children; 219 boys and 206 girls, in the 5th grade of three elementary schools in the city of Seoul. Then, in October, when subjects had been classified into underweight/obese by statistical analysis, mothers of obese or underweight children were interviewed by the authors to determine weaning history, daily food consumption of their children, and opinions of various snacks for children. Analysis of results in terms of correlation coefficient, chisquare test and percentage calculations, are as follows: 1. Physical growth and development Boys Girls Height (cm) $134.8{\pm}5.74\;134.4{\pm}5.97$ Weight (kg) $30.0{\pm}4.27\;29.5{\pm}5.16$ Chestgirth (cm) $64.1{\pm}3.59\;63.3{\pm}3.81$ Arm circumference (cm) $18.3{\pm}1.61\;18.2{\pm}1.70$ Triceps skinfold thickness (mm) $10.9{\pm}5.13\;12.7{\pm}4.86$ Various indices of nutrition such as relative weight, relative chestgirth, $R{\ddot{o}}hrer's$ index, Kaup index, Vervaeck index were determined. 2. Food habits 1) Food $preference{\cdots}{\cdots}A$ varying number of foods were selected from 60 items were accepted. It was found that the food which children liked best was fruit and snacks were popular one. Lowest ranking among LIKED foods were from strongly flavored vegetables and organ meat. In general, girls had more food dislikes than did boys. Selected as liked foods were fruits, rice noodle soup, biscuits, and peanuts. Disliked foods were liver, green onions, onions, green pepper, mushrooms, oysters, shellfish, and pork. Items which children never ate before were liver, mushrooms, fish cake, boiled rice mixed with sorghum, mayonnaise, and fresh water firsh. Reasons which children gave for dislike were undesirable flavor and odor. 2) Food $behavior{\cdots}{\cdots}It$ was found that boys liked sweet and salty flavors more than did the girls who more often liked sour flavor. The majority of children enjoyed evening meals more than lunch and breakfast. A number of children skipped breakfast because of lack of appetite or lack of time before going to school. Snacks were the most popular food, especially among girls. Their snacking habits were formed by the encouragement of the mother, and the relieve boredom. Educational backgrounds of mothers and family economical levels of children were remarkable correlated with mothers' attitudes toward feeding of children. There were several interesting findings relating body stature to some other responses; such as that the obese child has a small number of brothers, higher birth order, higher educated mothers and higher family cultural background. It was also discovered that food perference, except for fat and oil group foods was not related to body stature. Sweet taste was liked best and pepperly taste was mostly disliked. Sour taste was popular in the group of underweight. Underweight children were more finicky, disliked snacking, and didn't get much attention from their mothers. 3) Correlation between body stature and nutrition during their infancy. The majority of children, both from obese and underweight, were breast fed as infant. Twenty five per cent of obese children and 17.4 per cent of underwight children started weaning at $1{\sim}6$ months old. The most popular supplemental food of weaning was cereal gruel for the obese group, while boiled white rice and cereal gruel were most common for the underweight group. Highly significant relationships were found between stature of parents and their children. In the obese group 47.8 per cent of fathers and 45.9 per cent of mothers were overweight; however, none of the fathers and only one mother was found to be underweight. In daily food consumption patterns, meals consisting of bread or noodle were popular in the obese group but disliked by the underweight group. The study found clear contrast in that the obese group liked meat and fish while the underweight group liked fruits and vegetables, especially kimchee. The obese children desired to eat cereal foods, milk and milk products, and fat foods while the underweight group desired to eat fruits and vegetables. Frequency of snacks per day was much greater in the obese group. Foods which mothers believed to be good for the health were carrots, cucumbers, fruits, milk, potatoes, sweet potatoes, and breads, while sweet foods such as candies, drinks. chocolate were considered not good for the teeth. Watching television was not significantly related to statures of children. Most significant relationships were found beween frequencies of family guest meals/and eating-out, and children's statures. Nutritional problems which have been considered for the malnourished children in addition to those of children who have a tendency toward obesity, must be taken into consideration in the development of proper nutrition education through the channels of regular school teaching and teaching by parents in the homes. Korean standards of anthropometric measurements for children should be revised, current measurements show much higher figures than present Korean standards.

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A Methodology for Extracting Shopping-Related Keywords by Analyzing Internet Navigation Patterns (인터넷 검색기록 분석을 통한 쇼핑의도 포함 키워드 자동 추출 기법)

  • Kim, Mingyu;Kim, Namgyu;Jung, Inhwan
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.123-136
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    • 2014
  • Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis (다계층 이원 네트워크를 활용한 사용자 관점의 이슈 클러스터링)

  • Kim, Jieun;Kim, Namgyu;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.93-107
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    • 2014
  • In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

Analysis of Football Fans' Uniform Consumption: Before and After Son Heung-Min's Transfer to Tottenham Hotspur FC (국내 프로축구 팬들의 유니폼 소비 분석: 손흥민의 토트넘 홋스퍼 FC 이적 전후 비교)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.91-108
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    • 2020
  • Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.