• Title/Summary/Keyword: Keyword Data

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ValueRank: Keyword Search of Object Summaries Considering Values

  • Zhi, Cai;Xu, Lan;Xing, Su;Kun, Lang;Yang, Cao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.5888-5903
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    • 2019
  • The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.

Corpus-Based Literary Analysis (코퍼스에 기반한 문학텍스트 분석)

  • Ha, Myung-Jeong
    • The Journal of the Korea Contents Association
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    • v.13 no.9
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    • pp.440-447
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    • 2013
  • Recently corpus linguistic analyses enable researchers to examine meanings and structural features of data, that is not detected intuitively. While the potential of corpus linguistic techniques has been established and demonstrated for non-literary data, corpus stylistic analyses have been rarely performed in terms of the analysis of literature. Specifically this paper explores keywords and their role in text analysis, which is primary part of corpus linguistic analyses. This paper focuses on the application of techniques from corpus linguistics and the interpretation of results. This paper addresses the question of what is to be gained from keyword analysis by scrutinizing keywords in Shakespeare's Romeo and Juliet.

Research Trends in Journal of Fashion Business -A Social Network Analysis of Keywords in Fashion Marketing and Design Area- (키워드 네트워크 분석을 통한 「패션비즈니스」 연구 동향 -패션마케팅 및 디자인 분야를 중심으로-)

  • Lee, MiYoung;Lee, Jungmin
    • Journal of Fashion Business
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    • v.23 no.3
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    • pp.51-66
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    • 2019
  • The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

Keyword trends analysis related to the aviation industry during the Covid-19 period using text mining (텍스트마이닝을 활용한 Covid-19 기간 동안의 항공산업 관련 키워드 트렌드 분석)

  • Choi, Donghyun;Song, Bomi;Park, Dahyeon;Lee, Sungwoo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.115-128
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    • 2022
  • The purpose of this study is to conduct keyword trend analysis using articles data on the impact of Covid-19 in the aviation in dustry. In this study, related articles were extracted centering on the keyword "Airline" by dividing the period of 6months before and after Covid-19 occurrence. After that, Topic modeling(LDA) was performed. Through this, The main topic was extracted in the event of an epidemic such as Covid-19, It is expected to be used as primary data to predict the aviation industry's impact when occurrence like Covid-19.

Analysis of the Impact of Course Type and Delivery Modes on College Students' Online Course Satisfaction (비대면 온라인 수업에서 수업유형 및 운영방식에 따른 대학생의 수업만족도 차이 분석)

  • Kim, Min Kyung;Lee, Ji-Yeon
    • Journal of Information Technology Services
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    • v.21 no.3
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    • pp.73-87
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    • 2022
  • As the COVID-19 pandemic continues to prolong, non face-to-face, online classes has become the new normal in education. To examine the effect of course types and course delivery modes on student course satisfaction, the study analyzed survey data collected from 2,743 students enrolled in a 4-year university located in a metropolitan area. Basic Frequency analysis as well as keyword network analysis were used to analyze student survey data. The main results and implications of the study are as follows. First, the survey results indicated that students preferred asynchronous classes over synchronous online classes. This tendency was consistent regardless of student grades and majors as well as the course type. However, students majoring in more practice-oriented disciplines tend to prefer synchronous online classes and blended classes, and this tendency gets stronger with courses in major. Second, the keyword network analysis results further indicated that interactivity may play an important role in both synchronous and asynchronous online course satisfaction.

Enhancing Speech Recognition with Whisper-tiny Model: A Scalable Keyword Spotting Approach (Whisper-tiny 모델을 활용한 음성 분류 개선: 확장 가능한 키워드 스팟팅 접근법)

  • Shivani Sanjay Kolekar;Hyeonseok Jin;Kyungbaek Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.774-776
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    • 2024
  • The effective implementation of advanced speech recognition (ASR) systems necessitates the deployment of sophisticated keyword spotting models that are both responsive and resource-efficient. The initial local detection of user interactions is crucial as it allows for the selective transmission of audio data to cloud services, thereby reducing operational costs and mitigating privacy risks associated with continuous data streaming. In this paper, we address these needs and propose utilizing the Whisper-Tiny model with fine-tuning process to specifically recognize keywords from google speech dataset which includes 65000 audio clips of keyword commands. By adapting the model's encoder and appending a lightweight classification head, we ensure that it operates within the limited resource constraints of local devices. The proposed model achieves the notable test accuracy of 92.94%. This architecture demonstrates the efficiency as on-device model with stringent resources leading to enhanced accessibility in everyday speech recognition applications.

A Study on the Intelligence Information System's Research Identity Using the Keywords Profiling and Co-word Analysis (주제어 프로파일링 및 동시출현분석을 통한 지능정보시스템 연구의 정체성에 관한 연구)

  • Yoon, Seong Jeong;Kim, Min Yong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.139-155
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    • 2016
  • The purpose of this study is to find the research identity of the Korea Intelligent Information Systems Society through the profiling methods and co-word analysis in the most recent three-year('2014~'2016) study to collect keyword. In order to understand the research identity for intelligence information system, we need that the relative position of the study will be to compare identity by collecting keyword and research methodology of The korea Society of Management Information Systems and Korea Association of Information Systems, as well as Korea Intelligent Information Systems Society for the similar. Also, Korea Intelligent Information Systems Society is focusing on the four research areas such as artificial intelligence/data mining, Intelligent Internet, knowledge management and optimization techniques. So, we analyze research trends with a representative journals for the focusing on the four research areas. A journal of the data-related will be investigated with the keyword and research methodology in Korean Society for Big Data Service and the Korean Journal of Big Data. Through this research, we will find to research trends with research keyword in recent years and compare against the study methodology and analysis tools. Finally, it is possible to know the position and orientation of the current research trends in Korea Intelligent Information Systems Society. As a result, this study revealed a study area that Korea Intelligent Information Systems Society only be pursued through a unique reveal its legitimacy and identity. So, this research can suggest future research areas to intelligent information systems specifically. Furthermore, we will predict convergence possibility of the similar research areas and Korea Intelligent Information Systems Society in overall ecosystem perspectives.

An Analysis of Key Words Related to Traditional Korean Medicine Using Big Data of Two Search Engines (2대 포털사이트 빅데이터를 이용한 한방관련 키워드 분석)

  • Ahn, Jung-Yun;Keum, Ga-Jeong;Jang, Ah-Ryeong;Song, Ji-Chung
    • The Journal of Korean Medical History
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    • v.30 no.2
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    • pp.45-61
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    • 2017
  • Objectives : This research aims to investigate the consumer's interest in the Korean Medicine (KM) industry by using Google-trends and Naver-Data lab. A quick and uncomplicated way for those who are already involved with KM industry but do not have expertise in utilizing Big-data searches, is introduced. Methods : 'Direct keyword' was set by FGI (Focus Group Interview) and 'Detailed keyword' was set by using relevant word search and autocomplete search functions in the search engine. By inquiring Naver-Data lab, keyword search volumes are compared by age and sex, date range, and originating region of the researcher. It is possible to determine whether the data is reliable or authentic through examining the associated query. Selected direct keywords used through FGI (Focus Group Interview) were 'Acupuncture', 'Herbal Medicine', 'Cupping', 'Musculoskeletal Disease', 'Diet', and 'Stemina'. Based on these keywords, the following results were derived from the keyword analysis. Results : From August 2016, there was a noticeable surge of interest in men's 'Cupping'. The search for 'Diet' increased in the second quarter of 2016 from all ages. The search volume of 'Stemna' for individuals in their 20s is higher than that of those in their 30s or 40s'. Researchers from the region of Chungcheongbuk-do had a higher level of interest in analgesics and less interest in Korean Medicine. There is a greater interest in the KM market from European countries and America, than from Korea, China, and other Asian countries. Discussion : Despite the limitations of the research, it is meaningful to introduce a quick and easy data search method to compare information by age, sex, and region. Conclusion : The future of research into Korea Medicine and this market is confirmed by our data results which indicate interest from Europe, the United States, and other western countries, but less interest from Korea, China and other Asian countries.

A Study on the Meaning and Strategy of Keyword Advertising Marketing

  • Park, Nam Goo
    • Journal of Distribution Science
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    • v.8 no.3
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    • pp.49-56
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    • 2010
  • At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.

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Recommending Core and Connecting Keywords of Research Area Using Social Network and Data Mining Techniques (소셜 네트워크와 데이터 마이닝 기법을 활용한 학문 분야 중심 및 융합 키워드 추천 서비스)

  • Cho, In-Dong;Kim, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.127-138
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    • 2011
  • The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.