• Title/Summary/Keyword: Keyword-extension

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A Text-based Similarity Measure for Scientific Literature (논문 데이터베이스를 위한 텍스트 기반 유사도 계산 방안)

  • Yoon, Seok-Ho;Kim, Sang-Wook
    • The KIPS Transactions:PartD
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    • v.18D no.5
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    • pp.317-322
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    • 2011
  • This paper addresses computing of similarity among papers using text-based measures. First, we analyze the accuracy of the similarities computed using different parts of a paper, and propose a method of Keyword-Extension, which is very useful when text information is incomplete. Via a series of experiments, we verify the effectiveness of Keyword-Extension.

A Secure and Efficient E-Medical Record System via Searchable Encryption in Public Platform

  • Xu, Lei;Xu, Chungen;Zhang, Xing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4624-4640
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    • 2017
  • This paper mainly presents a secure and efficient e-Medical Record System via searchable encryption scheme from asymmetric pairings, which could provide privacy data search and encrypt function for patients and doctors in public platform. The core technique of this system is an extension public key encryption system with keyword search, which the server could test whether or not the files stored in platform contain the keyword without leaking the information about the encrypted file. Compared with former e-medical record systems, the system proposed here has several superior features: (1)Users could search the data stored in cloud server contains some keywords without leaking anything about the origin data. (2) We apply asymmetric pairings to achieve shorter key size scheme in the standard model, and adopt the dual system encryption technique to reduce the scheme's secure problem to the hard Symmetric External Diffie-Hellman assumption, which could against the variety of attacks in the future complex network environment. (3) In the last of paper, we analyze the scheme's efficiency and point out that our scheme is more efficient and secure than some other classical searchable encryption models.

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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Analysis of Characteristics of Scientific Inquiry Problem Finding Process in Small Group Free Inquiry (소집단 자유 탐구에서 과학적 탐구 문제 발견 과정의 특징 분석)

  • Cheon, Myeongki;Lee, Bongwoo
    • Journal of The Korean Association For Science Education
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    • v.38 no.6
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    • pp.865-874
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    • 2018
  • The purpose of this study is to explore the process of inquiry problem finding in high school students' small group free-inquiry. For this purpose, 91 second grade high school students took part in small group free-inquiry. We conducted interviews with students (48 students in 15 groups) who were relatively successful in the inquiry performed for one semester (about 4 months). Based on the results of the interviews, we analyzed the characteristics of the inquiry problem finding through the steps and strategies in the inquiry problem finding process. The main results are as follows: First, in the inquiry problem finding process, steps such as selecting keyword, presenting an inconvenience, presenting a question, and finding an inquiry problem were found, and in particular, the process of selecting the keyword that correspond to the subject of inquiry, such as the material and situation of inquiry, is very important step in inquiry problem finding. Second, the strategies that students used in the process of finding inquiry problem included searching information, review of prior research, sharing of knowledge and experience, linking and extension of knowledge and experience, environmental awareness, expert consultation, discussion of suitability, elaboration, etc. Third, finding an inquiry problem was relatively easy in the inquiry for finding out problems (i.e. inconvenience) in everyday life and investigating ways to solve them. Fourth, the review of prior researches through the internet was useful in the process of selecting keyword and elaboration. Fifth, the factors that students consider when selecting one of several candidate inquiry problems are feasibility, real-life applicability, and economic condition. Sixth, the current affairs had a positive impact on the inquiry problem finding. Based on the above results, we discussed some ways to increase students' inquiry problem finding ability.

Efficient Synonym Detection Method through Keyword Extension (키워드 확장을 통한 효율적인 유의어 검출 방법)

  • Ji, Ki Yong;Park, JiSu;Shon, Jin Gon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.767-770
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    • 2018
  • 인공지능의 발달로 사람이 사용하는 자연어 형태의 문장을 통해 정보를 주고받는 질의응답 시스템이 주목받고 있다. 이러한 질의응답 시스템은 자연어로 구성된 사용자의 질의문에서 의도를 정확하게 파악해야 한다. 단순히 질의어의 키워드에 의존한 검색은 단어의 중의성을 고려하지 않아 질의문의 의도를 정확히 파악하는 데 문제가 있다. 이런 문제점을 해결하기 위해 질의문의 의미와 맥락에 따른 연관성을 이용하여 유의어를 확장하는 방법이 연구되고 있다. 본 논문에서는 워드 임베딩을 통해 생성된 단어 유사도를 이용하여 질의문에서 추출된 키워드를 확장하는 방법을 제안한다.

A Collaborative URL Tagging Scheme using Browser Bookmark Categories as Keyword Support for Webpage Sharing (브라우저 북마크 분류를 키워드로 사용하는 웹페이지 공유를 위한 협동적 URL 태깅 방식)

  • Encarnacion, Nico;Yang, Hyun-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.12
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    • pp.1911-1916
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    • 2013
  • One significant challenge that arises in social tagging systems is the rapid increase in the number and diversity of the tags. As opposed to structured annotation systems, tags provide users an unstructured, open-ended mechanism to annotate and organize web-content. In this paper, we propose a scheme for URL recommendation that is based on a folksonomy which is comprised of user-defined tags, URL-keywords and the category folder name as the major element. This scheme will be further improved and implemented on a browser extension that recommends to users the best way to classify a particular URL.

Meta Information Retrieval using Sentence Analysis of Korean Dialogue Style (한국어 대화체 문장 분석을 이용한 메타 정보검색)

  • 박인철
    • Journal of the Korea Computer Industry Society
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    • v.4 no.10
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    • pp.703-712
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    • 2003
  • Today, documents existing on internet by the development of communication network increase in number. And it is required the information retrieval system that can efficiently acquire the necessary information. Most information retrieval systems retrieve documents using a simple keyword or a boolean query of keywords. But, the method is not fit for novice users to use and has many difficulties than user's dialogue query from the viewpoint of convenience and precise understanding for query. So, this paper has an aim to suggest the method that will cope with above problems and to design and implement a meta query processing system for information retrieval using Korean dialogue sentences. The system implemented in this paper can generates a new boolean query for a given Korean dialogue sentence and resolve lexical ambiguities through morphological analysis, syntactic analysis and extension of query using thesaurus.

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New Techniques for Anonymous HIBE with Short Ciphertexts in Prime Order Groups

  • Lee, Kwang-Su;Lee, Dong-Hoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.5
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    • pp.968-988
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    • 2010
  • Anonymous hierarchical identity based encryption (HIBE) is an extension of identity based encryption (IBE) that can use an arbitrary string like an e-mail address for a public key, and it additionally provide the anonymity of identity in ciphertexts. Using the anonymous HIBE schemes, it is possible to construct anonymous communication systems and public key encryption with keyword search. This paper presents an anonymous HIBE scheme with constant size ciphertexts under prime order symmetric bilinear groups, and shows that it is secure under the selective security model. Previous anonymous HIBE schemes were constructed to have linear size ciphertexts, to use composite order bilinear groups, or to use asymmetric bilinear groups that is a special type of bilinear groups. Our construction is the first efficient anonymous HIBE scheme that has constant size ciphertexts and that uses prime order symmetric bilinear groups. Compared to the previous scheme of composite order bilinear groups, ours is ten times faster. To achieve our construction, we first devise a novel cancelable random blinding technique. The random blinding property of our technique provides the anonymity of our construction, and the cancellation property of our technique enables decryption.

A Design of semantic web-based fish drug information system (시맨틱 웹기반 수산용 의약품 정보시스템 설계)

  • Ceong, Hee-Taek;Kim, Hae-Ran;Han, Soon-Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.145-155
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    • 2010
  • In this paper, we suggest a fish drug domain ontology to show an associated information and hierarchy together through concept-relation and inference mechanism instead of keyword matching. First, we investigate competency questions from workers of fishery industry and then we derive concepts and terminologies. Next, we present a process of fish drug ontology modelling using Protege-OWL editor, which is an extension of Protege that supports the Web Ontology Language(OWL). Last, we suggest the user interface of semantic web-based fish drug information system to search easily associated informations of fish drug using this ontology. It is to provide an effective search method that fish disease manager, fish farmer, and students majoring in fisheries can confirm details of diseases, fish, and drug evaluations associated with fish drug within one screen without moving to another position.

A Study of 'Emotion Trigger' by Text Mining Techniques (텍스트 마이닝을 이용한 감정 유발 요인 'Emotion Trigger'에 관한 연구)

  • An, Juyoung;Bae, Junghwan;Han, Namgi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.69-92
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    • 2015
  • The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.