• Title/Summary/Keyword: users' search terms

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N-ary Information Markets: Money, Attention, and Personal Data as Means of Payment

  • Stock, Wolfgang G.
    • Journal of Information Science Theory and Practice
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    • v.8 no.3
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    • pp.6-14
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    • 2020
  • On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

Research on the Development of Facets for Improvement in Searching Records: Focusing on Presidential Records (기록물의 검색 향상을 위한 패싯 개발에 관한 연구 - 대통령기록물을 중심으로 -)

  • Seong, Hyoju;Rieh, Hae-young
    • Journal of Korean Society of Archives and Records Management
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    • v.17 no.2
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    • pp.165-188
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    • 2017
  • As the recognition of the importance of user-oriented services is increasing, there has been a heightened attention for finding aids that could improve the effectiveness of searching. This study tried to draw various facet elements that can be applied to the presidential records retrieval system using presidential records as cases in analyzing various resources, considering the importance of facets in finding aids for the improvement of effectiveness in searching in the future and the importance of presidential records in Korea. In drawing facet elements based on the characteristics of presidential records, the websites of the National Archives (NARA) and Presidential (Prime Ministers') Archives as well as their search options were examined as cases. In addition, the morpheme of each title of presidential records were analyzed, as well as the terms entered by the users of the Presidential Archives Portal of Korea, the terms used in the request for information disclosure toward the Presidential Archives in Korea, the search options of the Presidential Archives Portal, and the elements of the description and metadata standards. The significance of this study lies on suggesting the methodology of developing various facets as main elements in finding aids using the presidential records as cases.

Comparative Evaluation of Directory Services Provided by Major Korean Search Portals: In the Field of Computer and Internet (주요 포털들의 디렉토리 서비스 비교 평가 - 컴퓨터, 인터넷 분야를 중심으로 -)

  • Park, So-Yeon
    • Journal of the Korean Society for Library and Information Science
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    • v.43 no.1
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    • pp.215-234
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    • 2009
  • This study aims to perform an evaluation of directory services provided by major Korean search portals: Naver, Daum, Yahoo-Korea, and Empas. A directory service of Open Directory is also compared. These directory services are evaluated in terms of the coverage, category creation criteria, site selection criteria, breadth and depth of hierarchy, clarity and currency of category names, order of category listing, and overall classification system. The results of this study can be implemented for the development and improvement of portal's directory services. Users can refer to the results of this study in choosing directory services from search portals.

Trends of Search Behavior of Korean Web Users (국내 웹 이용자의 검색 행태 추이 분석)

  • Park Soyeon;Lee Joon Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.39 no.2
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    • pp.147-160
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    • 2005
  • This study examines trends of web query types and topics submitted to NAVER during one year period by analyzing query logs and click logs. There was a seasonal difference in the distribution of query types. Query type distribution was also different between weekdays and weekends, and between different days of the week. The log data show seasonal changes in terms of the topics of queries. Search topics seem to change between weekdays and weekends, and between different days of the week. However, there was little change in overall patterns of search behavior across one year. The implications for system designers and web content providers are discussed.

A Popularity-driven Cache Management and its Performance Evaluation in Meta-search Engines (메타 검색 엔진을 위한 인기도 기반 캐쉬 관리 및 성능 평가)

  • Hong, Jin-Seon;Lee, Sang-Ho
    • Journal of KIISE:Databases
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    • v.29 no.2
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    • pp.148-157
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    • 2002
  • Caching in meta-search engines can improve the response time of users' request. We describe the cache scheme in our meta-search engine in terms of its architecture and operational flow. In particular, we propose a popularity-driven cache algorithm that utilizes popularities of queries to determine cached data to be purged. The popularity is a value that represents the normalized occurrence frequency of user queries. This paper presents how to collect popular queries and how to calculate query popularities. An empirical performance evaluation of the popularity-driven caching with the traditional schemes (i.e., least recently used (LRU) and least frequently used (LFU)) has been carried out on a collection of real data. In almost all cases, the proposed replacement policy outperforms LRU and LFU.

Clustering Representative Annotations for Image Browsing (이미지 브라우징 처리를 위한 전형적인 의미 주석 결합 방법)

  • Zhou, Tie-Hua;Wang, Ling;Lee, Yang-Koo;Ryu, Keun-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.62-65
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    • 2010
  • Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

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'Hot Search Keyword' Rank-Change Prediction (인기 검색어의 순위 변화 예측)

  • Kim, Dohyeong;Kang, Byeong Ho;Lee, Sungyoung
    • Journal of KIISE
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    • v.44 no.8
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    • pp.782-790
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    • 2017
  • The service, 'Hot Search Keywords', provides a list of the most hot search terms of different web services such as Naver or Daum. The service, bases the changes in rank of a specific search keyword on changes in its users' interest. This paper introduces a temporal modelling framework for predicting the rank change of hot search keywords using past rank data and machine learning. Past rank data shows that more than 70% of hot search keywords tend to disappear and reappear later. The authors processed missing rank value, using deletion, dummy variables, mean substitution, and expectation maximization. It is however crucial to calculate the optimal window size of the past rank data. We proposed an optimal window size selection approach based on the minimum amount of time a topic within the same or a differing context disappeared. The experiments were conducted with four different machine-learning techniques using the Naver, Daum, and Nate 'Hot Search Keywords' datasets, which were collected for 2 years.

The Development and Performance Measurements of Consumer Health Information(CHI) Educational Programs to Improve Health Literacy among Public Library Users (공공도서관 이용자의 소비자건강정보(CHI) 리터러시 향상을 위한 교육프로그램 개발 및 성과측정연구)

  • Noh, Younghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.23 no.4
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    • pp.391-414
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    • 2012
  • Despite the growth in public concern about health information, the ratio of users who can search for accurate and reliable health information sources has been found to be quite low. Public libraries, as the best contact point to general users, must provide training programs for improving health literacy so that users will have the ability to search and analyze health information, judge the accuracy and reliability of resources, and make informed health-related decisions. This study developed a health information literacy education program suitable for Korean public library users. The effectiveness of the training was measured after administering the program, and necessary improvements were identified. As a result, this study found the education program had the following effects: improved public library users' familiarity with CHI-related terms, improved users' ability to find CHI-related information resources on the Internet, and significantly improved knowledge about health-related websites and information sources. In addition, users expressed interest in seminars on a variety of health information sources in the public library and asked that CHI-related education be included in the library's regular programming. However, this research represented the first time CHI-related education for public library users was performed in Korea, and therefore many limitations were present in the education instructor, the diversity of subjects, and the methodology. Development of more advanced CHI-related education programs for users is still required.

A Study on the classification scheme for the design of Directory Search Engine on the web (web 데이터베이스의 디렉토리 설계를 위한 분류체계 연구)

  • 이명희
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.10 no.1
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    • pp.243-268
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    • 1999
  • The purpose of this study is to develop the classification scheme in subject-based directory search engine for educational research information on the web. Five classification systems. Yahoo Korea, Argus Clearinghouse, DDC, ERIC thesaurus and KEDI thesaurus were measured in terms of coverage of subject fields, system logic, accuracy of terminology and efficiency of searching. For the design of Classification Scheme, this study considered the content of subject areas, features of information resources and efficiency based on users. Finally, the Classification Scheme was established in terms of 16 main divisions and 47 sub-divisions in educational research information.

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A Natural Language Retrieval System for Entertainment Data (엔터테인먼트 데이터를 위한 자연어 검색시스템)

  • Kim, Jung-In
    • Journal of Korea Multimedia Society
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    • v.18 no.1
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    • pp.52-64
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    • 2015
  • Recently, as the quality of life has been improving, search items in the area of entertainment represent an increasing share of the total usage of Internet portal sites. Information retrieval in the entertainment area is mainly depending on keywords that users are inputting, and the results of information retrieval are the contents that contain those keywords. In this paper, we propose a search method that takes natural language inputs and retrieves the database pertaining to entertainment. The main components of our study are the simple Korean morphological analyzer using case particle information, predicate-oriented token generation, standardized pattern generation coherent to tokens, and automatic generation of the corresponding SQL queries. We also propose an efficient retrieval system that searches the most relevant results from the database in terms of natural language querying, especially in the restricted domain of music, and shows the effectiveness of our system.