• Title/Summary/Keyword: search engine

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A Usability Evaluation on the Visualization Techniques of Web Retrieval Results (웹 검색 결과 시각화 기법의 사용성 평가에 관한 연구)

  • Kim, Seong-Hee;Kim, Moon-Jeong
    • Journal of the Korean Society for Library and Information Science
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    • v.41 no.3
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    • pp.181-199
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    • 2007
  • This study is to suggest the usefulness of visualization techniques to display web retrieval results. We described the concept of visualization techniques and evaluated the usability for the SearchCrystal and KartOO search engines which provide visualization techniques for displaying the retrieval results. As a result, Searchcrystal search engine had higher score than KartOO system in terms of usability check lists.

An Exploratory Study of Performances between a Subject Directory and Keyword Search Engine in the Network Databases (네트웍 데이터베이스에서의 주제별 디렉토리와 키워드 검색엔진의 검색효율에 관한 탐색적 연구)

  • Lee Myeong-Hee
    • Journal of the Korean Society for Library and Information Science
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    • v.31 no.2
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    • pp.177-197
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    • 1997
  • The study measured whether two search engines retrieve different Web documents for 6 queries. Two different search engines, Alta Vista in terms of keyword search engines and Yahoo in terms of subject directory engines were measured using as criteria, total number of documents retrieved, total number of relevant documents retrieved, recall and precision ratios. In addition, Alta Vista was suitable for specific and technical terms, while Yahoo was effective for general and plain terms. However, more elaborate research needs to be tested in terms of query characteristics.

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Semantic Search System using Ontology-based Inference (온톨로지기반 추론을 이용한 시맨틱 검색 시스템)

  • Ha Sang-Bum;Park Yong-Tack
    • Journal of KIISE:Software and Applications
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    • v.32 no.3
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    • pp.202-214
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    • 2005
  • The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

Employment Effects Evaluation of Naver Shopping in 2018 (2018년 네이버 쇼핑의 고용영향 평가)

  • KIM, Heung-Kyu;JUNG, Yeon-Sung
    • The Journal of Industrial Distribution & Business
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    • v.10 no.5
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    • pp.27-36
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    • 2019
  • Purpose - Naver has emerged as a new leader in the open market. While existing open markets such as Gmarket, 11th Street, and so on are suffering from profitability deterioration, Naver is attracting sellers based on low commission and powerful search engine. We would like to analyze the impact of Naver shopping on the national economy, especially on employment, in a situation where the market reaction to Naver's strength as a leader in online shopping is mixed. Research Design, Data, and Methodology - Through the demand inducing inter-industry analysis, we estimate the employment inducement effect by Naver shopping from its shopping transaction. In turn, through the supply inducing inter-industry analysis, we estimate the employment inducement effect by Naver shopping from its low commission and powerful search engine. For the purpose of inter-industry analysis, as of 2018, the most recently announced 2014 inter-industry table (extension table) from the Bank of Korea is used. Results - The results of this study are as follows. First, Naver Shopping is expected to generate 7.8 trillion won's trade in 2018, resulting in 244,225 of job inducement, and 158,598 of employment inducement. In addition, Naver Shopping is estimated to benefit KRW 213 billion to its sellers due to low commission and powerful search function, resulting in 8,667 of job inducement, and 5,655 of employment inducement. Second, in terms of job inducement and employment inducement due to Naver Shopping's trade, transportation, business support service, information and communication, broadcasting, restaurants and lodging were ranked. Third, in terms of job inducement and employment inducement due to Naver Shopping's low commission and powerful search function, restaurants and hospitality, f/b and cigarette manufacturing, construction, and transportation equipment manufacturing were ranked. Conclusions - The number of job inducement resulting from low commission and powerful search engine of Naver shopping in 2018 was 8,667 (3.7% of 244,225, which was caused by transaction in Naver shopping in 2018), and employment inducement was 5,655 (3.7% of 158,598, which was caused by transaction in Naver shopping in 2018), which can be considered as additional employment impacts of Naver Shopping compared to the other online shopping operators.

Effective Web Crawling Orderings from Graph Search Techniques (그래프 탐색 기법을 이용한 효율적인 웹 크롤링 방법들)

  • Kim, Jin-Il;Kwon, Yoo-Jin;Kim, Jin-Wook;Kim, Sung-Ryul;Park, Kun-Soo
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.1
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    • pp.27-34
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    • 2010
  • Web crawlers are fundamental programs which iteratively download web pages by following links of web pages starting from a small set of initial URLs. Previously several web crawling orderings have been proposed to crawl popular web pages in preference to other pages, but some graph search techniques whose characteristics and efficient implementations had been studied in graph theory community have not been applied yet for web crawling orderings. In this paper we consider various graph search techniques including lexicographic breadth-first search, lexicographic depth-first search and maximum cardinality search as well as well-known breadth-first search and depth-first search, and then choose effective web crawling orderings which have linear time complexity and crawl popular pages early. Especially, for maximum cardinality search and lexicographic breadth-first search whose implementations are non-trivial, we propose linear-time web crawling orderings by applying the partition refinement method. Experimental results show that maximum cardinality search has desirable properties in both time complexity and the quality of crawled pages.

Improving Twitter Search Function Using Twitter API (트위터 API를 활용한 트위터 검색 기능 개선)

  • Nam, Yong-Wook;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.3
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    • pp.879-886
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    • 2018
  • The basic search engine on Twitter shows not only tweets that contain search keywords, but also all articles written by users with nicknames containing search keywords. Since the tweets unrelated to the search keyword are exposed as search results, it is inconvenient to many users who want to search only tweets that include the keyword. To solve this inconvenience, this study improved the search function of Twitter by developing an algorithm that searches only tweets that contain search keywords. The improved functionality is implemented as a Web service using ASP.NET MVC5 and is available to many users. We used a powerful collection method in C# to retrieve the results of an object, and it was also possible to output them according to the number of 'retweets' or 'favorites'. If the number of retrieved numbers is less than a given number, we also added an exclusion filter function. Thus, sorting search results by the number of retweets or favorites, user can quickly search for opinions that are of interest to many users. It is expected that many users and data analysts will find the developed function convenient to search on Twitter.

A Study on Improvement of Digital National Survey Map System (디지털국토통계지도 시스템 개선에 관한 연구)

  • Lee, Jong-Yong;An, Jung-Cheon;Cho, Sung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.60-70
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    • 2006
  • National atlas map for provide various information is one part of National territorial Statatics Survey but National atlas map in 2004 year don't have stability and ability. National territorial Statatics Survey in 2005 years have octuple data compare with data in 2004 years but have only one map. One map is going to provide with stability and ability. We don't use DBMS, But We make a similarly struct in file based program. We programmed system of dynamic-linked data with spatial data. To dynamic-linked system, we make search engine to based index struct and make combobox search system. spatial data only have index codes(year, national terrial indicator, area). If spatial data request specfied data, search engine search index code and provide DB data. New system is middle step of using DBMS. We redraw map for display real Korea area (with dokdo). New map is shape and similar Korea map.

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A Study on the Development of Search Algorithm for Identifying the Similar and Redundant Research (유사과제파악을 위한 검색 알고리즘의 개발에 관한 연구)

  • Park, Dong-Jin;Choi, Ki-Seok;Lee, Myung-Sun;Lee, Sang-Tae
    • The Journal of the Korea Contents Association
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    • v.9 no.11
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    • pp.54-62
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    • 2009
  • To avoid the redundant investment on the project selection process, it is necessary to check whether the submitted research topics have been proposed or carried out at other institutions before. This is possible through the search engines adopted by the keyword matching algorithm which is based on boolean techniques in national-sized research results database. Even though the accuracy and speed of information retrieval have been improved, they still have fundamental limits caused by keyword matching. This paper examines implemented TFIDF-based algorithm, and shows an experiment in search engine to retrieve and give the order of priority for similar and redundant documents compared with research proposals, In addition to generic TFIDF algorithm, feature weighting and K-Nearest Neighbors classification methods are implemented in this algorithm. The documents are extracted from NDSL(National Digital Science Library) web directory service to test the algorithm.

Detecting Intentionally Biased Web Pages In terms of Hypertext Information (하이퍼텍스트 정보 관점에서 의도적으로 왜곡된 웹 페이지의 검출에 관한 연구)

  • Lee Woo Key
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.59-66
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    • 2005
  • The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

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Categorizing Web Image Search Results Using Emotional Concepts (감성 개념을 이용한 웹 이미지 검색 결과 분류)

  • Kim, Young-Rae;Kwon, Kyung-Su;Shin, Yun-Hee;Kim, Eun-Yi
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.562-566
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    • 2009
  • In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

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