• Title/Summary/Keyword: Search Keywords

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SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval

  • Jo, Dae Woong;Kim, Myung Ho
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.2
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    • pp.97-104
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    • 2017
  • In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

EMRQ: An Efficient Multi-keyword Range Query Scheme in Smart Grid Auction Market

  • Li, Hongwei;Yang, Yi;Wen, Mi;Luo, Hongwei;Lu, Rongxing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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    • pp.3937-3954
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    • 2014
  • With the increasing electricity consumption and the wide application of renewable energy sources, energy auction attracts a lot of attention due to its economic benefits. Many schemes have been proposed to support energy auction in smart grid. However, few of them can achieve range query, ranked search and personalized search. In this paper, we propose an efficient multi-keyword range query (EMRQ) scheme, which can support range query, ranked search and personalized search simultaneously. Based on the homomorphic Paillier cryptosystem, we use two super-increasing sequences to aggregate multidimensional keywords. The first one is used to aggregate one buyer's or seller's multidimensional keywords to an aggregated number. The second one is used to create a summary number by aggregating the aggregated numbers of all sellers. As a result, the comparison between the keywords of all sellers and those of one buyer can be achieved with only one calculation. Security analysis demonstrates that EMRQ can achieve confidentiality of keywords, authentication, data integrity and query privacy. Extensive experiments show that EMRQ is more efficient compared with the scheme in [3] in terms of computation and communication overhead.

The study on the design of Korean Medical Article Retrieval System Supporting Semantic Navigation based on Ontology (의미 네비게이션을 지원하는 온톨로지 기반 한의학 논문 검색 시스템 설계 연구)

  • Ko, You-Mi;Eom, Dong-Myung
    • Korean Journal of Oriental Medicine
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    • v.11 no.2
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    • pp.35-52
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    • 2005
  • This study is to design a Semantic Navigation Retrieval System for Oriental Medicine Articles based on a XTM so that people can search and use them more effectively than before. Keywords extracted from articles are categorized 4 topics : herbs, prescription, disease, and action. Keywords analysis Ontology is modeled based on 4 topics and their relations, and then represented Topic maps. Next, Article analysis Ontology is consist of title, author, keywords, abstracts and organization Topics from metadata. Keywords and Article analysis Ontology were integrated through Keywords Topic. Korean Medical Article Retrieval System is optimistic in terms on search results supporting semantic navigation in the information service aspects and easier accessibility because all related information are semantically connected with each different DBs.

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Identifying Influencing Factors on the Price Per Click of Keyword Advertising : Focusing on Keyword Type, Search Number and Competition (온라인 키워드 광고 시장에서 광고 단가에 영향을 미치는 요인 분석 : 키워드 유형, 검색 횟수와 경쟁업체의 수를 중심으로)

  • Lee, Hong Joo
    • Journal of Information Technology Services
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    • v.11 no.3
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    • pp.257-267
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    • 2012
  • Many advertisers utilize sponsored search in search engines since customers want to find relevant information on their purchases from the search engines. Many factors have influences on price per click of the sponsored search. These influences are different based on the types of keywords such as search/experience or prominent/specific. However, differences of the influences have not been studied well. Thus, this study wants to identify the differences of the influences according the type of keywords. One month data of keyword advertising were collected from Naver. The influences of search number, click through rate, and competition on price per click were different according to the keyword types.

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 about IR Keyword Abstraction using AC Algorithm (AC 알고리즘을 이용한 정보검색 키워드 추출에 관한 연구)

  • 장혜숙;이진관;박기홍
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.667-671
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    • 2002
  • It is very difficult to extract the words fitted for the purpose in spite of the great importance of efficient keyword extraction in information retrieval systems because there are many compound words. For example, AC machine is not able to search compound keywords from a single keyword. The DER structure solves this problem, but there remains a problem that it takes too much time to search keywords. Therefore a DERtable structure based on these methods is proposed in this dissertation to solve the above problems in which method tables are added to the existing DER structure and utilized to search keywords.

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Pattern Analysis-Based Query Expansion for Enhancing Search Convenience (검색 편의성 향상을 위한 패턴 분석 기반 질의어 확장)

  • Jeon, Seo-In;Park, Gun-Woo;Nam, Kwang-Woo;Ryu, Keun-Ho
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.2
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    • pp.65-72
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    • 2012
  • In the 21st century of information systems, the amount of information resources are ever increasing and the role of information searching system is becoming criticalto easily acquire required information from the web. Generally, it requires the user to have enough pre-knowledge and superior capabilities to identify keywords of information to effectively search the web. However, most of the users undertake searching of the information without holding enough pre-knowledge and spend a lot of time associating key words which are related to their required information. Furthermore, many search engines support the keywords searching system but this only provides collection of similar words, and do not provide the user with exact relational search information with the keywords. Therefore this research report proposes a method of offering expanded user relationship search keywords by analyzing user query patterns to provide the user a system, which conveniently support their searching of the information.

A Study on the Features of the Next Generation Search Services (차세대 검색서비스의 속성에 관한 연구)

  • Lee, Soo-Sang;Lee, Soon-Young
    • Journal of the Korean Society for information Management
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    • v.26 no.4
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    • pp.93-112
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    • 2009
  • Recently in the area of the information environment, there are lively discussions about search 2.0 which is representative of the next generation search services. In this study, we divide information search model into matching and linking models according the developmental stages. Therefore, on the one hand, we analyze the background, main concepts, related attributes and cases of the next generation search services and the other, we identify the representative keywords by the group analysis of various attributes and cases of it. The result shows that the main keywords such as social search, artificial intelligence and semantic search, and relation/network based search are representative of the search 2.0.

Semantic-based Keyword Search System over Relational Database (관계형 데이터베이스에서의 시맨틱 기반 키워드 탐색 시스템)

  • Yang, Younghyoo
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.12
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    • pp.91-101
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    • 2013
  • One issue with keyword search in general is its ambiguity which can ultimately impact the effectiveness of the search in terms of the quality of the search results. This ambiguity is primarily due to the ambiguity of the contextual meaning of each term in the query. In addition to the query ambiguity itself, the relationships between the keywords in the search results are crucial for the proper interpretation of the search results by the user and should be clearly presented in the search results. We address the keyword search ambiguity issue by adapting some of the existing approaches for keyword mapping from the query terms to the schema terms/instances. The approaches we have adapted for term mapping capture both the syntactic similarity between the query keywords and the schema terms as well as the semantic similarity of the two and give better mappings and ultimately 50% raised accurate results. Finally, to address the last issue of lacking clear relationships among the terms appearing in the search results, our system has leveraged semantic web technologies in order to enrich the knowledgebase and to discover the relationships between the keywords.

Development of the Pattern Matching Engine using Regular Expression (정규 표현식을 이용한 패턴 매칭 엔진 개발)

  • Ko, Kwang-Man;Park, Hong-Jin
    • The Journal of the Korea Contents Association
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    • v.8 no.2
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    • pp.33-40
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    • 2008
  • In various manners, string pattern matching algorithm has been proven for prominence in speed of searching particular queries and keywords. Whereas, the existing algorithms are limited in terms of various pattern. In this paper, regular expression has been utilized to improve efficiency of pattern matching through efficient execution towards various pattern of queries including particular keywords. Such as this research would enable to search various harmful string pattern more efficiently, rather than matching simple keywords, which also implies excellent speed of string pattern matching compared to that of those existing algorism. In this research, the proposed string search engine generated from the LEX are more efficient than BM & AC algorithm for a string patterns search speed in cases of 1000 with more than patterns, but we have got similar results for the keywords pattern matching.