• Title/Summary/Keyword: Knowledge Retrieval

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A Study on the Design of a Topic Map-based Retrieval System for the Academic Administration Records of Universities (대학 학사행정 기록물의 토픽맵 기반 검색시스템 설계에 관한 연구)

  • Shin, Jiyu;Jung, Youngmi
    • Journal of Korean Society of Archives and Records Management
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    • v.16 no.1
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    • pp.175-193
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    • 2016
  • A topic map was designed as an efficient information retrieval method that is optimized for classification, organization, and navigation through the use of a semantic link network above information resources. With this, this study aims to design a topic map-based university archives retrieval system to provide the relevant information retrieval. For this study, electronic records that relate to the academic administration within two years of D university were collected, and topic map editing was carried out with Ontopia Omnigator. Topics were classified according to their functional analysis of academic administration. In the end, the number of topics was finalized as 626, with 6 types in general: academic work, staff, college register, student, university, etc. Association was separated into six types as well, which were formed with consideration to the relationships among topics. In addition, there are seven occurrence types: register class, register number, register date, receiver, title, creator, and identifier. It is expected that the associative nature of the designed topic map-based retrieval system in this study will make navigation of large records easy and allow incidental discovery of knowledge.

A Keyword Search Model based on the Collected Information of Web Users (웹 사용자 누적 사용정보 기반의 키워드 검색 모델)

  • Yoon, Sung-Hee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.777-782
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    • 2012
  • This paper proposes a technique for improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using query word senses can eliminating the irrelevant pages from the search result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the precision of retrieval system with user feedback deciding the query sense and information seeking behavior to pages.

Using Query Word Senses and User Feedback to Improve Precision of Search Engine (검색엔진의 정확률 향상을 위한 질의어 의미와 사용자 반응 정보의 이용)

  • Yoon, Sung-Hee
    • Journal of the Korean Society for information Management
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    • v.26 no.4
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    • pp.81-92
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    • 2009
  • This paper proposes a technique for improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using query word senses can eliminating the irrelevant pages from the search result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the precision of retrieval system with user feedback deciding the query sense and information seeking behavior to pages.

Improving Performance of Web Search Engine using Query Word Senses and User Feedback (질의어 의미정보와 사용자 피드백을 이용한 웹 검색엔진의 성능향상)

  • Yoon, Sung-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.2
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    • pp.280-285
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    • 2007
  • This paper proposes a technique improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using word senses is very important processing for improving performance by eliminating the irrelevant pages from the result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the performance of retrieval system with user feedback deciding the query sense and information seeking behavior to web pages.

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An Analysis of User Needs for User-Centered Information Retrieval System Design of University Library (대학도서관 이용자기반 정보검색시스템 설계를 위한 이용자 요구 분석)

  • Noh, Jin-Goo
    • Journal of the Korean Society for Library and Information Science
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    • v.34 no.4
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    • pp.69-95
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    • 2000
  • The purpose of this study is to derive system design factors and to analyze user needs of university library for design of user-centered information retrieval system. The result of this study can be summarized as follows: First, the concept of 'users-centered' in digital environment where the supporting role of intermediaries is growing bigger than before in the interaction with remote information retrieval system can be defined as the new concept of 'expansion of knowledge'. Second, 6 kinds of system design factors derived for user-centered information retrieval system design of the university libraries. Third, The user needs that examined and analyzed through the questionnaires made by user-centered approach according to the design factors should be considered for system design.

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Topic Level Disambiguation for Weak Queries

  • Zhang, Hui;Yang, Kiduk;Jacob, Elin
    • Journal of Information Science Theory and Practice
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    • v.1 no.3
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    • pp.33-46
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    • 2013
  • Despite limited success, today's information retrieval (IR) systems are not intelligent or reliable. IR systems return poor search results when users formulate their information needs into incomplete or ambiguous queries (i.e., weak queries). Therefore, one of the main challenges in modern IR research is to provide consistent results across all queries by improving the performance on weak queries. However, existing IR approaches such as query expansion are not overly effective because they make little effort to analyze and exploit the meanings of the queries. Furthermore, word sense disambiguation approaches, which rely on textual context, are ineffective against weak queries that are typically short. Motivated by the demand for a robust IR system that can consistently provide highly accurate results, the proposed study implemented a novel topic detection that leveraged both the language model and structural knowledge of Wikipedia and systematically evaluated the effect of query disambiguation and topic-based retrieval approaches on TREC collections. The results not only confirm the effectiveness of the proposed topic detection and topic-based retrieval approaches but also demonstrate that query disambiguation does not improve IR as expected.

Consideration of a Robust Search Methodology that could be used in Full-Text Information Retrieval Systems (퍼지 논리를 이용한 사용자 중심적인 Full-Text 검색방법에 관한 연구)

  • Lee, Won-Bu
    • Asia pacific journal of information systems
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    • v.1 no.1
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    • pp.87-101
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    • 1991
  • The primary purpose of this study was to investigate a robust search methodology that could be used in full-text information retrieval systems. A robust search methodology is one that can be easily used by a variety of users (particularly naive users) and it will give them comparable search performance regardless of their different expertise or interests In order to develop a possibly robust search methodology, a fully functional prototype of a fuzzy knowledge based information retrieval system was developed. Also, an experiment that used this prototype information retreival system was designed to investigate the performance of that search methodology over a small exploratory sample of user queries To probe the relatonships between the possibly robust search performance and the query organization using fuzzy inference logic, the search performance of a shallow query structure was analyzes. Consequently the following several noteworthy findings were obtained: 1) the hierachical(tree type) query structure might be a better query organization than the linear type query structure 2) comparing with the complex tree query structure, the simple tree query structure that has at most three levels of query might provide better search performance 3) the fuzzy search methodology that employs a proper levels of cut-off value might provide more efficient search performance than the boolean search methodology. Even though findings could not be statistically verified because the experiments were done using a single replication, it is worth noting however, that the research findings provided valuable information for developing a possibly robust search methodology in full-text information retrieval.

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Knowledge Representation in Knowledge-based Systems of Library and Information Science Field (문헌정보학 영역 지식기반시스템에서의 지식표현)

  • Jeong, Yeong-Mi
    • Journal of the Korean Society for information Management
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    • v.7 no.2
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    • pp.35-57
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    • 1990
  • Knowledge-based system is interpreted from the viewpoint of library and information science, and the concept of knowledge is defined in relation to information and data. Knowledge representation techniques are illustrated with examples from intelligent information retrieval systems and expert systems developed in library and information science field.

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Knowledge Level of Users of Keyword/Boolean Searching on an Online Public Access Catalog : SELIS (OPAC에 있어서 키워드/불연산자 탐색에 대한 이용자 지식수준 연구)

  • Koo Bon-Young
    • Journal of the Korean Society for Library and Information Science
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    • v.32 no.4
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    • pp.249-274
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    • 1998
  • It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

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An Ontology-based Knowledge Management System - Integrated System of Web Information Extraction and Structuring Knowledge -

  • Mima, Hideki;Matsushima, Katsumori
    • Proceedings of the CALSEC Conference
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    • 2005.03a
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    • pp.55-61
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    • 2005
  • We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

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