• Title/Summary/Keyword: Document Retrieval

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Path Combining System of XML Documents based on Relational DBMS (관계형 DBMS 기반의 XML 문서 경로 통합 시스템)

  • Lee, Bum-Suk;Hwang, Byung-Yeon
    • Journal of Korea Multimedia Society
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    • v.11 no.4
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    • pp.415-422
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    • 2008
  • With the increasing use of XML, considerable research is being conducted on the XML document management systems for more efficient storage and searching of XML documents. Depending on the base systems, these researches can be classified into object-oriented DBMS (OODBMS) and relational DBMS (RDBMS). OODBMS-based systems are better suited to reflect the structure of XML-documents than RDBMS based ones. However, using an XML parser to map the contents of documents to relational tables is a better way to construct a stable and effective XML document management system. The proposed X-Binder system uses an RDBMS-based inverted index; this guarantees high searching speed but wastes considerable storage space. To avoid this, the proposed system incorporates a path combining module agent that combines paths with sibling relations, and stores them in a single row. Performance evaluation revealed that the proposed system reduces storage wastage and search time.

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Design of a Hospice Referral System for Terminally Ill Cancer Patients Using a Standards-Based Health Information Exchange System

  • Lim, Kahyun;Kim, Jeong-Whun;Yoo, Sooyoung;Heo, Eunyoung;Ji, Hyerim;Kang, Beodeul
    • Healthcare Informatics Research
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    • v.24 no.4
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    • pp.317-326
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    • 2018
  • Objectives: The demand for hospice has been increasing among patients with cancer. This study examined the current hospice referral scenario for terminally ill cancer patients and created a data form to collect hospice information and a modified health information exchange (HIE) form for a more efficient referral system for terminally ill cancer patients. Methods: Surveys were conducted asking detailed information such as medical instruments and patient admission policies of hospices, and interviews were held to examine the current referral flow and any additional requirements. A task force team was organized to analyze the results of the interviews and surveys. Results: Six hospices completed the survey, and 3 physicians, 2 nurses, and 2 hospital staff from a tertiary hospital were interviewed. Seven categories were defined as essential for establishing hospice data. Ten categories and 40 data items were newly suggested for the existing HIE document form. An implementation guide for the Consolidated Clinical Document Architecture developed by Health Level 7 (HL7 CCDA) was also proposed. It is an international standard for interoperability that provides a framework for the exchange, integration, sharing, and retrieval of electronic health information. Based on these changes, a hospice referral scenario for terminally ill cancer patients was designed. Conclusions: Our findings show potential improvements that can be made to the current hospice referral system for terminally ill cancer patients. To make the referral system useful in practice, governmental efforts and investments are needed.

Efficient Linear Path Query Processing using Information Retrieval Techniques for Large-Scale Heterogeneous XML Documents (정보 검색 기술을 이용한 대규모 이질적인 XML 문서에 대한 효율적인 선형 경로 질의 처리)

  • 박영호;한욱신;황규영
    • Journal of KIISE:Databases
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    • v.31 no.5
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    • pp.540-552
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    • 2004
  • We propose XIR-Linear, a novel method for processing partial match queries on large-scale heterogeneous XML documents using information retrieval (IR) techniques. XPath queries are written in path expressions on a tree structure representing an XML document. An XPath query in its major form is a partial match query. The objective of XIR-Linear is to efficiently support this type of queries for large-scale documents of heterogeneous schemas. XIR-Linear has its basis on the schema-level methods using relational tables and drastically improves their efficiency and scalability using an inverted index technique. The method indexes the labels in label paths as key words in texts, and allows for finding the label paths that match the queries far more efficiently than string match used in conventional methods. We demonstrate the efficiency and scalability of XIR-Linear by comparing it with XRel and XParent using XML documents crawled from the Internet. The results show that XIR-Linear is more efficient than both XRel and XParent by several orders of magnitude for linear path expressions as the number of XML documents increases.

The MeSH-Term Query Expansion Models using LDA Topic Models in Health Information Retrieval (MeSH 기반의 LDA 토픽 모델을 이용한 검색어 확장)

  • You, Sukjin
    • Journal of Korean Library and Information Science Society
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    • v.52 no.1
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    • pp.79-108
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    • 2021
  • Information retrieval in the health field has several challenges. Health information terminology is difficult for consumers (laypeople) to understand. Formulating a query with professional terms is not easy for consumers because health-related terms are more familiar to health professionals. If health terms related to a query are automatically added, it would help consumers to find relevant information. The proposed query expansion (QE) models show how to expand a query using MeSH terms. The documents were represented by MeSH terms (i.e. Bag-of-MeSH), found in the full-text articles. And then the MeSH terms were used to generate LDA (Latent Dirichlet Analysis) topic models. A query and the top k retrieved documents were used to find MeSH terms as topic words related to the query. LDA topic words were filtered by threshold values of topic probability (TP) and word probability (WP). Threshold values were effective in an LDA model with a specific number of topics to increase IR performance in terms of infAP (inferred Average Precision) and infNDCG (inferred Normalized Discounted Cumulative Gain), which are common IR metrics for large data collections with incomplete judgments. The top k words were chosen by the word score based on (TP *WP) and retrieved document ranking in an LDA model with specific thresholds. The QE model with specific thresholds for TP and WP showed improved mean infAP and infNDCG scores in an LDA model, comparing with the baseline result.

Factors influencing success and safety of AED retrieval in out of hospital cardiac arrests in Singapore

  • NG, Jonathan Shen You;HO, Reuben Jia Shun;YU, Jae Yong;NG, Yih Yng
    • The Korean Journal of Emergency Medical Services
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    • v.26 no.2
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    • pp.97-111
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    • 2022
  • Purpose: Automated External Defibrillator (AED) usage in out-of-hospital cardiac arrests (OHCAs) improves the survival of patients. In Singapore, public AEDs are protected by locked boxes with a 'break glass' mechanism to deter theft. Community responders have sustained injuries while breaking glass to retrieve AEDs. This unprecedented study aimed to elucidate the factors influencing successful retrieval of an AED and to document the prevalence of injuries. Methods: A survey was created and distributed. Participants were required to have responded to an OHCA in the past 12 months. Comparison tests were performed with the Fischer-Freeman-Halton Exact test or Pearson chi square test at 5% significance levels, and with multiple logistic regression with a logit link function. Results: Eighty-eight participants were eligible. The success of retrieving an AED was found not to be impacted by occupation, age, gender or time. Participants who responded to an OHCA because of activation by the myResponder App were more likely to retrieve an AED successfully. (AOR 11.111, 95% CI: 2.141-58.824) Conclusion: Use of the myResponder mobile application is associated with the greater success of retrieving an AED. Successful retrieval of an AED is not impacted by time, gender, age, or the occupation of the responder. Community responders in Singapore remain motivated to respond to Cardiac Arrests despite risk of injury.

Multiple Cause Model-based Topic Extraction and Semantic Kernel Construction from Text Documents (다중요인모델에 기반한 텍스트 문서에서의 토픽 추출 및 의미 커널 구축)

  • 장정호;장병탁
    • Journal of KIISE:Software and Applications
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    • v.31 no.5
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    • pp.595-604
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    • 2004
  • Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

The Historical Study of SDI System (2) (SDI System의 사적 연구 (2))

  • Kim, Chong Hwoe
    • Journal of the Korean Society for information Management
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    • v.2 no.2
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    • pp.150-169
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    • 1985
  • This study is to introduce the SDI(Selective Dissemination of Information) system, a typical aspect of information retrieval systems nowadays quite popular. The term "SDI" is most often used to describe systems of using electronic data processing equipment as a means of matching the terms of user-interest profile against document descriptors and selecting those documents with a specified degree of similarity to the terms of the user-interest profile. Various up-ta-date informations on SDI systems developed after the first introduction of the original idea by "Luhn" are reviewed and compared. The stage of development, structure, characteristics, and various other matters concerning the SDI systems are analyzed, and discussed.

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Intelligent information filtering using rough sets

  • Ratanapakdee, Tithiwat;Pinngern, Ouen
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1302-1306
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    • 2004
  • This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

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On supporting full-text retrievals in XML query

  • Hong, Dong-Kweon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.4
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    • pp.274-278
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    • 2007
  • As XML becomes the standard of digital data exchange format we need to manage a lot of XML data effectively. Unlike tables in relational model XML documents are not structural. That makes it difficult to store XML documents as tables in relational model. To solve these problems there have been significant researches in relational database systems. There are two kinds of approaches: 1) One way is to decompose XML documents so that elements of XML match fields of relational tables. 2) The other one stores a whole XML document as a field of relational table. In this paper we adopted the second approach to store XML documents because sometimes it is not easy for us to decompose XML documents and in some cases their element order in documents are very meaningful. We suggest an efficient table schema to store only inverted index as tables to retrieve required data from XML data fields of relational tables and shows SQL translations that correspond to XML full-text retrievals. The functionalities of XML retrieval are based on the W3C XQuery which includes full-text retrievals. In this paper we show the superiority of our method by comparing the performances in terms of a response time and a space to store inverted index. Experiments show our approach uses less space and shows faster response times.

An EFASIT model considering the emotion criteria in Knowledge Monitoring System (지식모니터링시스템에서 감성기준을 고려한 EFASIT 모델)

  • Ryu, Kyung-Hyun;Pi, Su-Young
    • Journal of Internet Computing and Services
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    • v.12 no.4
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    • pp.107-117
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    • 2011
  • The appearance of Web has brought an substantial revolution to all fields of society such knowledge management and business transaction as well as traditional information retrieval. In this paper, we propose an EFASIT(Extended Fuzzy AHP and SImilarity Technology) model considering the emotion analysis. And we combine the Extended Fuzzy AHP Method(EFAM) with SImilarity Technology(SIT) based on the domain corpus information in order to efficiently retrieve the document on the Web. The proposed the EFASIT model can generate the more definite rule according to integration of fuzzy knowledge of various decision-maker, and can give a help to decision-making, and confirms through the experiment.