• Title/Summary/Keyword: Text Search

검색결과 549건 처리시간 0.028초

Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information

  • Oh, Heung-Seon;Jung, Yuchul
    • Journal of Information Science Theory and Practice
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    • 제5권3호
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    • pp.31-47
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    • 2017
  • The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.

Metadata Processing Technique for Similar Image Search of Mobile Platform

  • Seo, Jung-Hee
    • Journal of information and communication convergence engineering
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    • 제19권1호
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    • pp.36-41
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    • 2021
  • Text-based image retrieval is not only cumbersome as it requires the manual input of keywords by the user, but is also limited in the semantic approach of keywords. However, content-based image retrieval enables visual processing by a computer to solve the problems of text retrieval more fundamentally. Vision applications such as extraction and mapping of image characteristics, require the processing of a large amount of data in a mobile environment, rendering efficient power consumption difficult. Hence, an effective image retrieval method on mobile platforms is proposed herein. To provide the visual meaning of keywords to be inserted into images, the efficiency of image retrieval is improved by extracting keywords of exchangeable image file format metadata from images retrieved through a content-based similar image retrieval method and then adding automatic keywords to images captured on mobile devices. Additionally, users can manually add or modify keywords to the image metadata.

지능 정보검색 서비스를 위한 실시간검색어 변화량 평가 (Evaluating real-time search query variation for intelligent information retrieval service)

  • 정민영
    • 디지털융복합연구
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    • 제16권12호
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    • pp.335-342
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    • 2018
  • 포털 사이트의 핵심 서비스인 검색서비스는 입력되는 검색어 중에서 짧은 순간에 급상승하는 검색어를 대상으로 순간 검색빈도가 높은 것을 기준으로 순위별로 제시하는 것이므로 일정기간 동안 관심도가 높은 검색어를 곧바로 알려주기는 힘들다. 따라서 이를 극복하고 검색어 변화에 대한 향상된 분석결과가 나오게 하여 보다 지능적인 정보검색 서비스를 제공하기 위한 노력이 필요하다. 이를 위하여 본 논문에서는 실시간검색어의 관심도와 지속도, 그리고 주목도를 측정할 수 있는 기준을 제시한다. 그리고 그 기준에 맞추어 일정기간 동안 시간, 일간, 주간, 월간 실시간검색어에 대한 변화의 측정과 집계를 하고 이를 통해 관심도가 높은 이슈, 관심이 길게 지속된 이슈, 변화가능성이 커서 앞으로 주목해야 할 이슈를 평가한다.

복합키워드의 고속검색 알고리즘에 관한 연구 (A Study of High Speed Retrieval Algorithm of Long Component Keyword)

  • 이진관;정규철;이태헌;박기홍
    • 한국정보통신학회논문지
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    • 제8권8호
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    • pp.1769-1776
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    • 2004
  • 효율적인 키워드 추출은 정보검색 시스템에서 중요하지만 많은 키워드 중 적당한 키워드를 결정하기 위한 방법들은 여러 가지가 있다. 그중 단일 키워드만을 검색하는 AC알고리즘을 해결하기 위한 DER구조는 복합키워드 검색이 가능하나 많은 검색시간이 걸린다는 문제점을 가지고 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 DER구조의 검색방법을 기반으로 한 독립적인 검색테이블을 확장하여 EDER 구조라는 알고리즘을 구축하였다. 500개의 텍스트 파일을 실험한 결과 키워드의 포스팅 결과가 AC의 DER구조보다 EDER구조가 작았으며, 검색시간 또한 K5에서 DER구조가 0.6초, EDER구조가 0.2초로 더 빠른 검색을 보며주고 있어 제안 방법이 효과적임을 알 수 있었다.

국내 천문학 논문 검색 DB 구축 (CONSTRUCTION OF KOREAN ASTRONOMICAL JOURNAL DB)

  • 성현일;김순욱;임인성
    • 천문학논총
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    • 제21권2호
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    • pp.113-119
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    • 2006
  • The Korean Astronomical Data Center(KADC) in Korea Astronomy and Space Science Institute(KASI) has developed a database of astronomical journals published by the Korean Astronomical Society and the Korean Space Science Society. It consists of all bibliographic records of the Journal of the Korean Astronomical Society(JKAS), Publication of the Korean Astronomical Society(PKAS), and Journal of Astronomy & Space Sciences(JASS). The KADC provides useful search functions in the search page such as search criterion of bibcode, publication date, author names, title words, or abstract words. The journal name is one of the search criterion in which more than one journal can be designated at the same time. The criterion of author name is provided bilingually: English or Korean. The abstract and full text can be downloaded as PDF files. It is also possible to search papers related to a specific research topic published in Korean astronomical journals, provided by the KADC, which often cannot be found the worldwide, Astrophysics Data System(ADS) services. The KADC will become basic infrastructure for the systematic construction of bibliographic records, and hence, make the society of Korean astronomers more interactive and collaborative.

Discovery Layer in Library Retrieval: VuFind as an Open Source Service for Academic Libraries in Developing Countries

  • Roy, Bijan Kumar;Mukhopadhyay, Parthasarathi;Biswas, Anirban
    • Journal of Information Science Theory and Practice
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    • 제10권4호
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    • pp.3-22
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    • 2022
  • This paper provides an overview of the emergence of resource discovery systems and services, along with their advantages, best practices, and current landscapes. It outlines some of the key services and functionalities of a comprehensive discovery model suitable for academic libraries in developing countries. The proposed model (VuFind as a discovery tool) performs like other existing web-scale resource discovery systems, both commercial and open-source, and is capable of providing information resources from different sources in a single-window search interface. The objective of the paper is to provide seamless access to globally distributed subscribed as well as open access resources through its discovery interface, based on a unified index. This model uses Koha, DSpace, and Greenstone as back-ends and VuFind as a discovery layer in the front-end and has also integrated many enhanced search features like Bento-box search, Geodetic search, and full-text search (using Apache Tika). The goal of this paper is to provide the academic community with a one-stop shop for better utilising and integrating heterogeneous bibliographic data sources with VuFind (https://vufind.org/vufind).

Probabilistic Model for Performance Analysis of a Heuristic with Multi-byte Suffix Matching

  • Choi, Yoon-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권4호
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    • pp.711-725
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    • 2013
  • A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

Document Classification Model Using Web Documents for Balancing Training Corpus Size per Category

  • Park, So-Young;Chang, Juno;Kihl, Taesuk
    • Journal of information and communication convergence engineering
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    • 제11권4호
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    • pp.268-273
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    • 2013
  • In this paper, we propose a document classification model using Web documents as a part of the training corpus in order to resolve the imbalance of the training corpus size per category. For the purpose of retrieving the Web documents closely related to each category, the proposed document classification model calculates the matching score between word features and each category, and generates a Web search query by combining the higher-ranked word features and the category title. Then, the proposed document classification model sends each combined query to the open application programming interface of the Web search engine, and receives the snippet results retrieved from the Web search engine. Finally, the proposed document classification model adds these snippet results as Web documents to the training corpus. Experimental results show that the method that considers the balance of the training corpus size per category exhibits better performance in some categories with small training sets.