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An Efficient Semantic Ranked Keyword Search of Big Data Using Map Reduce

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJDTA) 바로가기
  • 간행물
    International Journal of Database Theory and Application SCOPUS 바로가기
  • 통권
    Vol.8 No.6 (2015.12)바로가기
  • 페이지
    pp.47-56
  • 저자
    P. Srinivasa Rao, M.H.M. Krishna Prasad, K. Thammi Reddy
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A267539

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원문정보

초록

영어
Information retrieval is fast becoming the prevailing form of information access, surpassing traditional database style searching. Ontologies have become the tool of choice employed in many information retrieval systems and more prominently in semantic information retrieval. In order to overcome the disadvantages in key word based information retrieval systems, which transfer irrelevant information, ontology has been designed. A system with ontology mimics the real world, where every task is laced with certain meaning as this is basic idea behind knowledge processing. Hadoop, which is an open source frame work for storing and processing large datasets, is used for pre-processing the text documents. First, a set of text documents are considered. Pre-processing is performed on a large domain of data using Hadoop MapReduce. This includes the removal of the stop words along with stemming and excluding less frequency words. Despite this pre-processing, owing to the colossal number of index terms still floating in the considered domain data, the problem of high dimensionality is encountered. Therefore the dimensionality of such a group of terms is reduced by identifying it as a concept and those concepts can be viewed as a single dimension in a ontology based information retrieval system. Now ontology is constructed by assigning synonym set to each concept in this structure using tools like word net. Thus constructed ontology can be mapped on to the processed query which gives us the relevant information from the data pool considered.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Methodology
  3.1. Pre-Processing
  3.2. Clustering
 4. Experimentation
  4.1. Environment Setup
 5. Conclusions and Future Work
 References

키워드

MapReduce Bigdata Hadoop Datamining Information Retrieval System

저자

  • P. Srinivasa Rao [ Associate Professor, Professor, Professor Dept.of CSE, MVGRCE, Dept.of CSE, JNTUK, Dept.of CSE GITAM University Vizianagaram, Kakinada, Visakhapatnam ]
  • M.H.M. Krishna Prasad [ Associate Professor, Professor, Professor Dept.of CSE, MVGRCE, Dept.of CSE, JNTUK, Dept.of CSE GITAM University Vizianagaram, Kakinada, Visakhapatnam ]
  • K. Thammi Reddy [ Associate Professor, Professor, Professor Dept.of CSE, MVGRCE, Dept.of CSE, JNTUK, Dept.of CSE GITAM University Vizianagaram, Kakinada, Visakhapatnam ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJDTA) [Science & Engineering Research Support Center, Republic of Korea(IJDTA)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Database Theory and Application
  • 간기
    격월간
  • pISSN
    2005-4270
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

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