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(A) new framework for entity search using sub-document level indexing and consensus ranking

(A) new framework for entity search using sub-document level indexing and consensus ranking

Material type
학위논문
Personal Author
최재훈 崔載薰
Title Statement
(A) new framework for entity search using sub-document level indexing and consensus ranking / Jaehoon Choi
Publication, Distribution, etc
Seoul :   Graduate School, Korea University,   2017  
Physical Medium
iv, 43장 : 삽화 ; 26 cm
기타형태 저록
A new framework for entity search using sub-document level indexing and consensus ranking   (DCOLL211009)000000072553  
학위논문주기
학위논문(박사)-- 고려대학교 대학원: 컴퓨터·전파통신공학과, 2017. 2
학과코드
0510   6YD36   316  
General Note
지도교수: 姜在雨  
Bibliography, Etc. Note
참고문헌: 장 40-43
이용가능한 다른형태자료
PDF 파일로도 이용가능;   Requires PDF file reader(application/pdf)  
비통제주제어
opinion mining , consensus search , subdocument level indexing , sentiment analysis,,
000 00000nam c2200205 c 4500
001 000045897594
005 20170329132613
007 ta
008 170103s2017 ulka bmAC 000c eng
040 ▼a 211009 ▼c 211009 ▼d 211009
085 0 ▼a 0510 ▼2 KDCP
090 ▼a 0510 ▼b 6YD36 ▼c 316
100 1 ▼a 최재훈 ▼g 崔載薰
245 1 1 ▼a (A) new framework for entity search using sub-document level indexing and consensus ranking / ▼d Jaehoon Choi
260 ▼a Seoul : ▼b Graduate School, Korea University, ▼c 2017
300 ▼a iv, 43장 : ▼b 삽화 ; ▼c 26 cm
500 ▼a 지도교수: 姜在雨
502 1 ▼a 학위논문(박사)-- ▼b 고려대학교 대학원: ▼c 컴퓨터·전파통신공학과, ▼d 2017. 2
504 ▼a 참고문헌: 장 40-43
530 ▼a PDF 파일로도 이용가능; ▼c Requires PDF file reader(application/pdf)
653 ▼a opinion mining ▼a consensus search ▼a subdocument level indexing ▼a sentiment analysis
776 0 ▼t A new framework for entity search using sub-document level indexing and consensus ranking ▼w (DCOLL211009)000000072553
900 1 0 ▼a Choi, Jae-hoon, ▼e
900 1 0 ▼a 강재우 ▼g 姜在雨, ▼e 지도교수
945 ▼a KLPA

Electronic Information

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(A) new framework for entity search using sub-document level indexing and consensus ranking (35회 열람)
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No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Stacks(Thesis)/ Call Number 0510 6YD36 316 Accession No. 123055699 Availability Available Due Date Make a Reservation Service B M

Contents information

Abstract

Search engines have become the necessities of life, today. Especially, a great part of searches are informational types. The purpose of informational search is getting useful information what user wants to know about topics such as movie, restaurant or even bio-medical. Due to the traditional structure of search engine, it has a limitation to retrieve rich information as results. Typical search system returns a list of documents. It’s very efficient for navigational or transnational search, but not for informational. In
case of an informational search, users have to go through the contents of documents to get information.
In order to address this problem, we introduce a new entity search framework named Consento designed to answer informational queries. This framework performs subdocument level indexing, as opposed to document indexing, to return semantic enhanced results. In particular, we define a new indexing unit, Maximal Coherent Semantic Unit (MCSU). An MCSU represents a segment of a document, which captures a single coherent
semantic. We also introduce a new ranking method, called ConsensusRank that counts captured semantics referring to an entity as a weighted vote. In order to validate the
efficacy of the proposed framework, we compare with standard retrieval models and their recent extensions for entity ranking. Experiments using bio medical, movie, hotel and restaurant data show the effectiveness of our framework.

Table of Contents

Abstract
Contents i
List of Figures iii
List of Tables iv
1 Introduction 1
2 Related Work 7
3 Consento architecture 10
3.1 Indexing Subsystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1.1 Preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1.2 Content Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1.3 Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.2 Search Subsystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2.1 Query Parsing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2.2 Retrieval and Ranking . . . . . . . . . . . . . . . . . . . . . . . . . 18
4 Validation 22
4.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.2 Comparison with Baselines . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5 Smith Search: Consento based Restaurant Search System 31
5.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.2 Smith Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.4 System Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
6 Conclusion 38
Bibliography 40
Acknowledgement
ii

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