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Improving Retrieval of Information f...

Zhao, Ruoxuan.

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Improving Retrieval of Information from the Internet.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Improving Retrieval of Information from the Internet./
Author:	Zhao, Ruoxuan.
Description:	167 p.
Notes:	Source: Masters Abstracts International, Volume: 51-04.
Contained By:	Masters Abstracts International51-04(E).
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR84918
ISBN:	9780494849187

Improving Retrieval of Information from the Internet.
Zhao, Ruoxuan.

Improving Retrieval of Information from the Internet. - 167 p.

Source: Masters Abstracts International, Volume: 51-04.

Thesis (M.Sc.)--University of Windsor (Canada), 2013.

To improve the quality of the search result returned by the internet which makes users have to look through a huge amount of links for the real answers, we utilized the high quality links Google produces and the Information Retrieval technology to implement a Question Answering (QA) system. This system analyzes and downloads the text contents from the relevant web pages Google searches based on the users' questions to build a dynamic knowledge collection; retrieves the relevant passages from the collection and sends the ranked passages back. The users can further refine their questions in the query refinement step for the better answers. A novel search strategy was designed to detect the semantic connections between the question and the documents. This answer retrieval also involves the TF-IDF algorithm and Vector Space Model for the document indexing. We have modified the original Cosine Coefficient Similarity Measurement to rank the candidate answers.

ISBN: 9780494849187Subjects--Topical Terms:

626642
Computer Science.

Improving Retrieval of Information from the Internet.
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100 1 $a Zhao, Ruoxuan. $3 2099295
245 1 0 $a Improving Retrieval of Information from the Internet.
300 $a 167 p.
500 $a Source: Masters Abstracts International, Volume: 51-04.
500 $a Adviser: Joan Morrissey.
502 $a Thesis (M.Sc.)--University of Windsor (Canada), 2013.
520 $a To improve the quality of the search result returned by the internet which makes users have to look through a huge amount of links for the real answers, we utilized the high quality links Google produces and the Information Retrieval technology to implement a Question Answering (QA) system. This system analyzes and downloads the text contents from the relevant web pages Google searches based on the users' questions to build a dynamic knowledge collection; retrieves the relevant passages from the collection and sends the ranked passages back. The users can further refine their questions in the query refinement step for the better answers. A novel search strategy was designed to detect the semantic connections between the question and the documents. This answer retrieval also involves the TF-IDF algorithm and Vector Space Model for the document indexing. We have modified the original Cosine Coefficient Similarity Measurement to rank the candidate answers.
590 $a School code: 0115.
650 4 $a Computer Science. $3 626642
650 4 $a Information Science. $3 1017528
650 4 $a Web Studies. $3 1026830
690 $a 0984
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710 2 $a University of Windsor (Canada). $b Computer Science. $3 2092546
773 0 $t Masters Abstracts International $g 51-04(E).
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791 $a M.Sc.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR84918