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Language Learning Through Comparison.

Babarsad, Omid Bakhshandeh.

Language Learning Through Comparison.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Language Learning Through Comparison./
Author:	Babarsad, Omid Bakhshandeh.
Description:	1 online resource (116 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Contained By:	Dissertation Abstracts International79-02B(E).
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9780355241570

Language Learning Through Comparison.
Babarsad, Omid Bakhshandeh.

Language Learning Through Comparison. - 1 online resource (116 pages)

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)--University of Rochester, 2017.

Includes bibliographical references

Natural Language Understanding (NLU) has been one of the longest-running and the most challenging areas in artificial intelligence. For any natural language comprehension system having a basic understanding of entities and concepts is a primary requirement. Comparison, where we name the similarities and differences between entities and concepts, is a unique cognitive ability in humans which requires memorizing facts, experiencing things and integration of concepts of the world. Clearly, developing NLU systems that are capable of comprehending comparison is a crucial step forward in AI. In this thesis, I will present my research on developing systems that are capable of comprehending comparison, through which, systems can learn world knowledge and perform basic commonsense reasoning.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355241570Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Language Learning Through Comparison.
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100 1 $a Babarsad, Omid Bakhshandeh. $3 1190001
245 1 0 $a Language Learning Through Comparison.
264 0 $c 2017
300 $a 1 online resource (116 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Adviser: James F. Allen.
502 $a Thesis (Ph.D.)--University of Rochester, 2017.
504 $a Includes bibliographical references
520 $a Natural Language Understanding (NLU) has been one of the longest-running and the most challenging areas in artificial intelligence. For any natural language comprehension system having a basic understanding of entities and concepts is a primary requirement. Comparison, where we name the similarities and differences between entities and concepts, is a unique cognitive ability in humans which requires memorizing facts, experiencing things and integration of concepts of the world. Clearly, developing NLU systems that are capable of comprehending comparison is a crucial step forward in AI. In this thesis, I will present my research on developing systems that are capable of comprehending comparison, through which, systems can learn world knowledge and perform basic commonsense reasoning.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Artificial intelligence. $3 559380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0800
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Rochester. $b Engineering and Applied Sciences. $3 1180170
773 0 $t Dissertation Abstracts International $g 79-02B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10618060 $z click for full text (PQDT)

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