國立虎尾科技大學 |

登入

回首頁

Learning Markov Logic Network Struct...

ProQuest Information and Learning Co.

Learning Markov Logic Network Structure by Template Constructing.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Learning Markov Logic Network Structure by Template Constructing./
作者:	Tong, Yingbei.
面頁冊數:	1 online resource (30 pages)
附註:	Source: Masters Abstracts International, Volume: 56-05.
Contained By:	Masters Abstracts International56-05(E).
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9781369884326

Learning Markov Logic Network Structure by Template Constructing.
Tong, Yingbei.

Learning Markov Logic Network Structure by Template Constructing. - 1 online resource (30 pages)

Source: Masters Abstracts International, Volume: 56-05.

Thesis (M.S.)--Iowa State University, 2017.

Includes bibliographical references

Markov logic networks (MLNs) are a statistical relational model that incorporates first- order logic and probability by attaching weights to first-order clauses. However, due to the large search space, the structure learning of MLNs is a computationally expensive problem. In this paper, we present a new algorithm for learning the structure of Markov Logic Network by directly utilizing the data to construct the candidate clauses. Our approach makes use of a Markov Network learning algorithm to construct a template network. We then apply the template to guide the candidate clauses construction process. The experimental results demonstrate that our algorithm is promising.

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

Mode of access: World Wide Web

ISBN: 9781369884326Subjects--Topical Terms:

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

554714
Electronic books.

Learning Markov Logic Network Structure by Template Constructing.
LDR:01840ntm a2200325Ki 4500 001 917026
005 20181005115846.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9781369884326
035 $a (MiAaPQ)AAI10271469
035 $a (MiAaPQ)iastate:16528
035 $a AAI10271469
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Tong, Yingbei. $3 1190931
245 1 0 $a Learning Markov Logic Network Structure by Template Constructing.
264 0 $c 2017
300 $a 1 online resource (30 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-05.
500 $a Adviser: Jin Tian.
502 $a Thesis (M.S.)--Iowa State University, 2017.
504 $a Includes bibliographical references
520 $a Markov logic networks (MLNs) are a statistical relational model that incorporates first- order logic and probability by attaching weights to first-order clauses. However, due to the large search space, the structure learning of MLNs is a computationally expensive problem. In this paper, we present a new algorithm for learning the structure of Markov Logic Network by directly utilizing the data to construct the candidate clauses. Our approach makes use of a Markov Network learning algorithm to construct a template network. We then apply the template to guide the candidate clauses construction process. The experimental results demonstrate that our algorithm is promising.
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
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Iowa State University. $b Computer Science. $3 1190932
773 0 $t Masters Abstracts International $g 56-05(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10271469 $z click for full text (PQDT)

筆 0 讀者評論

多媒體

評論

新增評論分享你的心得

Export

取書館別