Topic-based vector space model - Revision history

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2020-10-05T22:03:28Z

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← Previous revision		Revision as of 22:03, 5 October 2020
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	The '''Topic-based Vector Space Model (TVSM)'''<ref>{{~~cite~~ \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author1=Dominik Kuropka \| author2=Jörg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[vector space model]] of [[information retrieval]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.		The '''Topic-based Vector Space Model (TVSM)'''<ref>{{citation \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author1=Dominik Kuropka \| author2=Jörg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[vector space model]] of [[information retrieval]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.
	In contrast to the [[generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.		In contrast to the [[generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.

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	==Enhanced Topic-based Vector Space Model==		==Enhanced Topic-based Vector Space Model==
	The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{~~cite~~ \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author1=Dominik Kuropka \| author2=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similar to Vector Space model.		The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{citation \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author1=Dominik Kuropka \| author2=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similar to Vector Space model.

	==Implementations==		==Implementations==

Sietse Snel: fix deprecated reference syntax

2016-04-06T19:10:11Z

fix deprecated reference syntax

← Previous revision		Revision as of 19:10, 6 April 2016
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	The '''Topic-based Vector Space Model (TVSM)'''<ref>{{cite \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| ~~author~~=Dominik Kuropka \| ~~coauthors~~=~~Jorg~~ Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[vector space model]] of [[information retrieval]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.		The '''Topic-based Vector Space Model (TVSM)'''<ref>{{cite \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author1=Dominik Kuropka \| author2=Jörg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[vector space model]] of [[information retrieval]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.
	In contrast to the [[generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.		In contrast to the [[generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.

Line 6:		Line 6:

	==Enhanced Topic-based Vector Space Model==		==Enhanced Topic-based Vector Space Model==
	The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{cite \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| ~~author~~=Dominik Kuropka \| ~~coauthors~~=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similar to Vector Space model.		The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{cite \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author1=Dominik Kuropka \| author2=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similar to Vector Space model.

	==Implementations==		==Implementations==

Qwertyus: cat:VSM

2012-07-18T22:24:53Z

cat:VSM

← Previous revision		Revision as of 22:24, 18 July 2012
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	The Topic-based Vector Space Model (TVSM)<ref>{{cite \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author=Dominik Kuropka \| coauthors=Jorg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[~~Vector~~ space model]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.		The '''Topic-based Vector Space Model (TVSM)'''<ref>{{cite \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author=Dominik Kuropka \| coauthors=Jorg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[vector space model]] of [[information retrieval]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.
	In contrast to the [[~~Generalized~~ vector space model]] the TVSM does not depend on concurrence-based similarities between terms.		In contrast to the [[generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.

	==Definitions==		==Definitions==
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	{{reflist}}		{{reflist}}

	[[Category:~~Information~~ ~~retrieval~~]]		[[Category:Vector space model]]

Vanished user 3.1415926535897932384626433: /* Enhanced Topic-based Vector Space Model */

2010-02-05T05:33:55Z

Enhanced Topic-based Vector Space Model

← Previous revision		Revision as of 05:33, 5 February 2010
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	==Enhanced Topic-based Vector Space Model==		==Enhanced Topic-based Vector Space Model==
	The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{cite \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author=Dominik Kuropka \| coauthors=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are ~~similiar~~ to Vector Space model.		The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{cite \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author=Dominik Kuropka \| coauthors=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similar to Vector Space model.

	==Implementations==		==Implementations==

Riclas at 22:17, 25 January 2010

2010-01-25T22:17:39Z

← Previous revision		Revision as of 22:17, 25 January 2010
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			The Topic-based Vector Space Model (TVSM)<ref>{{cite \| url=http://www.kuropka.net/files/TVSM.pdf \| title=Topic-based Vector Space Model \| author=Dominik Kuropka \| coauthors=Jorg Becker \| year=2003}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) extends the [[Vector space model]] by removing the constraint that the term-vectors be orthogonal. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms and strong related terms. This facilitates the use of stopword lists, stemming and thesaurus in TVSM.
	#redirect [[Vector space model]]
			In contrast to the [[Generalized vector space model]] the TVSM does not depend on concurrence-based similarities between terms.

			==Definitions==
			The basic premise of TVSM is the existence of a ''d'' dimensional space ''R'' with only positive axis intercepts, i.e. ''R in R<sup>+</sup>'' and ''d in N<sup>+</sup>''. Each dimension of ''R'' represents a fundamental topic. A term vector ''t'' has a specific weight for a certain ''R''. To calculate these weights assumptions are made taking into account the document contents. Ideally important terms will have a high weight and stopwords and irrelevants terms to the topic will have a low weight. The TVSM document model is obtained as a sum of term vectors representing terms in the document. The similarity between two documents ''Di'' and ''Dj'' is defined as the scalar product of document vectors.

			==Enhanced Topic-based Vector Space Model==
			The enhancement of the Enhanced Topic-based Vector Space Model (eTVSM)<ref>{{cite \| url= http://kuropka.net/files/HPI_Evaluation_of_eTVSM.pdf \| author=Dominik Kuropka \| coauthors=Artem Polyvyanyy \| title=A Quantitative Evaluation of the Enhanced Topic-Based Vector Space Model \| year=2007}}</ref> (literature: [http://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=0514&lng=eng&id=]) is a proposal on how to derive term vectors from an [[Ontology_(information_science) \| Ontology]]. Using a synonym Ontology created from [[WordNet]] Kuropka shows good results for document similarity. If a trivial Ontology is used the results are similiar to Vector Space model.

			==Implementations==
			* [http://sourceforge.net/projects/etvsm/ Implementation of eTVSM in python]

			== References ==
			{{reflist}}

			[[Category:Information retrieval]]

Rossami: redirect per VfD decision

2005-06-21T22:06:56Z

redirect per VfD decision

← Previous revision		Revision as of 22:06, 21 June 2005
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			#redirect [[Vector space model]]
	{{VfD}}

	{{cleanup}}

	In automatic information filtering and [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on concurrence-based similarities between terms.

	==External links==

	* [http://www.kuropka.net/files/TVSM.pdf Description of the topic-based vector space model].

	{{comp-sci-stub}}

Jitse Niesen: spelling

2005-06-11T10:07:03Z

spelling

← Previous revision		Revision as of 10:07, 11 June 2005
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	{{cleanup}}		{{cleanup}}

	In automatic information filtering and [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on ~~conccurence~~-based similarities between terms.		In automatic information filtering and [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on concurrence-based similarities between terms.

	==External links==		==External links==

Paul August: fixed my typo

2005-06-10T17:53:25Z

fixed my typo

← Previous revision		Revision as of 17:53, 10 June 2005
Line 3:		Line 3:
	{{cleanup}}		{{cleanup}}

	In automatic information ~~filteringand~~ [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on conccurence-based similarities between terms.		In automatic information filtering and [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on conccurence-based similarities between terms.

	==External links==		==External links==

Paul August: change "coocurrence" to "concurrence" (or perhaps should be "co-ocurrence", they are synonyms, but perhaps that's the correct technical term)

2005-06-10T17:52:05Z

change "coocurrence" to "concurrence" (or perhaps should be "co-ocurrence", they are synonyms, but perhaps that's the correct technical term)

← Previous revision		Revision as of 17:52, 10 June 2005
Line 3:		Line 3:
	{{cleanup}}		{{cleanup}}

	In automatic information ~~filtering~~, the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be orthogonal. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on ~~cooccurence~~-based similarities between terms.		In automatic information filteringand [[information retrieval]], the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be [[orthogonal]]. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on conccurence-based similarities between terms.

	==External links==		==External links==

Tony Sidaway: cleanup

2005-06-10T13:20:13Z

cleanup

← Previous revision		Revision as of 13:20, 10 June 2005
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	{{cleanup}}		{{cleanup}}

	~~The~~ '''topic-based vector space model (TVSM)''' extends the [[vector space model]] ~~that~~ ~~way,~~ ~~['''what'''~~ ~~way?]~~ that term-vectors ~~are~~ ~~not necessarily~~ orthogonal ~~any more~~. ~~[Is this about [[epidemiology]], in which vectors are disease-carrying germs, or about vectors in the mathematical sense?]~~ In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on cooccurence-based similarities between terms.		In automatic information filtering, the '''topic-based vector space model (TVSM)''' extends the [[vector space model]] by removing the constraint that the term-vectors must be orthogonal. In contrast to the [[generalized vector space model]] the topic-based vector space model does not depend on cooccurence-based similarities between terms.

	==External links==		==External links==