| Records |
| Author |
Vargas-Vera, M.; Nagy, M.; De Pablos, P.O. |
| Title |
A Framework For Detecting And Removing Knowledge Overlaps In A Collaborative Environment: Case Of Study A Computer Configuration Problem |
Type |
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| Year |
2013 |
Publication |
Journal Of Web Engineering |
Abbreviated Journal |
J. Web Eng. |
| Volume |
12 |
Issue |
5 |
Pages |
422-438 |
| Keywords |
Knowledge-based systems; Knowledge integration; Configuration |
| Abstract |
This paper presents a framework for knowledge integration based on mappings between similar concepts in constraint graphs associated to a configuration problem. In particular, the paper deals with one of the problems which could arise when performing collaborative knowledge integration, namely detecting knowledge overlaps. The solution to the overlapping problem relies on the use of matching algorithms embedded in DSSim (short for Dempster-Shafer Similarity). To illustrate the approach, a case study of a computer configuration problem is presented. The solution to the knowledge overlap problem is important as it has the promise to become an alternative approach for the current knowledge integration solutions. Through our approach the real cost of integration can be reduced as it is not necessary to invest a great amount of resources beforehand a truly integrated system can be operational. |
| Address |
[Vargas-Vera, Maria] Univ Adolfo Ibanez, Ctr Invest Informat, Fac Ingn & Ciencias, Vinia Del Mar, Chile, Email: maria.vargas-vera@uai.cl; |
| Corporate Author |
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Thesis |
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| Publisher |
Rinton Press, Inc |
Place of Publication  |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1540-9589 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000324004200005 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
309 |
| Permanent link to this record |
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| Author |
Vargas-Vera, M.; Nagy, M. |
| Title |
Establishing agent trust for contradictory evidence by means of fuzzy voting model: An ontology mapping case study |
Type |
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| Year |
2014 |
Publication |
Computers In Human Behavior |
Abbreviated Journal |
Comput. Hum. Behav. |
| Volume |
30 |
Issue |
|
Pages |
745-752 |
| Keywords |
Ontology mapping; Semantic Web; Multi-agent systems; Uncertain reasoning |
| Abstract |
This paper introduces a novel trust assessment formalism for contradicting evidence in the context of multi-agent ontology mapping. Evidence combination using the Dempster rule tend to ignore contradictory evidence and the contemporary approaches for managing these conflicts introduce additional computation complexity i.e. increased response time of the system. On the Semantic Web, ontology mapping systems that need to interact with end users in real time cannot afford prolonged computation. In this work, we have made a step towards the formalisation of eliminating contradicting evidence, to utilise the original Dempster's combination rule without introducing additional complexity. Our proposed solution incorporates the fuzzy voting model to the Dempster-Shafer theory. Finally, we present a case study where we show how our approach improves the ontology mapping problem. (C) 2013 Elsevier Ltd. All rights reserved. |
| Address |
[Vargas-Vera, Maria] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Ctr Invest Informar & Telecomunicac, Vinia Del Mar, Chile, Email: maria.vargas-vera@uai.cl; |
| Corporate Author |
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Thesis |
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| Publisher |
Pergamon-Elsevier Science Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Volume |
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Edition |
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| ISSN |
0747-5632 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000330090900084 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
344 |
| Permanent link to this record |
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| Author |
Vargas-Vera, M. |
| Title |
A Framework for Extraction of Relations from Text using Relational Learning and Similarity Measures |
Type |
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| Year |
2015 |
Publication |
Journal Of Universal Computer Science |
Abbreviated Journal |
J. Univers. Comput. Sci. |
| Volume |
21 |
Issue |
11 |
Pages |
1482-1495 |
| Keywords |
Semantic Learning; Relational Learning; Similarity Measures; Semantic Web |
| Abstract |
Named entity recognition (NER) has been studied largely in the Information Extraction community as it is one step in the construction of an Information Extraction System. However, to extract only names without contextual information is not sufficient if we want to be able to describe facts encountered in documents, in particular, academic documents. Then, there is a need for extracting relations between entities. This task is accomplished using relational learning algorithms embedded in an Information Extraction framework. In particular, we have extended two relational learning frameworks RAPIER and FOIL. Our proposed extended frameworks are equipped with DSSim (short for Dempster-Shafer Similarity) our similarity service. Both extended frameworks were tested using an electronic newsletter consisting of news articles describing activities or events happening in an academic institution as our main application is on education. |
| Address |
[Vargas-Vera, Maria] Adolfo Ibanez Univ, Vinia Del Mar, Chile, Email: mvargasvera@gmail.com |
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Thesis |
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| Publisher |
Graz Univ Technolgoy, Inst Information Systems Computer Media-Iicm |
Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Issue |
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Edition |
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| ISSN |
0948-695x |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000368457300008 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
578 |
| Permanent link to this record |
