Trust based personalized recommender system
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/15003 |
Resumo: | We rely on the information from our trustworthy acquaintances to help us take even trivial decisions in our lives. Recommender Systems use the opinions of members of a community to help individuals in that community identify the information most likely to be interesting to them or relevant to their needs. These systems use the similarity between the user and recommenders or between the items to form recommendation list for the user. They do not take into consideration the social trust network between the entities in the society to ensure that the user can trust the recommendations received from the system. The paper proposes a model where a trust network exists between the peer agents and the personalized recommendations are generated on the basis of these trust relationships. The recommenders personalize recommendations by suggesting only those movies to user that matches its taste. Also, the social recommendation process is inherently fuzzy and uncertain. In the society, the information spreads through word-of-mouth and it is not possible to fully trust this information. There is uncertainty in the validity of such information. Again, when a product is recommended, it is suggested with linguistic quantifiers such as very good, more or less good, ordinary, and so on. Thus, uncertainty and fuzziness is inherent in the recommendation process. We have used Intuitionistic Fuzzy Sets to model such uncertainty and fuzziness in the recommendation process. |
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Trust based personalized recommender systemDegree of trustIntuitionistic fuzzy setsUnintentional encountersIntentional encountersWe rely on the information from our trustworthy acquaintances to help us take even trivial decisions in our lives. Recommender Systems use the opinions of members of a community to help individuals in that community identify the information most likely to be interesting to them or relevant to their needs. These systems use the similarity between the user and recommenders or between the items to form recommendation list for the user. They do not take into consideration the social trust network between the entities in the society to ensure that the user can trust the recommendations received from the system. The paper proposes a model where a trust network exists between the peer agents and the personalized recommendations are generated on the basis of these trust relationships. The recommenders personalize recommendations by suggesting only those movies to user that matches its taste. Also, the social recommendation process is inherently fuzzy and uncertain. In the society, the information spreads through word-of-mouth and it is not possible to fully trust this information. There is uncertainty in the validity of such information. Again, when a product is recommended, it is suggested with linguistic quantifiers such as very good, more or less good, ordinary, and so on. Thus, uncertainty and fuzziness is inherent in the recommendation process. We have used Intuitionistic Fuzzy Sets to model such uncertainty and fuzziness in the recommendation process.Universidade Federal de Lavras (UFLA)2006-03-012017-08-01T21:08:44Z2017-08-01T21:08:44Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfBEDI, P.; KAUR, H. Trust based personalized recommender system. INFOCOMP Journal of Computer Science, Lavras, v. 5, n. 1, p. 19-26, Mar. 2006.http://repositorio.ufla.br/jspui/handle/1/15003INFOCOMP; Vol 5 No 1 (2006): March, 2006; 19-261982-33631807-4545reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttp://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/118/103Copyright (c) 2016 INFOCOMP Journal of Computer ScienceAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessBedi, PunamKaur, Harmeet2021-09-23T01:56:55Zoai:localhost:1/15003Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-09-23T01:56:55Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Trust based personalized recommender system |
title |
Trust based personalized recommender system |
spellingShingle |
Trust based personalized recommender system Bedi, Punam Degree of trust Intuitionistic fuzzy sets Unintentional encounters Intentional encounters |
title_short |
Trust based personalized recommender system |
title_full |
Trust based personalized recommender system |
title_fullStr |
Trust based personalized recommender system |
title_full_unstemmed |
Trust based personalized recommender system |
title_sort |
Trust based personalized recommender system |
author |
Bedi, Punam |
author_facet |
Bedi, Punam Kaur, Harmeet |
author_role |
author |
author2 |
Kaur, Harmeet |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Bedi, Punam Kaur, Harmeet |
dc.subject.por.fl_str_mv |
Degree of trust Intuitionistic fuzzy sets Unintentional encounters Intentional encounters |
topic |
Degree of trust Intuitionistic fuzzy sets Unintentional encounters Intentional encounters |
description |
We rely on the information from our trustworthy acquaintances to help us take even trivial decisions in our lives. Recommender Systems use the opinions of members of a community to help individuals in that community identify the information most likely to be interesting to them or relevant to their needs. These systems use the similarity between the user and recommenders or between the items to form recommendation list for the user. They do not take into consideration the social trust network between the entities in the society to ensure that the user can trust the recommendations received from the system. The paper proposes a model where a trust network exists between the peer agents and the personalized recommendations are generated on the basis of these trust relationships. The recommenders personalize recommendations by suggesting only those movies to user that matches its taste. Also, the social recommendation process is inherently fuzzy and uncertain. In the society, the information spreads through word-of-mouth and it is not possible to fully trust this information. There is uncertainty in the validity of such information. Again, when a product is recommended, it is suggested with linguistic quantifiers such as very good, more or less good, ordinary, and so on. Thus, uncertainty and fuzziness is inherent in the recommendation process. We have used Intuitionistic Fuzzy Sets to model such uncertainty and fuzziness in the recommendation process. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-03-01 2017-08-01T21:08:44Z 2017-08-01T21:08:44Z 2017-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
BEDI, P.; KAUR, H. Trust based personalized recommender system. INFOCOMP Journal of Computer Science, Lavras, v. 5, n. 1, p. 19-26, Mar. 2006. http://repositorio.ufla.br/jspui/handle/1/15003 |
identifier_str_mv |
BEDI, P.; KAUR, H. Trust based personalized recommender system. INFOCOMP Journal of Computer Science, Lavras, v. 5, n. 1, p. 19-26, Mar. 2006. |
url |
http://repositorio.ufla.br/jspui/handle/1/15003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/118/103 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras (UFLA) |
publisher.none.fl_str_mv |
Universidade Federal de Lavras (UFLA) |
dc.source.none.fl_str_mv |
INFOCOMP; Vol 5 No 1 (2006): March, 2006; 19-26 1982-3363 1807-4545 reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1784550165578776576 |