Learning browsing patterns for context-aware recommendation
- Autores
- Godoy, Daniela Lis; Amandi, Analía
- Año de publicación
- 2006
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities.
IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Patterns
Information browsers - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
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- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23858
Ver los metadatos del registro completo
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Learning browsing patterns for context-aware recommendationGodoy, Daniela LisAmandi, AnalíaCiencias InformáticasPatternsInformation browsersThe success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities.IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1Red de Universidades con Carreras en Informática (RedUNCI)2006-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23858enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:37:10Zoai:sedici.unlp.edu.ar:10915/23858Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:37:10.226SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Learning browsing patterns for context-aware recommendation |
| title |
Learning browsing patterns for context-aware recommendation |
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Learning browsing patterns for context-aware recommendation Godoy, Daniela Lis Ciencias Informáticas Patterns Information browsers |
| title_short |
Learning browsing patterns for context-aware recommendation |
| title_full |
Learning browsing patterns for context-aware recommendation |
| title_fullStr |
Learning browsing patterns for context-aware recommendation |
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Learning browsing patterns for context-aware recommendation |
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Learning browsing patterns for context-aware recommendation |
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Godoy, Daniela Lis Amandi, Analía |
| author |
Godoy, Daniela Lis |
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Godoy, Daniela Lis Amandi, Analía |
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author |
| author2 |
Amandi, Analía |
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author |
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Ciencias Informáticas Patterns Information browsers |
| topic |
Ciencias Informáticas Patterns Information browsers |
| dc.description.none.fl_txt_mv |
The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities. IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1 Red de Universidades con Carreras en Informática (RedUNCI) |
| description |
The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities. |
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2006 |
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2006-08 |
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