Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery
This paper presents a distributed client-server architecture for the personalized delivery of textual news content to mobile users. The user profile consists of two separate models, that is, the long-term interests are stored in a skeleton profile on the server and the short-term interests in a deta...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2008-01-01
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| Series: | International Journal of Digital Multimedia Broadcasting |
| Online Access: | http://dx.doi.org/10.1155/2008/863613 |
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| _version_ | 1832556929118896128 |
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| author | Maria Papadogiorgaki Vasileios Papastathis Evangelia Nidelkou Simon Waddington Ben Bratu Myriam Ribiere Ioannis Kompatsiaris |
| author_facet | Maria Papadogiorgaki Vasileios Papastathis Evangelia Nidelkou Simon Waddington Ben Bratu Myriam Ribiere Ioannis Kompatsiaris |
| author_sort | Maria Papadogiorgaki |
| collection | DOAJ |
| description | This paper presents a distributed client-server architecture for the personalized delivery of textual news content to mobile users. The user profile consists of two separate models, that is, the long-term interests are stored in a skeleton profile on the server and the short-term interests in a detailed profile in the handset. The user profile enables a high-level filtering of available news content on the server, followed by matching of detailed user preferences in the handset. The highest rated items are recommended to the user, by employing an efficient ranking process. The paper focuses on a two-level learning process, which is employed on the client side in order to automatically update both user profile models. It involves the use of machine learning algorithms applied to the implicit and explicit user feedback. The system's learning performance has been systematically evaluated based on data collected from regular system users. |
| format | Article |
| id | doaj-art-f8f67a0c95954ac0a280fef8f6d57c57 |
| institution | Kabale University |
| issn | 1687-7578 1687-7586 |
| language | English |
| publishDate | 2008-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Digital Multimedia Broadcasting |
| spelling | doaj-art-f8f67a0c95954ac0a280fef8f6d57c572025-02-03T05:44:07ZengWileyInternational Journal of Digital Multimedia Broadcasting1687-75781687-75862008-01-01200810.1155/2008/863613863613Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content DeliveryMaria Papadogiorgaki0Vasileios Papastathis1Evangelia Nidelkou2Simon Waddington3Ben Bratu4Myriam Ribiere5Ioannis Kompatsiaris6Centre for Research and Technology Hellas (CERTH), Informatics and Telematics Institute (ITI), 1st Km Thermi-Panorama Road, Thessaloniki 57001, GreeceCentre for Research and Technology Hellas (CERTH), Informatics and Telematics Institute (ITI), 1st Km Thermi-Panorama Road, Thessaloniki 57001, GreeceCentre for Research and Technology Hellas (CERTH), Informatics and Telematics Institute (ITI), 1st Km Thermi-Panorama Road, Thessaloniki 57001, GreeceMotorola Labs, Motorola Ltd., Jays Close, Viables Industrial Estate, Basingstoke, Hampshire, RG22 4PD, UKMotorola Labs, Parc Les Algorithmes, Saint Aubin, 91193 Gif sur Yvette Cedex, FranceMotorola Labs, Parc Les Algorithmes, Saint Aubin, 91193 Gif sur Yvette Cedex, FranceCentre for Research and Technology Hellas (CERTH), Informatics and Telematics Institute (ITI), 1st Km Thermi-Panorama Road, Thessaloniki 57001, GreeceThis paper presents a distributed client-server architecture for the personalized delivery of textual news content to mobile users. The user profile consists of two separate models, that is, the long-term interests are stored in a skeleton profile on the server and the short-term interests in a detailed profile in the handset. The user profile enables a high-level filtering of available news content on the server, followed by matching of detailed user preferences in the handset. The highest rated items are recommended to the user, by employing an efficient ranking process. The paper focuses on a two-level learning process, which is employed on the client side in order to automatically update both user profile models. It involves the use of machine learning algorithms applied to the implicit and explicit user feedback. The system's learning performance has been systematically evaluated based on data collected from regular system users.http://dx.doi.org/10.1155/2008/863613 |
| spellingShingle | Maria Papadogiorgaki Vasileios Papastathis Evangelia Nidelkou Simon Waddington Ben Bratu Myriam Ribiere Ioannis Kompatsiaris Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery International Journal of Digital Multimedia Broadcasting |
| title | Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery |
| title_full | Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery |
| title_fullStr | Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery |
| title_full_unstemmed | Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery |
| title_short | Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery |
| title_sort | two level automatic adaptation of a distributed user profile for personalized news content delivery |
| url | http://dx.doi.org/10.1155/2008/863613 |
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