M-Eco enhanced Adaptation Service (D5.2)

Peter Dolog, Frederico Durao, Ricardo Gomes Lage, Martin Leginus, Rong Pan

Publikation: Bog/antologi/afhandling/rapportRapportForskning

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Resumé

In this report, we present the improvements of the Adaptive Tuning and Personalization (WP5) component of the M-Eco system. This component is focused on four main areas of interest to users of surveillance systems: presentation options for recommendation and adaptation, user and group models, user classification and modeling algorithms, and recommendation, adaptation and personalization strategies. In each of these areas, we propose new methods and improvements over those presented in the previous deliverable. For example, we extend the user profiling with the user's stated preferences for a set of locations and we propose new approaches for recommendations to groups and navigation through documents using tags. The extensions and new methods address diverse aspects of the M-Eco system such as motivation scenarios, configuration management, formal models, implementations and some real use case scenarios on how personalization can be applied to support medical surveillance. The result of personalization can be seen, for example, as a reordering on the ranking of recommendations or search results or a personalized tag cloud leading users to quick access the information fulfilling the users interests. The main contributions of the report are spatial reasoning methods evaluated in group recommendations, personalized tag clouds, and web services integration.
OriginalsprogEngelsk
Antal sider68
StatusUdgivet - 2012

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Dolog, P., Durao, F., Lage, R. G., Leginus, M., & Pan, R. (2012). M-Eco enhanced Adaptation Service (D5.2).
Dolog, Peter ; Durao, Frederico ; Lage, Ricardo Gomes ; Leginus, Martin ; Pan, Rong. / M-Eco enhanced Adaptation Service (D5.2). 2012. 68 s.
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abstract = "In this report, we present the improvements of the Adaptive Tuning and Personalization (WP5) component of the M-Eco system. This component is focused on four main areas of interest to users of surveillance systems: presentation options for recommendation and adaptation, user and group models, user classification and modeling algorithms, and recommendation, adaptation and personalization strategies. In each of these areas, we propose new methods and improvements over those presented in the previous deliverable. For example, we extend the user profiling with the user's stated preferences for a set of locations and we propose new approaches for recommendations to groups and navigation through documents using tags. The extensions and new methods address diverse aspects of the M-Eco system such as motivation scenarios, configuration management, formal models, implementations and some real use case scenarios on how personalization can be applied to support medical surveillance. The result of personalization can be seen, for example, as a reordering on the ranking of recommendations or search results or a personalized tag cloud leading users to quick access the information fulfilling the users interests. The main contributions of the report are spatial reasoning methods evaluated in group recommendations, personalized tag clouds, and web services integration.",
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Dolog, P, Durao, F, Lage, RG, Leginus, M & Pan, R 2012, M-Eco enhanced Adaptation Service (D5.2).

M-Eco enhanced Adaptation Service (D5.2). / Dolog, Peter; Durao, Frederico; Lage, Ricardo Gomes; Leginus, Martin; Pan, Rong.

2012. 68 s.

Publikation: Bog/antologi/afhandling/rapportRapportForskning

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T1 - M-Eco enhanced Adaptation Service (D5.2)

AU - Dolog, Peter

AU - Durao, Frederico

AU - Lage, Ricardo Gomes

AU - Leginus, Martin

AU - Pan, Rong

PY - 2012

Y1 - 2012

N2 - In this report, we present the improvements of the Adaptive Tuning and Personalization (WP5) component of the M-Eco system. This component is focused on four main areas of interest to users of surveillance systems: presentation options for recommendation and adaptation, user and group models, user classification and modeling algorithms, and recommendation, adaptation and personalization strategies. In each of these areas, we propose new methods and improvements over those presented in the previous deliverable. For example, we extend the user profiling with the user's stated preferences for a set of locations and we propose new approaches for recommendations to groups and navigation through documents using tags. The extensions and new methods address diverse aspects of the M-Eco system such as motivation scenarios, configuration management, formal models, implementations and some real use case scenarios on how personalization can be applied to support medical surveillance. The result of personalization can be seen, for example, as a reordering on the ranking of recommendations or search results or a personalized tag cloud leading users to quick access the information fulfilling the users interests. The main contributions of the report are spatial reasoning methods evaluated in group recommendations, personalized tag clouds, and web services integration.

AB - In this report, we present the improvements of the Adaptive Tuning and Personalization (WP5) component of the M-Eco system. This component is focused on four main areas of interest to users of surveillance systems: presentation options for recommendation and adaptation, user and group models, user classification and modeling algorithms, and recommendation, adaptation and personalization strategies. In each of these areas, we propose new methods and improvements over those presented in the previous deliverable. For example, we extend the user profiling with the user's stated preferences for a set of locations and we propose new approaches for recommendations to groups and navigation through documents using tags. The extensions and new methods address diverse aspects of the M-Eco system such as motivation scenarios, configuration management, formal models, implementations and some real use case scenarios on how personalization can be applied to support medical surveillance. The result of personalization can be seen, for example, as a reordering on the ranking of recommendations or search results or a personalized tag cloud leading users to quick access the information fulfilling the users interests. The main contributions of the report are spatial reasoning methods evaluated in group recommendations, personalized tag clouds, and web services integration.

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KW - recommender system

KW - tag cloud

KW - group recommendation

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Dolog P, Durao F, Lage RG, Leginus M, Pan R. M-Eco enhanced Adaptation Service (D5.2). 2012. 68 s.