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• W2155501445 abstract "The activity of generating Web recommendations has been based in the past mainly on content-based and collaborative-filtering algorithms, that exploit a pre-fixed user’s profile to compare the interests of a user with the content of a Web site and with the profiles of other users. However, some recent proposals introduced the possibility to automatically construct the user’s profile by software agents able to monitor “over the shoulders” the user’s behaviour. This way, the profile can contain some useful information about not only the user’s interest but also the user’s behaviour. For instance, in the CILIOS approach recently presented, the user’s profile contains a logic program, automatically constructed by a neural network-based approach, that represents causal implications about events belonging to the user’s environment. In this paper we propose to use the logic knowledge extracted by CILIOS to support Web recommendation activities. A new type of agent, called CILWEB, is provided with both the CILIOS inductive learning capability and an additional implication-based recommendation algorithm. The introduction of the implication-based recommendations gives to the CILWEB agent the capability of better performing with respect to the traditional recommendation systems, as it is shown by some experimental results." @default.
• W2155501445 created "2016-06-24" @default.
• W2155501445 creator A5035309719 @default.
• W2155501445 date "2010-01-01" @default.
• W2155501445 modified "2023-09-26" @default.
• W2155501445 title "Web Recommender Agents with Inductive Learning Capabilities" @default.
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• W2155501445 doi "https://doi.org/10.1007/978-1-84996-074-8_9" @default.
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