In this paper, we tackle the profile overloading problem. We propose a new method based on co-training algorithm for detecting and removing irrelevant elements.
Several systems such as adaptive systems, etc. provide responses to the user by taking into account, among other, his profile.
Jan 27, 2016 · In this paper, we tackle the profile overloading problem. We propose a new method based on co-training algorithm for detecting and removing ...
Pertinent User Profile based on Adaptive Semi-supervised Learning ...
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This work proposes a virtual integration system founded on ontologies that provides a consensual terminology between the multiple data sources integrated ...
In this paper, we tackle the profile overloading problem. We propose a new method based on co-training algorithm for detecting and removing irrelevant elements.
Rim Zghal Rebaï, Leila Ghorbel , Corinne Amel Zayani , Ikram Amous : Pertinent User Profile based on Adaptive Semi-supervised Learning. KES 2013: 313-320.
In this paper, we tackle the profile overloading problem. We propose a new method based on co-training algorithm for detecting and removing irrelevant elements.
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In this way, we propose in this paper a semi-supervised learning based method for automatically identifying irrelevant profile elements. ... based user profile ...
Pertinent User Profile based on Adaptive Semi-supervised Learning. Rim Zghal Rebaï, Leila Ghorbel, Corinne Amel Zayani, Ikram Amous.
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