Publication statistics

Pub. period:1999-2010
Pub. count:8
Number of co-authors:11



Co-authors

Number of publications with 3 favourite co-authors:

Silvia Schiaffino:3
Marcelo Armentano:2
Daniela Godoy:2

 

 

Productive colleagues

Analia Amandi's 3 most productive colleagues in number of publications:

Marcelo S. Pimenta:5
Isabela Gasparini:3
Silvia Schiaffino:3
 
 
 

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Analia Amandi

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Publications by Analia Amandi (bibliography)

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2010
 
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Schiaffino, Silvia, Armentano, Marcelo and Amandi, Analia (2010): Building respectful interface agents. In International Journal of Human-Computer Studies, 68 (4) pp. 209-222.

To provide personalized assistance to users, interface agents have to learn not only a user's preferences and interests with respect to a software application, but also when and how the user prefers to be assisted. Interface agents have to detect the user's intention to determine when to assist the user, and the user's interaction and interruption preferences to provide the right type of assistance without hindering the user's work. In this work we describe a user profiling approach that considers these issues within a user profile and a decision making approach that enables the agent to choose the best type of assistance for a given user in a given situation. We also describe the results obtained when evaluating our proposal in the tourism domain, and we compare these results with some previous ones in the calendar management domain.

© All rights reserved Schiaffino et al. and/or Academic Press

2008
 
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Garca, Patricio, Schiaffino, Silvia N. and Amandi, Analia (2008): An enhanced Bayesian model to detect students' learning styles in Web-based courses. In J. Comp. Assisted Learning, 24 (4) pp. 305-315.

 
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Schiaffino, Silvia, Amandi, Analia, Gasparini, Isabela and Pimenta, Marcelo S. (2008): Personalization in e-learning: the adaptive system vs. the intelligent agent approaches. In: Proceedings of the 2008 Brazilian Symposium on Human Factors in Computing Systems 2008. pp. 186-195.

Nowadays it is essential to obtain personalization in e-learning, to provide help to students' activities in this environment. There are two main research directions that aim at providing personalization in e-learning: adaptive educational systems and intelligent tutors (agents). This paper presents the adaptability approach designed for the AdaptWeb system and the eTeacher agent, describing design and implementation issues, and discussing results obtained from students' evaluation in these real applications. Then, this paper presents a comparison about them.

© All rights reserved Schiaffino et al. and/or Sociedade Brasileira de Computao

2006
 
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Villaverde, J., Godoy, Daniela and Amandi, Analia (2006): Learning styles' recognition in e-learning environments with feed-forward neural networks. In J. Comp. Assisted Learning, 22 (3) pp. 197-206.

2005
 
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Godoy, Daniela and Amandi, Analia (2005): User Profiling for Web Page Filtering. In IEEE Internet Computing, 9 (4) pp. 56-64.

2004
 
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Schiaffino, Silvia and Amandi, Analia (2004): User-interface agent interaction: personalization issues. In International Journal of Human-Computer Studies, 60 (1) pp. 129-148.

Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. Most interface agents achieve personalization by learning a user's preferences in a given application domain and assisting him according to them. In this work we adopt a different approach to personalization: how to personalize the interaction between interface agents and users in a mixed-initiative interaction context. We have empirically studied a set of interaction issues that agents have to take into account to achieve this goal and we present our results in this article. Some of these personalization issues are: discovering the type of assistant a user wants, learning when (and if) to interrupt the user, discovering how the user wants to be assisted in different contexts. As a result of our experiments, we have defined the components of a user interaction profile that models a user's interaction and assistance preferences. This profile will enable interface agents to enhance and personalize their interaction with users by discovering how to provide each user assistance of the right sort at the right time.

© All rights reserved Schiaffino and Amandi and/or Academic Press

 
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Amandi, Analia and Armentano, Marcelo (2004): Connecting web applications with interface agents. In Int. J. Web Eng. Technol., 1 (4) pp. 454-470.

1999
 
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Cordero, D., Roldan, P., Schiafino, S. and Amandi, Analia (1999): Intelligent Agents Generating Personal Newspapers. In: ICEIS 1999 1999. pp. 195-202.

 
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