A case-based approach to user modeling

Micarelli, Alessandro; Sciarrone, Filippo; Ambrosini, Leonardo; Cirillo, Vincenzo

doi:10.1007/bfb0056343

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…design [13,14], and some relating examples in engineering applications have been reported [9,[15][16][17]. In this survey paper, the-state-of-art of connectionist model-based CBR system design is discussed.…”

Section: Case-based Reasoning System and Annsmentioning

confidence: 99%

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Case-Based Reasoning System and Artificial Neural Networks: A Review

Chen

Burrell

2001

NCA

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Section: Case-based Reasoning System and Annsmentioning

confidence: 99%

“…The multilayer feedforward neural network was introduced for case indexing and retrieval [9,16,17]. Because of its powerful non-linear mapping ability, the MFNN is particularly well suited for describing complicated feature-case relationships.…”

Section: Case Indexing and Case Retrievalmentioning

confidence: 99%

Case-Based Reasoning System and Artificial Neural Networks: A Review

Chen

Burrell

2001

NCA

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A Case-Based Approach to Image Recognition

Micarelli

Neri

Sansonetti

2000

Lecture Notes in Computer Science

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Anatomy and Empirical Evaluation of an Adaptive Web-Based Information Filtering System

Micarelli

Sciarrone

2004

User Modeling and User-Adapted Interaction

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A case study in adaptive information filtering systems for the Web is presented. The described system comprises two main modules, named HUMOS and WIFS. HUMOS is a user modeling system based on stereotypes. It builds and maintains long term models of individual Internet users, representing their information needs. The user model is structured as a frame containing informative words, enhanced with semantic networks. The proposed machine learning approach for the user modeling process is based on the use of an artificial neural network for stereotype assignments. WIFS is a content-based information filtering module, capable of selecting html/text documents on computer science collected from the Web according to the interests of the user. It has been created for the very purpose of the structure of the user model utilized by HUMOS. Currently, this system acts as an adaptive interface to the Web search engine ALTA VISTA™. An empirical evaluation of the system has been made in experimental settings. The experiments focused on the evaluation, by means of a non-parametric statistics approach, of the added value in terms of system performance given by the user modeling component; it also focused on the evaluation of the usability and user acceptance of the system. The results of the experiments are satisfactory and support the choice of a user model-based approach to information filtering on the Web

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A case-based approach to user modeling

Cited by 6 publications

References 14 publications

Case-Based Reasoning System and Artificial Neural Networks: A Review

Case-Based Reasoning System and Artificial Neural Networks: A Review

A Case-Based Approach to Image Recognition

Anatomy and Empirical Evaluation of an Adaptive Web-Based Information Filtering System

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