User Modelling for News Web Sites with Word Sense Based Techniques
B. Magnini, and C. Strapparava. User Modeling and User-Adapted Interaction, 14 (2-3):
239--257(June 2004)
Abstract
SiteIF is a personal agent for a bilingual news web site that learns user's interests from the requested pages. In this paper we propose to use a word sense based document representation as a starting point to build a model of the user's interests. Documents passed over are processed and relevant senses (disambiguated over WordNet) are extracted and then combined to form a semantic network. A filtering procedure dynamically predicts new documents on the basis of the semantic network.
There are two main advantages of a sense-based approach: first, the model predictions, being based on senses rather than words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We report the results of a comparative experiment that has been carried out to give a quantitative estimation of these improvements.
%0 Journal Article
%1 citeulike:576263
%A Magnini, Bernardo
%A Strapparava, Carlo
%D 2004
%J User Modeling and User-Adapted Interaction
%K news user-profile
%N 2-3
%P 239--257
%T User Modelling for News Web Sites with Word Sense Based Techniques
%V 14
%X SiteIF is a personal agent for a bilingual news web site that learns user's interests from the requested pages. In this paper we propose to use a word sense based document representation as a starting point to build a model of the user's interests. Documents passed over are processed and relevant senses (disambiguated over WordNet) are extracted and then combined to form a semantic network. A filtering procedure dynamically predicts new documents on the basis of the semantic network.
There are two main advantages of a sense-based approach: first, the model predictions, being based on senses rather than words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We report the results of a comparative experiment that has been carried out to give a quantitative estimation of these improvements.
@article{citeulike:576263,
abstract = {{SiteIF is a personal agent for a bilingual news web site that learns user's interests from the requested pages. In this paper we propose to use a word sense based document representation as a starting point to build a model of the user's interests. Documents passed over are processed and relevant senses (disambiguated over WordNet) are extracted and then combined to form a semantic network. A filtering procedure dynamically predicts new documents on the basis of the semantic network.
There are two main advantages of a sense-based approach: first, the model predictions, being based on senses rather than words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We report the results of a comparative experiment that has been carried out to give a quantitative estimation of these improvements.}},
added-at = {2018-03-19T12:24:51.000+0100},
author = {Magnini, Bernardo and Strapparava, Carlo},
biburl = {https://www.bibsonomy.org/bibtex/2c1e0e092c775e89fef5e32786c3c2bb0/aho},
citeulike-article-id = {576263},
interhash = {3d1e0227302c64f780a173687ecb5634},
intrahash = {c1e0e092c775e89fef5e32786c3c2bb0},
journal = {User Modeling and User-Adapted Interaction},
keywords = {news user-profile},
month = jun,
number = {2-3},
pages = {239--257},
posted-at = {2006-06-06 20:38:46},
priority = {2},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{User Modelling for News Web Sites with Word Sense Based Techniques}},
volume = 14,
year = 2004
}