@article{AddaValtchevEtAl07IEEEinternet,
title = {Toward Recommendation Based on Ontology-Powered Web-Usage Mining},
author = {Mehdi Adda and Petko Valtchev and Rokia Missaoui and Chabane Djeraba},
journal = {Internet Computing},
number = {4},
pages = {45-52},
url = {http://dx.doi.org/10.1109/MIC.2007.93},
volume = {11},
year = {2007},
abstract = {Content adaptation on the Web reduces available information to a subset
that matches a user's anticipated needs. Recommender systems rely
on relevance scores for individual content items; in particular,
pattern-based recommendation exploits co-occurrences of items in
user sessions to ground any guesses about relevancy. To enhance the
discovered patterns' quality, the authors propose using metadata
about the content that they assume is stored in a domain ontology.
Their approach comprises a dedicated pattern space built on top of
the ontology, navigation primitives, mining methods, and recommendation
techniques.},
issn = {1089-7801}, timestamp = {2008.02.19}, file = {IEEE Digital Library:2007/AddaValtchevEtAl07IEEEinternet.pdf:PDF}, owner = {flint},
keywords = {adaptive ai data ieee interaction ontology paper pattern recognition search user v0805 web }
}
::