Preprocessing and Mining Web Log Data for Web Personalization
M. Baglioni, U. Ferrara, A. Romei, S. Ruggieri, und F. Turini.
AIIA 2003: Advances in Artificial Intelligence,* Volume 2829 von Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2003)

We describe the web usage mining activities of an on-going project, called ClickWorld, that aims at extracting models of the navigational behaviour of a web site users. The models are inferred from the access logs of a web server by means of data and web mining techniques. The extracted knowledge is deployed to the purpose of offering a personalized and proactive view of the web services to users. We first describe the preprocessing steps on access logs necessary to clean, select and prepare data for knowledge extraction. Then we show two sets of experiments: the first one tries to predict the sex of a user based on the visited web pages, and the second one tries to predict whether a user might be interested in visiting a section of the site.

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http://dx.doi.org/10.1007/978-3-540-39853-0_20

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@incollection{baglioni2003preprocessing,
  abstract = {We describe the web usage mining activities of an on-going project, called ClickWorld, that aims at extracting models of the navigational behaviour of a web site users. The models are inferred from the access logs of a web server by means of data and web mining techniques. The extracted knowledge is deployed to the purpose of offering a personalized and proactive view of the web services to users. We first describe the preprocessing steps on access logs necessary to clean, select and prepare data for knowledge extraction. Then we show two sets of experiments: the first one tries to predict the sex of a user based on the visited web pages, and the second one tries to predict whether a user might be interested in visiting a section of the site.},
  added-at = {2013-03-30T15:52:31.000+0100},
  author = {Baglioni, M. and Ferrara, U. and Romei, A. and Ruggieri, S. and Turini, F.},
  biburl = {https://puma.uni-kassel.de/bibtex/21607f6c312b64832bab33fa843442d5e/stephandoerfel},
  booktitle = {AI*IA 2003: Advances in Artificial Intelligence},
  description = {Preprocessing and Mining Web Log Data for Web Personalization - Springer},
  doi = {10.1007/978-3-540-39853-0_20},
  editor = {Cappelli, Amedeo and Turini, Franco},
  interhash = {8dc29cedada5b8e9b3571ae77b983e2f},
  intrahash = {1607f6c312b64832bab33fa843442d5e},
  isbn = {978-3-540-20119-9},
  keywords = {classification gender interest mining user weblog},
  pages = {237-249},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  timestamp = {2013-03-30T15:52:31.000+0100},
  title = {Preprocessing and Mining Web Log Data for Web Personalization},
  url = {http://dx.doi.org/10.1007/978-3-540-39853-0_20},
  volume = 2829,
  year = 2003
}

%0 Book Section
%1 baglioni2003preprocessing
%A Baglioni, M.
%A Ferrara, U.
%A Romei, A.
%A Ruggieri, S.
%A Turini, F.
%B AI*IA 2003: Advances in Artificial Intelligence
%D 2003
%E Cappelli, Amedeo
%E Turini, Franco
%I Springer Berlin Heidelberg
%K classification gender interest mining user weblog
%P 237-249
%R 10.1007/978-3-540-39853-0_20
%T Preprocessing and Mining Web Log Data for Web Personalization
%U http://dx.doi.org/10.1007/978-3-540-39853-0_20
%V 2829
%X We describe the web usage mining activities of an on-going project, called ClickWorld, that aims at extracting models of the navigational behaviour of a web site users. The models are inferred from the access logs of a web server by means of data and web mining techniques. The extracted knowledge is deployed to the purpose of offering a personalized and proactive view of the web services to users. We first describe the preprocessing steps on access logs necessary to clean, select and prepare data for knowledge extraction. Then we show two sets of experiments: the first one tries to predict the sex of a user based on the visited web pages, and the second one tries to predict whether a user might be interested in visiting a section of the site.
%@ 978-3-540-20119-9

PUMA

Preprocessing and Mining Web Log Data for Web Personalization
M. Baglioni, U. Ferrara, A. Romei, S. Ruggieri, und F. Turini.
AIIA 2003: Advances in Artificial Intelligence,* Volume 2829 von Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2003)

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PUMA

Preprocessing and Mining Web Log Data for Web PersonalizationM. Baglioni, U. Ferrara, A. Romei, S. Ruggieri, und F. Turini. AI*IA 2003: Advances in Artificial Intelligence, Volume 2829 von Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2003)

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Preprocessing and Mining Web Log Data for Web Personalization
M. Baglioni, U. Ferrara, A. Romei, S. Ruggieri, und F. Turini.
AIIA 2003: Advances in Artificial Intelligence,* Volume 2829 von Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2003)