WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers /

WorkshopTheme The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth of electronic commerce. In addition, customer interactions, including personalized content, e-mail c- paigns, and online feedback provide new channels of...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Kohavi, Ron (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Masand, Brij M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Spiliopoulou, Myra (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Srivastava, Jaideep (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
Έκδοση:1st ed. 2002.
Σειρά:Lecture Notes in Artificial Intelligence ; 2356
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Detail and Context in Web Usage Mining: Coarsening and Visualizing Sequences
  • A Customer Purchase Incidence Model Applied to Recommender Services
  • A Cube Model and Cluster Analysis for Web Access Sessions
  • Exploiting Web Log Mining for Web Cache Enhancement
  • LOGML: Log Markup Language for Web Usage Mining
  • A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking
  • Mining Indirect Associations in Web Data.