- AutorIn
- Nick Golovin
- Erhard Rahm
- Titel
- Automatic Optimization of Web Recommendations Using Feedback and Ontology Graphs
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-327854
- Quellenangabe
- Web engineering : 5th international conference#proceedings
Erscheinungsort: Berlin [u.a.]
Verlag: Springer
Erscheinungsjahr: 2005
Titel Schriftenreihe: Lecture notes in computer science
Bandnummer Schriftenreihe: 3579
Seiten: 375-386
ISBN: 978-3-540-27996-9 - Erstveröffentlichung
- 2005
- Abstract (EN)
- Web recommendation systems have become a popular means to im-prove the usability of web sites. This paper describes the architecture of a rule-based recommendation system and presents its evaluation on two real-life ap-plications. The architecture combines recommendations from different algo-rithms in a recommendation database and applies feedback-based machine learning to optimize the selection of the presented recommendations. The rec-ommendations database also stores ontology graphs, which are used to semanti-cally enrich the recommendations. We describe the general architecture of the system and the test setting, illustrate the application of several optimization ap-proaches and present comparative results.
- Freie Schlagwörter (EN)
- World wide web, application system
- Klassifikation (DDC)
- 004
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-327854
- Veröffentlichungsdatum Qucosa
- 24.01.2019
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch