Machine learning paradigms : applications in recommender systems /: applications in recommender systems. (2015)
- Record Type:
- Book
- Title:
- Machine learning paradigms : applications in recommender systems /: applications in recommender systems. (2015)
- Main Title:
- Machine learning paradigms : applications in recommender systems
- Further Information:
- Note: Aristomenis S. Lampropoulos, George A. Tsihrintzis.
- Authors:
- Lampropoulos, Aristomenis S
Tsihrintzis, George A - Contents:
- Introduction -- Review of Previous Work Related to Recommender Systems -- The Learning Problem.-Content Description of Multimedia Data -- Similarity Measures for Recommendations based on Objective Feature Subset Selection -- Cascade Recommendation Methods -- Evaluation of Cascade Recommendation Methods -- Conclusions and Future Work.
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2015
- Copyright Date:
- 2015
- Extent:
- 1 online resource, illustrations
- Subjects:
- 005.56
Engineering
Recommender systems (Information filtering)
Machine learning
COMPUTERS -- General
Machine learning
Recommender systems (Information filtering)
Computers -- Intelligence (AI) & Semantics
Computers -- Computer Vision & Pattern Recognition
Artificial intelligence
Computer vision
Artificial intelligence
Computer vision
Electronic books - Languages:
- English
- ISBNs:
- 9783319191355
3319191357
3319191349
9783319191348 - Related ISBNs:
- 9783319191348
- Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF title page (Ebsco, viewed June 17, 2015). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.354628
- Ingest File:
- 01_314.xml