Free shipping on all orders over $79* Limited Time Only
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Machine Learning Paradigms : Applications in Recommender Systems - Aristomenis S. Lampropoulos

Machine Learning Paradigms

Applications in Recommender Systems

By: Aristomenis S. Lampropoulos, George A. Tsihrintzis

eText | 13 June 2015

At a Glance

eText

$149.01

or 4 interest-free payments of $37.25 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in "big data" as well as "sparse data" problems.

The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and Recommender Systems, as well as for the general reader in the fields of Applied and Computer Science who wishes to learn more about the emerging discipline of Recommender Systems and their applications. Finally, the book provides an extended list of bibliographic references which covers the relevant literature completely.

on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionEngineering & TechnologyTechnology in GeneralEngineering in GeneralComputing & I.T.Computer ScienceArtificial IntelligenceComputer VisionImage Processing

More in Artificial Intelligence

AI-Powered Search - Trey Grainger

eBOOK

AI-Powered Search

eBook

$52.99

HBR Guide to Generative AI for Managers : HBR Guide - Elisa Farri

eBOOK

HBR Guide to Generative AI for Managers

HBR Guide

eBook

RRP $37.26

$29.99

20%
OFF
AI : The End of Human Race - Alex Wood

eBOOK

AI

The End of Human Race

eBook

$16.99

This product is categorised by