Sold Out

Recommender System – Stage 1 (Introduction)

Event Information

Share this event

Date and Time

Location

Location

University of Technology Sydney

235 Jones St

Ultimo, NSW 2007

Australia

View Map

Friends Who Are Going
Event description

Description

The quantity of online information has been growing relentlessly and has exceeded user’s processing capabilities, which prevents users from discovering information and aggravates making informed decisions. The information overloading highlights the need for personalised applications that simplify information discovery by taking into account the preferences and needs of their users. These are exploited in Web-based and mobile applications for various purposes, such as finding relevant news items, filtering out junk emails, recommending products to purchase, or adaptively visualising content for users.

One type of personalised application that is popular in the research community and in commercial applications is recommender systems. These provide to users personalised recommendations for services and products they may be interested to examine or purchase. The generation of recommendations typically exploits information collected during the past interactions of users with the system (and other users), and the available domain information. Two fundamental families of recommendation algorithms are deployed: social methods that leverage the “wisdom of the crowd” and knowledge-based methods that exploit the available domain and expert-engineered information.

This course will provide an encompassing overview of the fundamental methods used in this exciting area of research and practice. The participants will gain a thorough understanding of the algorithms and techniques exploited by personalised recommender systems. The course will also include a number of examples and practical lab exercises, which will give the participants the flavour of challenges and constraints posed by the deployment of recommendation technologies.

Who will benefit?

All those involved in BIG DATA for their organisation:

  • Industry practitioners and data scientists, willing to integrate personalised and recommendation technologies into the products and services

  • Academics and researchers, willing to understand how their work can be enhanced by the application of recommendation technologies

  • Graduate students and early-career researchers in the broad areas of data analytics, Web mining, and social media.

Course outcomes:


Upon completion of this course, students will be able to:

  • Understand several fundamental techniques used by recommender systems.

  • Learn how to evaluate the performance of recommender system.

  • Practically implement basic user modelling and recommendation components.

About the presenters:

Dr. Shlomo Berkovsky - is a Principal Researcher and Team Leader at Data61, CSIRO. He studies online behaviour of users and their interaction with information, technologies, and other users. As such, his work involves aspects of data science, human-computer interaction, and behavioural sciences. His specific research interests include user modelling, Web personalisation, recommender systems, and persuasive technologies.

Dr Max (Qinxue) Meng - is a Data Scientist with the CBA. Work focus is supervised and unsupervised models to do customer segmentation, customer profiling and customer behaviour analysis.

Contact Information:

For specific queries regarding course content, please contact Colin Wise, Advanced Analytics Institute Tel: +61 (02) 9514 9267 or email colin.wise@uts.edu.au with questions relating to this course.

For all other enquiries regarding enrolment or payment, please contact UTS Short Courses on Tel: +61 (02) 9514 2913 or email short.courses@uts.edu.au

Share with friends

Date and Time

Location

University of Technology Sydney

235 Jones St

Ultimo, NSW 2007

Australia

View Map

Save This Event

Event Saved