To disseminate advanced knowledge on hot topics in computational intelligence seminars will be organized and distributed through the web free of charge to our members. Past webinars can also be accessed by members free of charge.
Webinar Speaker: Prof. Joao Paulo Carvalho
Webinar Chair: Dr Keeley Crockett
Title: Recommender Systems: Using Fuzzy Fingerprints for "Proper" Recommendations
Date & Time: 26th November at 16:00 (GMT) Find your local time
Registration URL: https://attendee.gotowebinar.com/register/4709075663532294668
Webinar ID: xxx-xxx-xxx
Most Recommender Systems rely exclusively on ratings and are known as Memory-based Collaborative Filtering systems. This is the currently dominant approach outside of academia due to the low implementation effort and service maintenance, when compared with more complex Model-based approaches. Traditional Memory-based systems have as their main goal to predict ratings, using similarity metrics to determine similarities between the users’ (or items) rating patterns. In this talk, we propose item and user-based Fuzzy Collaborative Filtering approaches that do not necessarily rely on rating prediction, instead leveraging on Fuzzy Fingerprints to create a novel similarity based recommendation approach. Fuzzy Fingerprints provide a concise and compact representation of users allowing the reduction of the dimensionality usually associated with user-based collaborative filtering.
Prof. Joao Paulo Carvalho has a PhD (2002), a MSc (1996) and an Electrical and Computer Engineer (1992) degree from Instituto Superior Técnico, University of Lisbon, Portugal, where he is currently a Tenured Associate Professor at the Department of Electrical Engineering and Computers. He has lectured courses on Computational Intelligence, Distributed Systems, Entrepreneurship and Technology Transfer, Computer Architectures and Digital Circuits since 1999. He is in the Board of Directors of INESC-ID, where he is a senior researcher and has coordinated 5 funded research projects and participated in more than a dozen national and European funded projects.
His current main research interest involves developing and applying new Computational Intelligence techniques to natural language processing, text mining, social network analysis, social sciences and earth sciences. He has authored over 130 papers in international scientific Journals, books and peer-reviewed conferences. He is Area Editor of Fuzzy Sets and Systems and was Associate Editor of 2 other international Journals. He will be the General Chair of IPMU2020, was program co-chair and organizer of IFSA-EUSFLAT2009, Web chair of the 2010 IEEE World Congress on Computational Computation, FUZZ-IEEE2015 and FUZZ-IEEE2017 Publicity-chair, IPMU2016 program-chair, IEEE-WCCI2017 PR and Publicity-chair, and is PC member of more than 30 international conferences.
IEEE Computational Intelligence Society are pleased to announce two exciting competitions in 2019
- Competition 1:
Three Minute Thesis (3MT®) - is a competition that challenges doctoral students to describe their research to a non-specialist audience in just three minutes. For this competition, you will be allowed to only use a maximum of 4 slides in your webinar and no other resources or props. Competition is open to students only.
- Competition 2
Two minute Elevator Pitch - It in this competition you need to summarise your Computational Intelligence based research, by telling people in simple English, what you do, what is your solution, and why does it matter.Competition is open to all.
Prizes for each competition
- 1st prize - $300 USD
- 2nd prize - $200 USD
- 3rd prize - $100 USD
- Opening Date: 21st October 2019
- Closing Date: 29th November 2019
- Announcement of Winners: December 2019
Competition Submission via
You will be required to submit a Webinar Title, Abstract, a URL to webinar (maximum 3 minutes). The webinar can be submitted as an URL to *any* repository e.g. (YouTube, Youku, BiliBili, Dropbox, Github, Google Drive, etc...).
The webinar must be narrated in English.
How your submission will be judged ?
Submissions will be judged by a panel of CI Experts based on the novelty of the computational intelligence approach, soundness, relevance to emerging topics in CI, presentation and clarity. The Popularity of your webinar (number of "likes" vs "dislikes" and comments in YouTube) will be taken into consideration.
How do I submit?
- First name:
- Last name:
- Competition Entered: 1) Three Minute Thesis OR 2) Two minute Elevator Pitch
- Title of Webinar:
- URL of Webinar:
The IEEE Computational intelligence Society has the right to declare any prize void
Featured Archived Webinar
Challenging the stigma surrounding the role of women in technology, a journey from combinatorial optimization to IBM
From the IEEE Computational Intelligence Society (CIS), this webinar session presented by Dr Amy Khalfay will cover the role of females within technology and the wider STEM sector.
Many people feel that you must have studied a certain degree, know a programming language, or prefer to work alone to be able to have a career in technology. This is not the case, these careers are open to everyone, from any background. During this session we will be exploring some of the misconceptions about careers within STEM, discovering the many types of roles and doing some myth busting. We will also discuss my personal journey to becoming a graduate technology consultant for IBM, my background of research and my commitment to ensuring more females enter STEM careers. My PhD, titled "Optimization heuristics for solving technician and task scheduling problems", focused on solving NP-hard combinatorial optimization problems that arise in the real world and was sponsored by industry. The project enabled me to enhance my soft skills, write academically, learn to code and develop a deeper understanding of real-world business problems and innovative ways to solve them. Biography: Dr Amy Khalfay is currently a graduate technology consultant for IBM, joining in October 2017. Prior to this Amy completed a BSc in Mathematics (2014) and a PhD in Operational Research (2017). Amy is also a committee member of IEEE Women in Engineering. Amy's research area is combinatorial optimisation solving NP-hard scheduling problems. Areas of skill include Java, Statistical Analysis, Mathematical Modelling and Algorithm Design and Development.
Additional archived Webinars can be accessed here.
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