Machine Learning

A Novel Approach to Recommendation Algorithm Selection using Meta-Learning

Our paper “A Novel Approach to Recommendation Algorithm Selection using Meta-Learning” was accepted for publication at the 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS): Introduction  The ‘algorithm selection problem’ describes the challenge of finding the most effective algorithm for a given recommendation scenario. Some typical recommendation scenarios are news websites [3], digital libraries [4, 5], movie-streaming platforms [13]. The performance of recommender system algorithms vary in these different scenarios [3, 6, 10, 11, 15] as illustrated in Fig. 1. Performance variation occurs for many reasons, for example, the effectiveness of collaborative filtering algorithms changes depending on the number of ratings available from users [10]. Algorithms also perform differently depending on the demographic characteristics of users [6][11], depending on Read more…

By Andrew Collins, ago
Research

Participate in the “Track Your Daily Routine” Research Study About Your Smartphone Usage and Your Personality

A colleague of mine has initiated a new research project to analyse smartphone users’ usage behaviour and personality. He and his team have released an Android app named TYDR: Track Your Daily Routine. With the data from TYDR, they want to research if they can estimate the personality of a smartphone user by the data that can be collected automatically. This could eventually lead to not needing to fill out questionnaires anymore. There are potential benefits for mobile health apps and recommender systems – apps could know what type of person the user is and adapt to his/her needs. The main features include: Personality evaluation Visualization of your visited locations Photo statistics Music statistics Calls statistics Steps taken statistics App usage statistics Read more…

By Joeran Beel, ago
Recommendations as-a-Service (RaaS)

The Architecture of Mr. DLib’s Scientific Recommender-System API

Our manuscript “The Architecture of Mr. DLib’s Scientific Recommender-System API” got accepted at the “26th Irish Conference on Artificial Intelligence and Cognitive Science” (AICS), and here is the pre-print version (HTML below; PDF on arxiv). The bibliographic BibTeX data is: @InProceedings{Beel2018MDLArch, author = {Beel, Joeran and Collins, Andrew and Aizawa, Akiko}, title = {The Architecture of Mr. DLib’s Scientific Recommender-System API}, booktitle = {Proceedings of the 26th Irish Conference on Artificial Intelligence and Cognitive Science}, year = {2018}, volume = {26}, volumes = {1}, number = {26}, pages = {1–12}, abstract = {Recommender systems in academia are not widely available. This may be in part due to the difficulty and cost of developing and maintaining recommender systems. Many operators of Read more…

By Joeran Beel, ago
Recommender Systems

Report/Photos from the 12th ACM Conference on Recommender Systems in Vancouver

Today, the 12th ACM Conference on Recommender Systems began in Vancouver, Canada. We attend and will present our work on meta-learning reference parsing tools in which we treat reference extraction from scientific articles as a recommendation problem. If you also attend the conference, visit us during the poster session on Thursday. So far, it has been a great conference with many exciting talks. A few of the many great presentations are the following Why I like it: Multi-task Learning for Recommendation and Explanation We describe a novel, multi-task recommendation model, which jointly learns to perform rating prediction and recommendation explanation by combining matrix factorization, for rating prediction, and adversarial sequence to sequence learning for explanation generation. The result is evaluated using real-world Read more…

By Joeran Beel, ago
Jobs & Internships

Living in Tokyo / Working at the NII

This page provides information for students who are interested in working at the National Institute of Informatics (NII) in Tokyo, Japan. This page focuses on students who are already accepted as internship students, or who want to get an idea what work and life in Tokyo will be like. If you are interested in applying for an internship as a student at TCD or ADAPT, talk to your supervisor and apply for the Earrach Sakura Award. If you are from another university, find out if your university has a memorandum of understanding (MoU) with the NII. If your university has a MoU with the NII, find out who the coordinator at your university is, and contact the coordinator. Impressions To Read more…

By Joeran Beel, ago
Conferences

AICS’2018: We Co-Organize the 26th Irish Conference on Artificial Intelligence and Cognitive Science

We are delighted to announce the 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS’2018), which we will co-organize together with Rob Brennan, Ruth Byrne, Jeremy Debattista, and a renowned program committee. AICS 2018 takes place from December 6 to 7, 2018 at Trinity College Dublin, more precisely in the Long Room Hub. Deadline for submissions is 30th September 2018. There will be three tracks for submissions, namely full papers, NECTAR Papers, and student papers. The call for papers invites papers relating particularly to machine learning, machine translation, neural networks, data mining, cognitive modelling, behaviour epistemology, evolutionary computation, recommender systems, collective intelligence, human learning, and several more. AICS 2018 is sponsored by the ADAPT Research Centre, Trinity Long Room Hub, and Trinity College Dublin. AICS dates Read more…

By Joeran Beel, ago
Internal

Our new website is live!

Today, we launched our new website https://www.scss.tcd.ie/joeran.beel/. It provides lots of information about our research, publications, projects, and teaching relating to recommender systems, machine learning and more. The new website also combines the blog posts of our project websites Mr. DLib and Docear.  

By Joeran Beel, ago
Jobs / Career

We Are Hiring: 1 Software/Machine-Learning Engineer & 1 Software Architect / Product Owner for a Recommender-System Business Start-up

UPDATE: We will soon advertise another position for this start-up. Please come back in a few days. The School of Computer Science and Statistics of Trinity College Dublin and the ADAPT Centre received funding to hire 2 employees for 2 years* to spin-out a business start-up in the field of recommender-systems as-a-service and machine learning in Dublin. The two positions are to be filled with one machine-learning engineer and one software architect/product manager, whereas both employees are expected to work together very closely. They will be responsible for developing a recommender-system as-a-service that uses a unique technology, based on the research of Prof Dr Joeran Beel who will be the project lead (read here for a brief outline of the Read more…

By Joeran Beel, ago
Recommender Systems

Seminar by Prof Dietmar Jannach: “Recommender Systems – Beyond Matrix Completion”

We are delighted to announce a seminar by Prof Dr Dietmar Jannach on Recommender Systems at Trinity College Dublin. Dietmar Jannach is a well-known researcher in the field of recommender systems and author of the book “Recommender Systems: An Introduction“. The seminar is open to all staff, students, and visitors in Dublin who are interested in recommender systems. Title: Recommender Systems – Beyond Matrix Completion Abstract: Automated recommendations have become a common part of our daily online user experience. Significant advances were made in recent years in terms of algorithmic approaches to compute recommendations for users. The main task in such an algorithm-focused setting is to predict through machine learning approaches how relevant a certain item will be for an Read more…

By Joeran Beel, ago
Jobs & Internships

We welcome two DAAD interns in recommender systems and machine learning (Dublin & Tokyo)

As part of the DAAD RISE Worldwide program, we were awarded two funded internship positions for two undergraduate students both being from Germany. The two interns will be conducting a research project as part of Mr. DLib in the fields of recommender systems, machine learning and natural language processing. Gordian (University of Munich / LMU) and Martin (Universty of Göttingen) will spend around three months with us over the summer — Gordian at the National Institute of Informatics in Tokyo, and Martin at the ADAPT Centre and School of Computer Science at the Trinity College Dublin.

By Joeran Beel, ago