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serecsys 2016 : ICDM 2016 Workshop on Semantics-Enabled Recommender Systems (SERecSys)


When Dec 12, 2016 - Dec 12, 2016
Where Barcelona, Spain
Submission Deadline Aug 17, 2016
Notification Due Sep 13, 2016
Final Version Due Sep 20, 2016
Categories    recommender systems   data mining   semantics

Call For Papers

Call for papers

A recommender system is designed to suggest items that are expected to interest a user. In order to filter the items and produce the recommendation, Data Mining techniques are largely employed. Among the most popular recommendation approaches in the literature and in real-world applications (e.g., e-commerce websites) are the so-called content-based recommender systems. Content-based recommender systems suggest to users items that are similar to those they previously evaluated. The early systems used relatively simple retrieval models, such as the Vector Space Model, with the basic TF-IDF weighting.

Simple (word-based) interest descriptions may fall short both because of semantic ambiguity and because they lack of generality. Recently, content-based recommender systems evolved and started employing external knowledge sources (e.g., ontologies) to improve accuracy and scope of recommendations.

More recent approaches have been based on deep learning. Other approaches, such as, have employed word embeddings in the recommendation process. Among the best known and high-performance implementations following these lines of research we mention Google's word2vec.

Given the rapid advances of Semantic Technologies, there is still a large number of options for recommender systems to take advantage of semantics.

Our workshop will solicit contributions in all topics related to employing Semantic Technologies in Recommender Systems, focused (but not limited) to the following list:

- Novel approaches to user profiling in recommender systems that model behavior with semantic technologies;
- Content-based recommendation algorithms that employ novel uses of semantic technologies;
- Recommendation explanation using semantic technologies;
- Generation of novel, diverse, and serendipitous recommendations using semantic technologies;
- Hybrid recommender systems that combine semantic technologies with other recommendation techniques (e.g, collaborative);
- Group-based approaches that use semantic technologies to describe the group preferences or to generate recommendations.

Accepted papers will be included in the IEEE ICDM 2016 Workshops Proceedings volume published by IEEE Computer Society Press, and will also be included in the IEEE Xplore Digital Library. The workshop proceedings will be in a CD separated from the CD of the main conference. The CD is produced by IEEE Conference Publishing Services (CPS).

Types of contributions

We will consider three different submission types, all in the IEEE 2-column format: regular (8 pages), short (4 pages) and extended abstracts (2 pages).

Research and position papers (regular or short) should be clearly placed with respect to the state of the art and state the contribution of the proposal in the domain of application, even if presenting preliminary results. In particular, research papers should describe the methodology in detail, experiments should be repeatable, and a comparison with the existing approaches in the literature should be made where possible. Position papers should introduce novel point of views in the workshop topics or summarize the experience of a researcher or a group in the field.

Practice and experience reports (short) should present in detail the real-world scenarios in which Semantic Technologies are employed for recommendation purposes.

Demo proposals (extended abstract) should present the details of a prototype or complete application that employs Semantic Technologies in Recommender Systems. The systems will be demonstrated to the workshop attendees.

Submission Guidelines

All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2016 submission guidelines available at

Papers should be submitted in PDF format, electronically, using the CyberChair submission system, available at:

Important Dates

- Paper Submission Due: August 12, 2016
- Acceptance Notification: September 13, 2016



For general enquires regarding the workshop, send an email to

Workshop Chairs

Ludovico Boratto (EURECAT, Spain)
Salvatore Carta (University of Cagliari, Italy)
Giovanni Stilo (Sapienza University of Rome, Italy)

Related Resources

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ECML-PKDD 2017   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery
RecSys 2017   RecSys 2017 : 11th ACM Conference on Recommender Systems
AdCHIReS 2017   Special Issue on Advances in Computer-Human Interaction for Recommender Systems
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
RecSys@FLAIRS 2017   Recommender Systems Special Track at the International FLAIRS Conference
ACML 2017   The 9th Asian Conference on Machine Learning
Smart-City-IoT-Security 2017   Special Issue on Security of IoT-enabled Infrastructures in Smart Cities
MLRec 2017   MLRec 2017 : 3rd International Workshop on Machine Learning Methods for Recommender Systems
DMCIT 2017   ACM-2017 International Conference on Data Mining, Communications and Information Technology(DMCIT 2017)--EI