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SERecSys 2017 : 2nd ICDM Workshop on Semantics-Enabled Recommender Systems


When Nov 18, 2017 - Nov 18, 2017
Where New Orleans (USA)
Submission Deadline Aug 10, 2017
Notification Due Sep 4, 2017
Final Version Due Sep 9, 2017
Categories    recommender systems   data mining   semantics

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 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.

Moreover, semantic technologies will soon find a connection with cognitive computing, cooperating in the definition of the so-called cognitive recommender systems. 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;
- Cognitive recommender systems;
- 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.

- Paper submission: August 7, 2017
- Notification of acceptance: September 4, 2017
- Camera-ready version submission: September 9, 2017
- Workshop date: November 18, 2017

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.

Insights and results papers (short) should provide a presentation of ideas and insights, along with the results that validate these ideas, to have quick and inspiring exchanges among the workshop attendants. The “insights and results” papers will be presented in a novel and dedicated “Voodoo session” (inspired by the location of the workshop), which is aimed at stimulating these exchanges.

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.

The reviewing process will be coordinated by the organizers. Each paper will receive three reviews: two externals to the organizing committee and one internal. The external reviewers will be contacted according to their expertise in the paper topic.

Accepted papers will be included in the IEEE ICDM 2017 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).
Authors of selected papers will be invited to submit an extended version in a journal special issue.

All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2017 submission guidelines available at

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

Dr. Huzefa Rangwala (George Mason University, USA)

Facebook page:
For general enquires regarding the workshop, send an email to

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

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