[Asis-l] [Deadline extension] Workshop on Engineering Computer-Human Interaction in Recommender Systems

[Ludovico Boratto]

*** Deadline Extended: April 8th, 2016 ***

Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS) 
In conjunction with the ACM SIGCHI Symposium on Engineering Interactive Computing Systems 
21 June, 2016 
Brussels, Belgium


Aims and goals 

In our daily activities we interact with different types of devices, i.e. personal computers, smartphones and tablets, in order to access information. The interactions exploit also different means, such as the usage of mobile applications, the visualization and the upload of user-generated content in social networks, the browsing of a website, and so on. 

Recommender Systems produce suggestions to users for items, contents, user profiles, etc. they have not considered but might interest them, by analyzing what they previously liked, bought, watched or listened. Such an explicit feedback is an expression of extreme ratings either positive or negative. In the middle of the range stays a set of different actions in the interface that might be interpreted as feedback, but that needs to be collected implicitly. Even if the literature provides different techniques for collecting implicit feedback, they are tailored for specific types of applications. 

>From the user's point of view Recommender Systems remain a black box that suggests objects or contents, but the users hardly understand why some items are included in the suggestion list. Providing the users with an understandable representation of how the system represents them would have two types of benefits. On the one hand, the user is able to track the origin of each suggested item, connecting it to a property in the user model. This would increase the user's trust towards the system. On the other hand, the user may change incorrect attributes and this would lead to more precise recommendations. For instance, it would be possible for the user to search for the latest album of her sister's favorite band in order to give a present for her birthday. But maybe the user likes a completely different genre. 

In this regard the user interface engineering community has the expertise for generalizing the existing approaches, and to elaborate new patterns and metaphors for supporting users in both inspecting and controlling Recommender Systems and the goal of this workshop is to solicit the collaboration between recommendation and user interface experts. 

This workshop solicits contributions in all topics related to engineering Human-Computer Interaction in Recommender Systems, focused (but not limited) to the following list: 

- Design patterns, metaphors and innovative solutions for the end-user inspection and control of a Recommender System 
- Case studies, applications, prototypes of innovative ways for considering the users' interactions as data for Recommender Systems 
- Position papers on problems and solutions for supporting the Recommender Systems through user interaction and the user while interacting with applications that exploit Recommender Systems 
- Feature selection and data filtering approaches to extract information from the data gathered through Human-Computer Interaction techniques, for recommendation purposes 
- Analysis of implicit data collected from real-world systems, in order to evaluate their effectiveness for recommendation and personalization purposes 


Submissions 

We will consider three different submission types, all in the ACM SIGCHI format: regular (6 pages), short (4 pages) and extended abstracts (2 pages). A link to a short video (e.g. 5 minutes) may be also submitted. 

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 Human-Computer Interaction is engineered for recommendation purposes. 

Demo proposals (extended abstract) should present the details of a prototype or complete application that engineers Human-Computer Interaction 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. 

All accepted papers will be made available on the workshop website together with the material generated during the meeting. The EnCHIReS 2016 Workshop proceedings will also be available in the CEUR series, and indexed on DBLP and Scopus. Authors of selected papers will be invited to submit an extended version in a journal special issue. 

Workshop participants are encouraged to present a poster about their contributions or workshop results at the main conference, EICS 2016. 


Format 

All submissions have to be prepared according to the CHI Archive Format and submitted in PDF format through the workshop management system at EasyChair (https://easychair.org/conferences/?conf=enchires2016). 


Important Dates 

- Paper Submission: April 8, 2016 
- Author Notification: April 15, 2016 
- Early registration deadline: May 1, 2016 


Website

http://sites.unica.it/enchires/


Contact 

For general enquires regarding the workshop, send an email to enchires at gmail.com 


Workshop Chairs 

Ludovico Boratto (Università di Cagliari, Italy) 
Lucio Davide Spano (Università di Cagliari, Italy) 
Salvatore Carta (Università di Cagliari, Italy) 
Gianni Fenu (Università di Cagliari, Italy)