**** Apologies for cross postings ****

BLINKS Workshop @UMAP 2016 – CALL FOR PAPERS
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1st Workshop on Big, LINKed and Social data for User Modeling and 
Personalized Intelligent Systems (BLINKS)

co-located with UMAP 2016 (http://umap2016.com) - Halifax (Canada) - 
13-17 July 2016

Twitter: http://www.twitter.com/blinksworkshop
Web: http://www.di.uniba.it/~swap/blinks
eMail: [log in to unmask]

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ABSTRACT
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Since the creation of the World Wide Web, data has been growing at a 
frantic pace. This steep and continuous growth had another push with the 
advent of the Social Web, where almost any user can create and share 
content of different types on the Web. According to a recent claim by 
IBM, 90% of the data available today have been created in the last two 
years. This uncontrolled and exponential growth of the online 
information gives new life to the research in the area of user modelling 
and personalization, since information about users’ preferences, 
sentiment and opinions can now be obtained by mining data gathered from 
many heterogeneous sources.

As an example, many recent work rely on the analysis of the content 
posted by people on social networks and micro-blogs to unveil latent 
information about their interests, automatically extract people 
personality traits, build preference models on the ground of textual 
reviews, and so on. At the same time, the recent phenomenon of (Linked) 
Open Data fueled this research line by making available a huge amount of 
machine-readable textual data.

All these trends has further paved the way to the design of intelligent 
and personalized systems able to separate signal from noise and hence 
extract some real value from this plethora of textual content produced 
on the Web: examples of such services are online brand monitoring 
platforms, social recommender systems and smart cities-related 
applications, as incident detection systems or personalized city tour 
planners.

However, a complete exploitation of such textual streams requires a 
comprehension of the information conveyed by people. In turn, this 
requires a deep understanding of the language, which is not trivial.

The major goal of this workshop is to stimulate the attention of the 
scientific community on the aforementioned topics.

The workshop aims to provide a forum for discussing open problems, 
challenges and innovative research approaches in the area, in order to 
investigate whether the adoption of techniques for semantic content 
representation can be effective to build a new generation of 
personalized and intelligent systems based on the analysis of Social, 
Big and Linked Open Data.


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TOPICS
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Topics of interests include but are not limited to:

Big, Linked, Social Data Mining
o Techniques for social user data collection, aggregation and analysis
o Social Sensing (aggregating user-based data to obtain people-based 
findings)
o Opinion Mining and Sentiment Analysis of social content;
o Network Analysis and Community Detection.
o Privacy, Trust , Reputation and ethical issues;
o Scalability issues and technologies for massive social data extraction;

Techniques for the analysis of Big, Linked, Social Data
o Natural Language Processing pipelines;
o Semantics Analysis for enhanced content representation;
o Semantics Representation based on Open Knowledge Sources (Wikipedia, 
DBpedia, Freebase, etc.);
o Semantics Representation based on Entity Linking algorithms (TagMe, 
Babelfy, DBpedia Spotlight,
o Multilingual Content representation;
o Geometrical Semantics Models (e.g. Distributional Models);
o New Trends in Content Representation (e.g. Deep Learning approaches).

User Modeling
o User Modeling based on Social and Linked Open Data;
o User Modeling based on Semantic Content Analysis;
o User Modeling based on Big Data Analytics;
o User Modeling based on Emotions and Personality Traits;
o Tracking implicit feedbacks (e.g. social activities) to infer user 
interests;
o Holistic User Modeling, interoperable and decentralized profiles.

Applications
o Recommender Systems based on Big, Linked, Social Data;
o Recommender Systems based on Emotions and Personality;
o Adaptation and Personalization in e-Government domain;
o Online Monitoring based on Social Data (Social CRM, Brand Analysis, etc.)
o Location-based and Context-aware Adaptive Applications;
o Intelligent and Personalized Smart Cities-related Applications (e.g. 
Event Detection, Incident etc.);

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SUBMISSIONS
===============
We encourage the submission of original contributions, investigating the 
impact of content analysis techniques on adaptive and personalized services:

(A) Full research papers (max 5 pages - ACM format);
(B) Short Research papers and Demos (max 2 pages - ACM format);

Submission site: https://easychair.org/conferences/?conf=blinks2016

All submitted papers will be evaluated by at least two members of the 
program committee, based on originality, significance, technical 
soundness, and clarity of expression. Papers should be formatted 
according to the ***ACM formatting guidelines***.

Submissions must be made through the EasyChair conference system prior 
the specified deadline (all deadlines refer to GMT). At least one of the 
authors should register and take part at the conference to make the 
presentation.

The final proceedings will be published on CEUR-WS.org in the joint 
Poster and Demo proceedings of UMAP 2016. We will be looking at the 
possibility of editing a journal special issue from the workshop.

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IMPORTANT DATES
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* Full paper submission: May 7, 2016 (GMT)
* Reviews Due: May 28, 2016 (GMT)
* Paper notification: June 1, 2016
* Camera-ready paper: June 7, 2016

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ORGANIZATION
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Geert-Jan Houben - Delft University of Technology, The Netherlands
Pasquale Lops - University of Bari, Italy
Cataldo Musto - University of Bari, Italy
Denis Parra - Catholic University of Chile, Chile
Giovanni Semeraro - University of Bari, Italy

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PROGRAM COMMITEE
=====================
Liliana Ardissono, Università di Torino
Martin Atzmueller, University of Kassel
Robin Burke, DePaul University
Ivan Cantador, Universidad Autonoma de Madrid
Paolo Cremonesi, Politecnico di Milano
Peter Dolog, Aalborg University
Fabio Gasparetti, Roma Tre University
Cristina Gena, Università di Torino
Alessandro Giuliani, Università di Cagliari
Claudia Hauff, Delft University of Technology
Tsvika Kuflik, University of Haifa
Fedelucio Narducci, Università di Bari
Simone Paolo Ponzetto, Universitat Mannheim
Alan Said, Recorded Future
Shaghayegh Sahebi, University of Pittsburgh, United States
Marko Tkalcic, Free University of Bolzano
Christoph Trattner, KMI-TU Graz
Saul Vargas, Mendeley
Markus Zanker, University Klagenfurt, Austria
Yong Zheng, DePaul University

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