[bull-ia] TLDKS Special issue on « Context-aware data access over social media

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————————— Call for Papers

Transactions on Large-Scale Data- and Knowledge-Centered Systems (TLDKS)
Special Issue on « Context-aware data access over social media streams »


Social media streams delivered by an increasing number of social
platforms (e. g. Twitter, Facebook) provide an immense framework for
intelligence gathering supporting a wide range of highly useful services
such as crisis management, health-care monitoring and market research.
Effective and efficient access to social data streams is an essential
step for many such services. However, traditional access methods are no
longer able to cope with the complexity of social streaming data.
Indeed, unlike traditional web content, social media streams pose a
number of issues mainly including large data volumes, high performance
requirement, brevity, noise, multilingual form, temporality and
dynamicity. This creates an opportunity, particularly for information
retrieval and database communities, to revisit their vision about data
access. One research direction we focus on in this special issue is the
leveraging of contextual data to better understanding and processing
streaming data. This last decade, context features such as userís search
history, preferences, location, and devices have become prevalent in
various domains of information access. More particularly, social media
streams give rise to new challenges represented by the generation of
dynamic contextual features such as social interactions, timely updates,
userís evolving topics and opinions, userís characteristics (e. g.
influence, trust), the diversity of their forms (meta data, text, image)
as well as their semantic-related interdependence. Dealing with those
challenges will require the development of novel models, techniques, and
tools for ensuring effective and efficient information access systems.
The objective of this special issue is to present recent research works
concerning context-based data and information access over social media
streams. Original papers preferably but not limited to the following
topics are welcome:

Topics of interest include (but are not limited to):

– Query rewriting, reranking, building context-driven views to
support access to data streams
– Using knowledge bases and open data for enhancing data streams
– Temporal, continous and location-based querying
– Modeling evolving profiles from social data streams: geo-locating
users, inferring personal metadata (eg. personality, gender, interests,
– Building temporal and dynamic summaries of data streams
– Cost models and optimization for efficient access to data streams
– Performance evaluation and benchmarking of streaming data access tasks
– Applications (crisis management, health care monitoring,
smart-cities, political analysis)

Guidelines for preparing and submitting the manuscript will be available
on the
TLKDS website: http://tldks.faw.at/submission/
Manuscripts should be submitted by one of the authors of the manuscript
the online Manuscript Tracking System:

Franck Morvan, University of Toulouse, IRIT, UPS
Lynda Tamine, University of Toulouse, IRIT, UPS


* Papers Due: December 20, 2017
* Author notification: Mars 31, 2018
* Camera Ready: Juillet 27, 2018
* Publication Date: November 2018

Prof. Lynda Tamine Lechani
Université Paul Sabatier (UPS)
Institut de Recherche en Informatique de Toulouse (IRIT)
118 Route de Narbonne, 31062 Toulouse Cedex 9
Tel : (+33) (0)5 61 55 64 78 e-mail : Lynda.Lechani@irit.fr

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