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Special Session
Special Session on
Recommender Systems
 - SSRS 2012

4 - 7 October, 2012 - Barcelona, Portugal

Within the International Conference on Knowledge Discovery and Information Retrieval - KDIR 2012



Sophia Ananiadou
University of Manchester
United Kingdom

Brief Bio
Sophia Ananiadou received her PhD in Natural Language Processing (NLP) from the University of Manchester. Currently, she is Professor of Computer Science in the School of Computer Science, University of Manchester and director of the National Centre for Text Mining (, hosted at the School of Computer Science and Manchester Institute of Biotechnology. Her research interests include using advanced NLP techniques for biomedical text mining, such as event extraction, developing large-scale resources (terminological resources and annotated data), text mining services and interoperable text mining platforms. Her current projects include UKPubMedCentral, text mining for the reconstruction of pathways, and extraction of semantic metadata for the automated measurement of open source software. She was the recipient three times (2006-2008) of the IBM UIMA innovation award for her work in interoperable platforms for text mining and was also awarded the Daiwa Adrian prize (2004). She has authored over 200 publications.


Recommender Systems are software tools, platforms, engines or techniques providing users with suggestions for items that they may find interesting or useful. Recommender systems may be seen as a kind of information filtering systems that predict the preference that a user would give to an item. The prediction may be based either on collaborative filtering or content-based filtering, depending on using user's past behavior or a series of item features, i.e. discrete characteristics of items. Hybrid Recommender Systems combine both. There are more and more applications of recommender systems in e-commerce.
This special session seeks to attract both academic researchers and practitioners who are concerned with the study and application of any type of recommender systems. Papers addressing ideas and/or research projects describing new algorithms, new methods or new applications are particularly welcome.



Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines and Templates.
Papers should be submitted electronically via the web-based submission system at:


All accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on CD-ROM support - and submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP and EI (Elsevier Index).
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library (
SCITEPRESS is member of CrossRef (
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library


KDIR Special Sessions - SSRS 2012