ACM TIST Special Issue on Search and Mining User-generated Contents

Deadline: 1 December 2010
More info at ACM TIST webpage

Social Media have been able to shift the way information is generated and consumed. At first, information was generated by one person and “consumed” by many people, but nowadays most part of the information available in the Web is generated by users, which has changed the needs in information access and management. Social Networks like Facebook or Twitter manage tens of PB of information, with flows of hundreds of TB per day, and hundreds of billions of relationships.

User generated content provides an excellent scenario to apply the metaphor of mining any kind of information. In a social media context, users create a huge amount of data where we can look for valuable nuggets of knowledge by applying diverse search (information retrieval) and mining techniques (data mining, text mining, web mining, opinion mining). In this kind of data, we can find both structured information (ratings, tags, links) and unstructured information (text, audio, video), and we have to learn how to combine existing techniques in order to take advantage of the existing information heterogeneity while extracting useful knowledge.
The primary goal of this special issue of ACM Transactions on Intelligent Systems and Technology is to foster research in the interplay between Social Media, Data/Opinion Mining and Search, aiming to reflect the actual developments on technologies that exploit user generated contents.

Topics of Interest

We invite researchers and professionals from a broad range of disciplines to submit to this special issue. Papers may encompass any or all of the following types of works: foundational theoretical analyses, modelling, simulation, and empirical studies. Moreover, authors may examine different aspects of search and mining user generated contents in a variety of possible contexts. Topics of interest include, but are not limited to:


A) Mining Social Media

• Social networks analysis/mining
• Tagging/links/graphs analysis and mining
• Community detection and evolution
• Influence, trust and privacy analysis
• Social media monitoring/analysis

B) Opinion Mining and Sentiment Analysis

• Opinion extraction/classification/summarization/visualization
• Temporal sentiment analysis
• Cross-lingual/cross-domain sentiment analysis
• Irony detection in opinion mining
• Wish analysis
• Product review analysis

C) Search in Social Media

• Novel social search algorithms
• Social ranking
• Multi-entity search
• Multifaceted search
• User Modelling and Personalization in Social Media

D) Other Social Intelligent Systems

• Social Recommender systems
• Semantic Social Media
• Market analysis
• Cross-lingual/cross-domain social intelligent systems

Submission Guidelines

Manuscripts submitted to the special issue should contain original material not published in nor submitted to other journals. Each paper will be reviewed by at least 3 expert reviewers. Papers which do not meet publication quality standards, or does not pass the editorial assessment of suitability of this special issue will be rejected before the review process.
Full papers should be sent via TIST's On-Line Submission system http://mc.manuscriptcentral.com/tist (please select “Special Issue: Search and Mining User Generated Contents” as the manuscript type), and should not exceed 20 pages length. Details of the journal and manuscript preparation are available on the website: http://tist.acm.org/

[CFP] SMUC 2010 Workshop @ CIKM 2010

----------------------------------------------------------------------------------
CALL FOR PAPERS

SMUC2010: 2nd International Workshop on Search and Mining User-generated Contents
http://labs.brainsins.com/events/smuc2010
Workshop at CIKM 2010 (http://www.yorku.ca/cikm10/)
October 30, 2010, Toronto, Canada
Submission deadline: 30 June, 2010
-----------------------------------------------------------------------------------

SMUC10 aims to become a forum for researchers from several Information and Knowledge Management areas like data/text mining, information retrieval, semantics, etc. that apply their work into the fields of Social Media and Opinion/Sentiment Analysis where the main goal is to process user generated contents.

User generated content provides an excellent scenario to apply the metaphor of mining any kind of information. In a social media context, users create a huge amount of data where we can look for valuable nuggets of knowledge by applying several search techniques (information retrieval) or mining techniques (data mining, text mining, web mining, opinion mining, etc.). In this kind of data we can find both structured information (ratings, tags, links, etc.) and unstructured information (text, audio, video, etc.), and we must learn to combine existing techniques in order to take advantage of this heterogeneity while extracting useful knowledge.


TOPICS OF INTEREST
================

SMUC10 workshop is an extraordinary place where to present on-going works that exploit Social Media and/or use Opinion Mining technologies. Topics of interest include, but are not limited to:

A) Mining Social Media

Social networks analysis/mining
Tagging analysis/mining
Link and graphs analysis/mining
Community detection and evolution
Influence, trust and privacy analysis
Topic detection and trend discovery
Spamming and phishing detection
Wikipedia/Social Media vandalism
Social media monitoring/analysis

B) Opinion Mining and Sentiment Analysis

Opinion extraction, classification, summarization and visualization
Blogs analysis
Opinion flame
Temporal sentiment analysis
Cross-lingual/cross-domain sentiment analysis
Irony detection in opinion mining
Wish analysis
Product review analysis

C) Search in Social Media

Novel social search algorithms
Social ranking
Multi-entity/Multifaceted search
Multilingual and/or multimedia IR for Social Media
User Modeling and Personalization in Social Media
Architectures, scalability and efficiency

D) Other Social Intelligent Systems

Recommender systems
Semantic Social Media
Plagiarism detection
Market analysis
Cross-lingual/cross-domain social intelligent systems
Business Intelligence Applications (direct marketing, branding, etc.)


DATES
=================

* Submission: 30 June, 2010
* Notification of acceptance: 30 July, 2010
* Camera Ready: 15 August, 2010
* Workshop: 30 October, 2010


SUBMISSIONS
==================

Each contribution should not exceed the length of 8 pages, and must be prepared following ACM camera-ready template: http://www.acm.org/sigs/pubs/proceed/template.html

All papers must be submitted in Adobe Portable Document Format (PDF). Please ensure that any special fonts used are included in the submitted documents. Please use the following link to submit your paper: Easychair Submission System for SMUC 2010 http://www.easychair.org/conferences/?conf=smuc2010.

The workshop proceedings will be published as Eproceedings by the same publisher that publishes the CIKM main conference proceedings, and will be in the same CD that contains the CIKM'10 main conference Eproceedings.

We are actually on conversations with a couple of journals to organize a special issue with extended versions of selected papers. The information about this special issue will be published on the workshop's website.


ORGANIZING COMMITTEE
==================

* Jose C. Cortizo, BrainSins / European University of Madrid, Spain (contact person, josecarlos.cortizo@wipley.com)
* Francisco M. Carrero, BrainSins / European University of Madrid, Spain
* Ivan Cantador, Autonomous University of Madrid, Spain
* Jose A. Troyano, University of Seville, Spain
* Paolo Rosso, Technical University of Valencia, Spain



PROGRAM COMMITTEE
==================

[To be completed]

* Ahmed Abbasi (University of Wisconsin-Milwaukee, USA)
* Nitin Agarwal (University of Arkansas at Little Rock, USA)
* Enrique Amigo (National University of Distance Education, Spain)
* Ching-Man Au Yeung (NTT Communication Science Laboratories, Japan)
* Alexandra Balahur (Sapienza Università di Roma, Italy)
* Alberto Barrón (Technical University of Valencia, Spain)
* Dominik Benz (University of Kassel, Germany)
* Pushpak Bhattacharyya (IIT Bombay, India)
* Erik Cambria (University of Stirling, Scotland)
* Pablo Castells (Autonomous University of Madrid, Spain)
* Meeyoung Cha (Korea Advanced Institute of Science and Technology, Korea)
* Fermin Cruz (University of Seville, Spain)
* Victor Diaz (University of Seville, Spain)
* Viet Ha-Thuc (University of Iowa, USA)
* Akshay Java (MSN Microsoft, USA)
* Ralf Klamma (RWTH Aachen University, Germany)
* Zornitsa Kozareva (Information Sciences Institute at the University of Southern California, USA)
* Hady W. Lauw (Institute for Infocomm Research, Singapore)
* Luis Martin (BrainSins, Spain)
* Patricio Martinez-Barco (University of Alicante, Spain)
* Andres Montoyo (University of Alicante, Spain)
* Claudiu C. Musat (Politechnical University of Bucharest, Romania)
* Manuel Palomar (University of Alicante, Spain)
* Manos Papagelis (University of Toronto, Canada)
* Victor Peinado (National University of Distance Education, Spain)
* Isabella Peters (University of Duesseldorf, Germany)
* Martin Potthast (Bauhaus-Universität Weimar, Germany)
* Antonio Reyes (Technical University of Madrid, Spain)
* Horacio Rodriguez (Technical University of Catalonia, Spain)
* Efstathios Stamatatos (University of Aegean, Greece)
* Benno Stein (Bauhaus-Universität Weimar, Germany)
* Ralf Steinberger (European Commission, Joint Research Centre)
* Markus Strohmaier (Graz University of Technology, Austria)
* Jie Tang (Tsinghua University, China)
* Jordi Turmo (Technical University of Catalonia, Spain)
* Luis Alfonso Ureña (University of Jaen, Spain)

CFP: APRESW Extended to March 15

APRESW 2010 (1st International Workshop on Adaptation, Personalization and REcommendation in the Social-semantic Web), colocated under the ESWC 2010, has extended its deadline to March 15.

RecSys + ECML/PKDD = Barcelona, September

This year's editions of RecSys (ACM Recommender Systems) and ECML/PKDD (European Conference on Machine Learning) will be held in Barcelona. ECML will be from 20th to 24th of September (Monday to Friday), and RecSys will start on Sunday (26th) and will finish 30th of September (thursday).

There is a clear topic relation between RecSys and ECML, in fact most of actual RecSys approaches has been proben in other fields (like data-mining, machine learning, information retrieval, etc.) before. For whom, like me, work around the two fields, is a great opportunity to assist two great conference in a single travel, and discover Barcelona, that is a really great city.

[REMINDER] Special Issue of International Journal of Electronic Commerce on Mining Social Media

The deadline fot the special issue on Mining Social Media on the International Journal of Electronic Commerce is approaching (deadline for abstract is January 15). If you are interested on publishing on this special issue, please, take care about the dates.

CFP: Special Issue of International Journal of Electronic Commerce on Mining Social Media

After the experience of organizing the 1st International Workshop on Social Media (papers now online), we've been organizing a special issue of the IJEC (International Journal of Electronic Commerce) on Mining Social Media. Now we release the CFP hoping to receive high quality papers on Mining Social Media:


OVERVIEW

Recently, Forrester published a report, “The Future of the Social Web” where they sketched a timeline of the development of the Social Web, dividing its evolution in 5 eras. According to that report, the first era of the development of the Social Web started to explode the social relationships among users. Then, in the social functionality era, these social relationships resulted in the social functionality era where several websites started to add social functionalities in order to help users to interact with their peers. We are now in the era of Social Colonization, where technologies like Facebook Connect or Google Friend Connect have standardized social functionalities among websites and a vast majority of websites now include several social functionalities. Soon these federated identities will empower people to enter the era of social context with personalized and social content, and the development of tools for personalize social content will aim the development of the era of social commerce.

The primary goal of the proposed special issue of International Journal of Electronic Commerce is to foster research in the interplay between Social Media, Data Mining and Electronic Commerce, trying to reflect the actual developments on technologies that fit on the Social Context era.


SCOPE

The International Journal of Electronic Commerce is the #1-ranked journal on Electronic Commerce globally. This Special Issue will provide a significant opportunity for authors to publish important novel and original contributions in the area of Data Mining applied to Social Media. The guest editors seek papers and proposals that address various aspects of Mining Social Media, including recommender systems for social media, data mining algorithms designed to explode Social Networks, information management for Social Networks, etc.


RESEARCH QUESTIONS

We invite scholars and professionals from a broad range of disciplines to submit to this Special Issue. Papers may encompass any or all of the following: foundational theoretical analyses, modelling, simulation, and empirical studies. Authors may examine different aspects of mining social media in any of a variety of possible contexts. Special topics of interest include, but are not limited to, the following:

A. Data Mining for Social Networks

• Novel Algorithms
• Association Rules
• Mining semi-structured data
• Classification and Ranking
• Clustering
• Text Mining
• Machine Learning
• Privacy Preserved Data Mining
• Statistical Methods
• Temporal and spatial data mining
• Parallel and Distributed Data Mining
• Interactive and Online Mining
• Data and Knowledge Visualization
• Multimedia mining (audio/video)
• Ensemble Methods
• Web Mining
• Graph Mining
• Link Mining

B. Information Management for Social Networks

• Recommender Systems
• Information Retrieval
• Sentiment Analysis
• Natural Language Processing
• Question Answering
• Semantic Processing
• Graph Analysis and Complex Networks
• Social Network Analysis

C. Possible applications

• Electronic Commerce
• E-Mail Spam Detection
• Blog/Social Networks Spam Detection
• Community Detection
• Users/content recommenders
• Trends discovery
• Blogs/Social Networks Community Dynamics
• User Reviews Ranking
• Blogs/Social Networks Contributions Summarization
• Abuse/Fraud Detection
• User Profile Modelling
• Event Detection and Tracking in Social Media
• Online Advertising


SUBMISSION GUIDELINES

Manuscripts submitted to the special issue should contain original material not published in nor submitted to other journals. Each manuscript has to have a cover page with the author information and another page with title and abstract but the author information omitted. The review process is double-blind and papers which do not meet publication quality standards will be rejected before the review process.

Interested authors are required to submit extended abstracts of no more than two pages for their planned submissions. This will give the editorial team an opportunity to determine if a given submission is appropriate for expedited handling and review.

Full papers should be sent via e-mail to Jose Carlos Cortizo <josecarlos.cortizo@wipley.com> in anonymized PDF Format, not including any author names or affiliations, and should not exceed 40 pages.


IMPORTANT DATES

• Abstracts DeadLine: 15 January 2010
• Abstracts Feedback: 30 January 2010
• Full Paper Submission: 15 April 2010
• Revision Notification: 1 June 2010
• Revised Manuscripts: 1 August 2010
• Final Decision: 1 October 2010
  

1st International Workshop on Mining Social Media Programme

While we are still working on the final proceedings to be published in Bubok, and in the post-workshop special issue on a journal to be announced soon, we have the final version of the programme of the Mining Social Media Workshop. If you are interested on Mining Social Media, this will be a very good place to meet with other researchers and practicioners. Registration is open.

• 9:30 - 11:00; Keynote speaker, William W. Cohen
• 11:00 - 11:30; Coffee Break
• 11:30 - 13:30; 6 paper presentations (20 minutes per paper)
  • "Using prediction Markets and Twitter to predict a Swine Flu Pandemic", Joshua Ritterman, Miles Osborne and Ewan Klein
  • "Comparison of Rule-based to Human Analysis of Chat Logs", April Kontostathis, Lynne Edwards, Jen Bayzick, India McGhee, Amanda Leatherman and Kristina Moore
  • "Detecting Blogs Independently from the Language and Content", Francisco Manuel Rangel and Anselmo Peñas
  • "Improve Web Search Ranking with Social Tagging", Shihn-Yuarn Chen and Yi Zhang
  • "Combining Tag Cloud Learning with SVM Classification to Achieve Intelligent Search for Relevant Blog Articles", Ahmad Ammari and Valentina Zharkova
  • "Folksonomy Analyzer: a FCA-based Tool for Conceptual Knowledge Discovery in Social Tagging Systems", Kyoung-Mo Yang, Suk-Hyung Hwang, Yu-Kyung Kang, Hae-Sool Yang
• 13:30 - 15:30; Lunch Break
• 15:30 - 17:00; 4 paper presentations (20 minutes per paper)
  • "Fundamental operations for organizing resource groups in Grouped folksonomy", Yu-Kyung Kang, Suk-Hyung Hwang and Hae-Sool Yang
  • "A Comparison of Approaches to Determine Topic Similarity of Weblogs for Privacy Protection", Dong Yi Wu and Amanda Stent
  • "Data-Driven Ontologies for Recommender Engines in Social Networks", Ingo Bax and János Moldvay
  • "Expert Stock Picker: The Wisdom of (the Experts in the) Crowds", Shawndra Hill, Noah Ready-Campbell
• 17:00 - 17:30; Coffee Break
• 17:30 - 19:30; Industry Panel with Tuenti, Strands and Optenet

Funded PhD position in Dynamic Network Analysis (Ireland)

The Unit for Information Mining and Retrieval (http://uimr.deri.ie) invites applications for a funded PhD Studentship as part of the Clique Research Cluster at DERI. At the Clique Research Cluster (http://www.cliquecluster.org), we are investigating and analysing how very large real-life social networks, on-line forums, biological networks and other networks of interest evolve. Some areas we are interested in include:

• Analysing how communities in these networks form and change with time;
• Analysing how information and innovation diffuses and formulating models to describe the observed diffusion behaviour;
• Analysing churn in online communities and mobile call networks.

The Candidate

We are seeking applications for a PhD candidature in dynamic graph analysis. The successful candidate will analyse how particular properties of the networks change, and use network changes to detect abnormal events or to predict how information diffusion is enhanced or hampered. The successful candidate should have a bachelors degree in computer science, maths, science or engineering, and have the pre-requisites for PhD studies at NUI Galway (http://www.nuigalway.ie).

The PhD studentship covers academic fees and includes a generous stipend for a four year period. In addition, desired, though not necessary, requirements are:

• Familiarity with basic graph theory (e.g., finding connected components, shortest paths);
• Familiarity with modelling and simulation;
• Familiarity with social network analysis;
• Familiarity with dynamic data analysis (e.g., data streaming algorithms, incremental algorithms);
• Familiarity with text mining, feature extraction and machine learning;
• Masters or equivalent degree in graph analysis, modelling or social network analysis.

The successful candidate will work with the PI Dr. Conor Hayes and Dr. Jeffrey Chan as part of the Clique Research Cluster at DERI, NUI Galway.


Application

Interested applicants should send an application with the subject header CLIQUE_PhD_09 to conor.hayes@deri.org. The application should contain a CV, a one page statement explaining how the candidate's background is compatible with the aims of the Clique Research Cluster and a list of references.


Vía Social Media Research Mail-list

MSM09, Deadline Extended until September 6

The submission deadline for the 1st International Workshop on Mining Social Media has been extended until 6th of September. If you're working on any possible application of data mining techniques, or even recommender systems, information retrieval or any other Information Access technique to Social Media, this is a very good place to submit your work.

New Book: Modelling and Data Mining in Blogosphere

A new Data Mining for Social Media book has been released. Authored by Nitin Agarwal (University of Arkansas at Little Rock) and Huan Liu (Arizona State University), "This book offers a comprehensive overview of the various concepts and research issues about blogs or weblogs. It introduces techniques and approaches, tools and applications, and evaluation methodologies with examples and case studies".

ISBN: 9781598299083 paperback
ISBN: 9781598299090 ebook

Online version available:

Table of Contents:

• Chapter 1: Modeling Blogosphere
• Chapter 2: Blog Clustering and Community Discovery
• Chapter 3: Influence and Trust
• Chapter 4: Spam Filtering in Blogosphere
• Chapter 5: Data Collection and Evaluation
• Appendix A: Tools in Blogosphere
• Appendix B: API Examples

Wikipedia Page Traffic Statistics for DataMiners

Gregory Piatetsky pointed in KDnuggets Twitter account the release of a data package containing 7 months of hourly pageview statistics for all articles in Wikipedia. This dataset has a compressed size over 320 GB, over 1 TB uncompressed, and includes 7 months of hourly page traffic statistics for over 2.5 Million Wikipedia articles. All text content, statistics and link data in the dataset are licensed under GFDL (GNU Free Document License).

1st International Workshop on Mining Social Media

I'm very glad to announce the MSM09 workshop that we are organizing in Sevilla (Spain), November 9. I hope to see some of you there :D

-------------------------------------------------------
CALL FOR PAPERS

1st International Workshop on Mining Social Media
http://www.socialgamingplatform.com/msm09/
Workshop at CAEPIA 2009 (http://www.lsi.us.es/caepia09)
November 9, 2009, Sevilla, Spain
Submission deadline: July 31, 2009
-------------------------------------------------------

OVERVIEW

Social Media are technological tools that allow users sharing and discuss information. Most Social Media are Internet based applications that manage textual information, as blogs (Blogger, Wordpress), microblogging (Twitter, Pownce), wikis (Wikipedia), forums, or Social Networks (Facebook, MySpace, LinkedIn). But there also exist other Social Media Internet applications where users share more than text, as photo sharing tools (Flickr, Picasa), video sharing (YouTube, Vimeo), livecasting (Ustream), or audio and music sharing (last.fm, ccMixter, FreeSound). More recent Social Media includes virtual worlds (Second Life), online gaming (World of Warcraft, WarHammer Online), game sharing (Miniclip.com) and Mobile Social Media like Nomad Social Networks where users share their current position in the Real World.

Social Media have been able to shift the way information is generated and consumed. At first, information was generated by one person and “consumed” by many people, but now the information is generated by many people and consumed by many people, changing the needs in information access and management. It is also noticeable that Social Media applications manage huge quantities of users and data: Facebook and MySpace manage between 100 and 150 million users, it is estimated that 1 million blog posts are generated each day, microblogging services like Twitter generates 3 million messages each day, YouTube manages more that 150.000 million videos, etc. All these points make clear that Social Media is an excellent application field for data miners.


CALL FOR PARTICIPATION

The Mining Social Media workshop aims to bring practitioners but also researchers with a specific focus on the application of existent or novel Data Mining techniques into the field of Social Media. We encourage the submission of experimental papers where Data Mining techniques are applied into existent Social Media, but also more theoretical papers that show clear application in real Social Media applications. The interesting topics include blog post analysis, blog comments analysis, blog spam, recommender systems for Social Media, clickstream analysis, relevance analysis, spam users detection, behavior analysis, contextual mining, Social Media user segmentation, route analysis for nomad Social Networks, multimedia mining, search in Social Media, etc.

All the submissions must be practical or theoretical applications of Data Mining or Information Management to Social Media (blogs, wikis, social networks, social services, e-mail, etc.).

A. Data Mining for Social Networks
* Novel Algorithms
* Association Rules
* Mining semi-structured data
* Classification and Ranking
* Clustering
* Text Mining
* Machine Learning
* Privacy Preserved Data Mining
* Statistical Methods
* Temporal and spatial data mining
* Parallel and Distributed Data Mining
* Interactive and Online Mining
* Data and Knowledge Visualization
* Multimedia mining (audio/video)
* Ensemble Methods
* Web Mining
* Graph Mining
* Link Mining
B. Information Management for Social Networks
* Recommender Systems
* Information Retrieval
* Sentiment Analysis
* Natural Language Processing
* Question Answering
* Semantic Processing
* Graph Analysis and Complex Networks
* Social Network Analysis
C. Possible applications
* E-Mail Spam Detection
* Blog/Social Networks Spam Detection
* Community Detection
* Users/content recommenders
* Trends discovery
* Blogs/Social Networks Community Dynamics
* User Reviews Ranking
* Blogs/Social Networks Contributions Summarization
* Abuse/Fraud Detection
* User Profile Modeling
* Event Detection and Tracking in Social Media

We welcome contributions through research papers and industrial reports/case studies on applications. We also welcome work-in-progress contributions, as well papers discussing potential research directions.


IMPORTANT DATES

* Deadline for submission: 31 July 2009
* Notification of acceptance: 17 September 2009
* Workshop: 9 November 2009


INVITED SPEAKER

* William W. Cohen (Carnegie Mellon University)


INDUSTRY PANEL

The Industry Panel features panelists from several Social Media companies, who will give their vision about needs, opportunities and current solutions of Data Mining and related techniques to real Social Media solutions. Up to date, Strands (http://www.strands.com) and Tuenti (http://www.tuenti.com) have confirmed their presence in this panel.


SUBMISSION OF PAPERS

Submissions must be anonymous. Papers must be sent in a PDF file, written in English and not exceed 12 pages including figures, references, etc. and should be formatted according to the Springer LNAI guidelines. Papers will be reviewed by at least two PC members, and accepted papers will be published in the workshop proceedings. We are currently studying the possibility of publishing Springer post-proceedings and a special issue on a Data Mining journal.


SPONSORS (confirmed as of May 3, 2009):

* MAVIR (http://www.mavir.net)
* UEM (http://www.uem.es)
* Fundación Madri+D para el Conocimiento (http://www.madrimasd.org)
* STRANDS (http://www.strands.com)


ORGANIZATION COMMITEE

* Jose Carlos Cortizo (Social Gaming Platform, Universidad Europea de Madrid) - primary contact (josecarlos.cortizo@wipley.com)
* Francisco Manuel Carrero (Social Gaming Platform, Universidad Europea de Madrid)
* Jose Maria Gomez (Optenet)
* Enrique Puertas (Universidad Europea de Madrid)
* Borja Monsalve (Social Gaming Platform, Universidad Europea de Madrid)


PROGRAM COMMITEE

* Nitin Agarwal (University of Arkansas at Little Rock, USA)
* Aris Anagnostopoulos (Sapienza Università di Roma , Italy)
* Raul Arrabales (Universidad Carlos III de Madrid, Spain)
* Dominik Benz (University of Kassel, Germany)
* Paolo Boldi (University of Milano, Italy)
* Iván Cantador (Universidad Autónoma de Madrid & University of Glasgow, United Kingdom)
* Francisco Manuel Carrero (Social Gaming Platform, Spain)
* Pablo Castells (Universidad Autónoma de Madrid, Spain)
* Meeyoung Cha (Max Planck Institute, Germany)
* Yun Chi (Nec Laboratories America, USA)
* Jose Carlos Cortizo (Social Gaming Platform, Spain)
* Debora Donato (Yahoo! Research, Spain)
* Cesar Estebanez (Universidad Carlos III de Madrid, Spain)
* Jose Maria Gomez (Optenet, Spain)
* Antonio Gulli (Ask.com, Italy)
* Viet Ha-Thuc (University of Iowa, USA)
* José Antonio Iglesias Martínez (Universidad Carlos III de Madrid, Spain)
* Akshay Java (MSN Microsoft, USA)
* Gueorgi Kossinets (Google, USA)
* Zornitsa Kozareva (Universidad de Alicante, Spain)
* Beate Krause (University of Kassel, Germany)
* Emmanuelle Lebhar (CNRS & Universidad de Chile, Chile)
* Agapito Ledezma Espino (Universidad Carlos III de Madrid, Spain)
* Kristina Lerman (USC Information Sciences Institute, California, USA)
* Ee-Peng Lim (Singapore Management University, Singapore)
* Stéphane Marchand-Maillet (University of Geneva, Switzerland)
* Luis Martin (Universidad Politecnica de Madrid, Spain)
* Borja Monsalve (Social Gaming Platform, Spain)
* Cesar de Pablo (Universidad Carlos III de Madrid, Spain)
* Manos Papagelis (University of Toronto, Canada)
* Victor Peinado (Universidad Nacional de Educación a Distancia, Spain)
* Enrique Puertas (Universidad Europea de Madrid, Spain)
* Josep Lluis de la Rosa (Universidad de Girona & Rensselaer Polytechnic Institute, USA)
* Sara Owsley Sood (Pomona College, USA)
* Markus Strohmaier (Graz University of Technology, Austria)
* Yaiza Temprado (Universidad Europea de Madrid, Spain)
* Marc Torrens (Strands, Spain)

Social Media, Data Mining & Machine Learning

I've been more than two months without updating the blog. A lot of work with my new company, trying to find funding for starting-up, and developing tons and tons of code lines. Now I'll try to update the blog once per week of once each two weeks, at least, but as my research interests have shifted a little bit to Social Media applications, I've decided to change the name of the blog from "Business Intelligence, Data Mining & Machine Learning" o "Social Media, Data Mining & Machine Learning". Probably the name of the blog is not so important, but working now on Social Media I feel more comfortable with that keywork in the title.

IEEE International Conference on Data Mining 2009

December 6-9, 2009 Miami, U.S.A.

The IEEE International Conference on Data Mining (ICDM) has established itself as the world's premier research conference in data mining. The 2009 edition of ICDM provides a leading forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences.

The conference covers all aspects of data mining, including algorithms, software and systems, and applications. In addition, ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing.

By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining.

Besides the technical program, the conference will feature workshops, tutorials, panels, and the ICDM data mining contest.

Topics of Interest

• Data mining foundations
• • Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, pattern discovery, and association analysis)
  • Models and algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
  • Developing a unifying theory of data mining
  • Mining sequences and sequential data
  • Mining spatial and temporal datasets
  • Mining textual and unstructured datasets
  • Distributed data mining
  • High performance implementations of data mining algorithms
  • Privacy and anonymity-preserving data analysis
• Mining in emerging domains
• • Stream data mining
  • Mining moving object data, RFID data, and data from sensor networks
  • Ubiquitous knowledge discovery
  • Mining multi-agent data
  • Mining and link analysis in networked settings: web, social and computer networks, and online communities
  • Mining the semantic web
  • Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks
• Methodological aspects and the KDD process
• • Data pre-processing, data reduction, feature selection, and feature transformation
  • Quality assessment, interestingness analysis, and post-processing
  • Statistical foundations for robust and scalable data mining
  • Handling imbalanced data
  • Automating the mining process and other process related issues
  • Dealing with cost sensitive data and loss models
  • Human-machine interaction and visual data mining
  • Integration of data warehousing, OLAP and data mining
  • Data mining query languages
  • Security and data integrity
• Integrated KDD applications, systems, and experiences
• • Bioinformatics, computational chemistry, ecoinformatics
  • Computational finance, online trading, and analysis of markets
  • Intrusion detection, fraud prevention, and surveillance
  • Healthcare, epidemic modeling, and clinical research
  • Customer relationship management
  • Telecommunications, network and systems management
  • Sustainable mobility and intelligent transportation systems

Important Dates

• April 13, 2009 - Deadline for workshop proposals
• June 26, 2009 - Deadline for paper submission, tutorial submission, and panel proposals
• September 4, 2009 - Notification to authors
• September 28, 2009 - Deadline for camera-ready copies
• December 6-9, 2009 Conference

Our presentation in IDEAL 2008

Tomorrow we will be presenting our paper in IDEAL 2008. We finished the presentation the other day and I've uploaded it to SlideShare in order to share it with you

Presentación en IDEAL 2008

(tags: metamap umls)

Dashboards, pointing the way of Business Intelligence

I use to read an interesting spanish blog related to BI world, called TodoBI, which pointed me to an article about the importance of dashboards in Business Intelligence, written by Tom Gonzalez. In this article, Tom exposes his vision about the future of Business Intelligence. Tom believes that BI should focus on dashboards, adopting a user-centric approach instead of a more data-centric one. In Tom's words

So where does that leave us today, and what does this all mean for the future of BI? I think dashboards represent just the first step for the next major phase in BI both from a technology and a methodology perspective. For lack of a better term I will label this next phase the "BI user experience" as represented by user interfaces that information workers and business executives interact with to "experience" their data [...] Your ability to process that information and the inherent relationships within that data is exponentially higher and faster with the bar chart. This is one area where the human brain still far exceeds the power of technology-driven computation in its ability to recognize and process patterns composed of large volumes of information.

I totally agree with Tom's vision, which fits in my vision of the connection between Machine Learning, Data Mining and Business Intelligence. For me, ML, DM and BI can be seen as 3 different areas, but they can also be seen as a chain where each one plays an important role. DM is data centric as it focuses on data, BI is user centric as it should deal with users needs and ML is the intelligence behind the process (althought not every need needs an intelligent process).

In the figure, ML is represented inside DM and DM inside BI. From the BI point of view, DM is like glacé cherry, a turn of the screw from the statistical processes behind BI. ML is inside DM as it is the engine for processing all the data in DM processes.

WWW Tracks

This year, WWW Conference is held at 10 minutes from my work, at Universidad Europea de Madrid. There are several interesting tracks dealing with different aspects of the Web. The most interesting, for me, are the following tracks: "Data Mining", "Social Networks and Web 2.0", "Semantic/Data Web".

I knew about the CFP but the last time I visited the web there was no info about the tracks. A post in Hurst's blog, reminded me to refresh the info about the WWW Conference.

Data Mining Competition: Discovering Knowledge in NHANES Data

The Knowledge Discovery and Data Mining Working Group of the American Medical Information Association (AMIA) is announcing its second annual data mining competition for the purpose of studying best practices related to knowledge discovery in health care data. This year’s data set is the National Health and Nutrition Examination Survey (NHANES). This is a juried, international data mining competition open to students of any subject or discipline. Four winning individuals or teams will be invited to present their results at the AMIA 2008 Annual Symposium. (No funds for travel or Symposium registration will be provided). Final submissions for the competition are due to the moderator by midnight, September 15, 2008, MDT. Winners of the contest will be invited to present their work at the AMIA Annual Symposium in a panel sponsored by the Knowledge Discovery and Data Mining Working Group. Winners will be selected and recognized by an international panel of judges associated with the KDDM-WG. Please visit http://www.amia.org/mbrcenter/wg/kddm/contest.asp for more details.

Eligibility

This contest is open to student members of the American Medical Informatics Association, planning to attend the AMIA 2008 Annual Symposium. However, students may hail from any subject or discipline. For information on joining AMIA, please visit: http://www.amia.org/mbrcenter/mbrshp/ . The work can be completed by an individual or group, but only one individual will present at the symposium for a winning team.

Participation in the Contest

As a contestant, you are invited to produce meaningful information/ knowledge with knowledge discovery or data mining approaches of your choice, using the publicly available National Health and Nutrition Examination Survey (NHANES) data. The data itself is publicly accessible, and available here: http://www.cdc.gov/nchs/nhanes.htm. The latest data release (as of this announcement) is 2005-2006, but there is no restriction on the specific data release to be used, and entries may utilize multiple data releases. A wide variety of data mining approaches are acceptable, including both supervised and unsupervised learning and the extraction of temporal association and precedence rules. Both applied and methodological entries are appropriate. Final submissions for the competition are due to the moderator by midnight, September 15, 2008, MDT (U.S. Mountain Daylight Time). Winners will be selected and recognized by an international panel of judges associated with the KDDM-WG. Winners of the contest will be invited to present their work at the AMIA Annual Symposium in a dedicated session. (No funds for travel or registration will be provided).

Contest Entry

Entries should consist of the following:

1. A written report (paper), not to exceed a maximum of five (8.5 x 11 inch) pages, including:
   • An abstract of 125 - 150 words
   • Names, academic degree(s), affiliations, and locations (city, state, and country, if international) of all authors (advisers should be added as authors).
   • Content could include sections of introduction, methods, results, discussion, and conclusion, but is left to author discretion.
   • See the Submission Template (MS Word) for correct format. The (pdf) may be helpful.
2. Name and address of student's training education program
3. Advisor's name and contact information
4. A joint statement, signed by the student and the advisor, that identifies the student's specific contribution to the work presented, and attests that the studend prepared the paper.

Submission

Entries must be submitted as .doc or .pdf files. Submit entry to the contest moderator via e-mail: mollie.poynton@nurs.utah.edu. The deadline is midnight, September 15, 2008, MDT.

Useful Links

• National Health and Nutrition Examination Survey (NHANES)
• American Medical Informatics Association, Knowledge Discovery and Data Mining Working Group
• 2007 Data Mining Competition, Winning Entries

PAKDD 2009

The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009) is held on Bangkok, Thailand, 27-30 April 2009.

The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09) is a major international conference in the areas of data mining and knowledge discovery. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and automatic scientific discovery, data visualization, causal induction and knowledge-based systems. The conference website is at http://www.pakdd2009.org.

Important Dates:

• 09 September 2008, Abstract Submission (CFP)
  
• 16 September 2008, Paper Submission
• 19 September 2008, Workshop Proposal (CF Workshop Proposal)
  
• 26 September 2008, Workshop Notification
• 17 November 2008, Tutorial Proposal (CF Tutorial Proposal)
  
• 28 November 2008, Tutorial Notification
• 08 December 2008, Author Notification
• 09 January 2009, Camera Ready
• 27-30 April 2009, Conference & Workshop

KDD 2009 in Paris

KDD comes to Europe, that's a great new for european dataminers :) From June 28 to July 1, KDD will be held at Paris. There are no key dates defined for the conference, but I suppose the Call for Papers will be by the end of January 2009.