Archive for the ‘Events’ Category

Data Mining Conferences 2010-2011

Wednesday, December 1st, 2010

A list of data mining research conferences, workshops, and meetings. Some of them are as follows:

[1] SIAM Conference on Data Mining (SDM 2011)
This conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending tutorials (included with conference registration). A set of focused workshops are also held on the last day of the conference. The proceedings of the conference are published in archival form, and are also made available on the SIAM web site.
Website: http://www.siam.org/meetings/sdm11/

[2] SIGKDD Conference on Knowledge Discovery and Data Mining
The annual ACM SIGKDD conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. KDD-2011 will feature keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, demonstrations, and the KDD Cup competition.
Website: http://kdd.org/kdd/2011/

[3] ACM SIGMOD 2011
The annual ACM SIGMOD/PODS conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools, and experiences.
Website: http://www.sigmod2011.org/index.shtml

[4] IJCAI 2011
The IJCAI-11 Program Committee invites submissions of technical papers for IJCAI-11, to be held in Barcelona, Spain, July 19-22, 2011. Submissions are invited on significant, original, and previously unpublished research on all aspects of artificial intelligence. The theme of IJCAI-11 is “Integrated and Embedded Artificial Intelligence” (IEAI) with a focus on artificial intelligence that crosses discipline boundaries within AI, and between AI and other disciplines. Building systems often requires techniques from more than one area (e.g. both machine learning and natural language processing, or both planning and preference representation). In addition, larger systems often have AI components embedded within that provide intelligent functionalities such as learning and reasoning. The conference will include a special track dedicated to such work.
Website: http://ijcai-11.iiia.csic.es/

[5] ECML PKDD 2011
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) will take place in Athens, Greece from September 5th to 9th, 2011. This event builds upon a very successful series of 21 ECML and 14 PKDD conferences, which have been jointly organized for the past ten years.
Website: http://www.ecmlpkdd2011.org/

Other Conferences:

[6] TDWI World Series Conference
What is your corporate data strategy? Most business and IT professionals point to their data models, data quality tools, or even a spreadsheet data “dictionary.” Maybe you’re just getting started with a new data quality project. Maybe you already have several data management initiatives in place and are making good progress. Or perhaps you’ve recently inherited the mess someone else made. In any case, does your right hand know what your left is up to? Several departmental data initiatives—even successful ones—do not equal a corporate data strategy. TDWI fosters a community of learning where business and technical professionals come together to gain knowledge and skills, network with peers, and advance their careers. Through education and research programs, TDWI enables individuals, teams, and organizations to leverage information to improve decision making, optimize performance, and achieve business objectives.
Website: http://events.tdwi.org/events/las-vegas-world-conference-2011/home.aspx?utm_source=AttendeeMktg&utm_medium=E-Mail&utm_campaign=lv20g

Realizing the popularity, and the need of Data Mining in the road ahead, has resulted into organizing many more conferences (also conferences into  many more specialized data mining streams) to be held all over the world. So, many more conferences, lots of research and great innovations and discoveries lay ahead.

  • Share/Bookmark

RCOMM 2010: Rapid Miner Conference

Friday, July 16th, 2010

RapidMiner Community Meeting And Conference – RCOMM 2010

As RapidMiner has once again proved to be the most-used open source data mining tool among the community of data analysts world-wide in a recent poll, it is now the time to give a face to that community. Therefore, Rapid-I hosts the first RapidMiner Community Meeting And Conference (RCOMM 2010) and invites users and developers of RapidMiner to take part and share their RapidMiner experiences with other members of the community. The RCOMM 2010 intends to intensify the community life and strengthen the RapidMiner network by bringing together users and developers of RapidMiner from all backgrounds, may they be scientific or commercial, from the whole variety of applications and from all grades of knowledge. A vital exchange of ideas, application reports, and scientific results will help beginners to advance and will inspire the already advanced leading them to professionalism. Users will profit from in-depth knowledge of developers, who in turn will gain from picking up requirements and ideas for further development.

The RCOMM 2010 encompasses conference talks, in which invited lecturers will discuss aspects of state-of-the-art data mining with RapidMiner. A Call-for-Papers will be issued for those who would like to present their work in that scope. Workshops will be held to give participants a hands-on experience concerning several topics regarding RapidMiner usage. Additionally, attendees of the RCOMM 2010 will also have the option to participate in several courses given by professional RapidMiner consultants in the surrounding of the user meeting.

Dates & Deadlines:
Submission Deadline:August 6, 2010
Notification of Acceptance:August 13, 2010
Camera-ready Papers:August 20, 2010
Conference: September 13 – 16, 2010

Visit Conference Home: RCOMM
Registration Link: Registration
Schedule Link: Schedule

  • Share/Bookmark

Annual survey shows the importance & high spirits towards data mining

Sunday, March 28th, 2010

As a service to the data mining community, RexerAnalytics conducts an annual online survey (started in 2009). It analyzes some factors like experiences, priorities, views and challenges being faced by data mining industry. The Third Annual Data Miner Survey results were announced after studying the reports of 710 respondents from the data mining community. It was concluded that data miners and their organization’s are highly confident and happy with their services and analytic capabilities giving a feedback of  “above average” or “excellent” performances. Most of them even assured that economy conditions will never be a set back or a weak point for them. According to the survey result, the most commonly used and most satisfying primary data mining tools this year are IBM SPSS Modeler (SPSS Clementine), Statistica, and IBM SPSS Statistics (SPSS Statistics). Open source tool Weka is increasingly used by both academic and for-profit data miners. SAS Enterprise Miner dropped in data miner’s tool rankings this year.

Some highlights:

  • 40-item survey of data miners, conducted on-line in early 2009.
  • 710 participants from 58 countries.
  • Data miners’ most commonly used algorithms are regression, decision trees,
    and cluster analysis.
  • Half of data miners say their results are helping to drive strategic
    decisions and operational processes.
  • 58% say they are adding to the knowledge base in the field.
  • 60% of respondents say the results of their modeling are deployed
    always or most of the time.
  • Most data miners feel that the economy will not negatively impact them.
  • Almost half of industry data miners rate the analytic capabilities of their
    company as above average or excellent.  But 19% feel their company has
    minimal or no analytic capabilities.
  • The top challenges facing data miners are dirty data, explaining data mining
    to others, and difficult access to data.  However, in 2009 fewer data miners
    listed data quality and data access as challenges than in the previous year.
  • IBM SPSS Modeler (SPSS Clementine), Statistica, and IBM SPSS Statistics
    (SPSS Statistics) are identified as the “primary tools” used by the most data
    miners.
  • Open-source tools Weka and R made substantial movement up data
    miner’s tool rankings this year, and are now used by large numbers of
    both academic and for-profit data miners.
  • SAS Enterprise Miner dropped in data miner’s tool rankings this year.
  • Users of IBM SPSS Modeler, Statistica, and Rapid Miner are the most
    satisfied with their software.
  • Fields & Industries:  Data mining is everywhere.  The most sited areas are
    CRM / Marketing, Academic, Financial Services, & IT / Telecom.  And in the
    for-profit sector, the departments data miners most frequently work in are
    Marketing & Sales and Research & Development.

[RexterAnalytics]

  • Share/Bookmark

SAS: Leader in Predictive Analytics

Saturday, February 6th, 2010

SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market.  SAS predictive analytics and data mining solutions were evaluated by Forrester against 53 criteria in three categories through vendor surveys, product demonstration and vendor-reference interviews. SAS earned top overall ranking in all three categories — current offering, strategy and market presence — including perfect scores for functionality, professional services, licensing and cost, direction, and company financials criteria and has been named a leader among nine vendors in The Forrester Wave: Predictive Analytics and Data Mining Solutions, Q1 2010.

Today’s industry generates large volumes of data from all sectors such as  financial, retail,  factory, call centers, and customer products,  and so forth, SAS Analytics lets them realize the value within these growing volumes of data.

[Read more @ SAS]

  • Share/Bookmark