For ECML PKDD 2012 in Bristol, UK, we solicit submissions for demos. Submissions must describe working systems and be based on state-of-the-art machine learning and data mining technology. These systems may be innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting. We particularly welcome demos that use open-source software.<\/p>\n
Submissions to all topics listed in the call for papers under Demo submissions will be evaluated on relevance, maturity of the systems to be presented and technical challenges they solve, but also on potential usefuleness to a large number of conference attendees.<\/p>\n Accepted demos will be presented in a special demonstration session, and accepted demonstration papers (4 pages) will be included in the conference proceedings, published by Springer Verlag in the “Lecture Notes in Artificial Intelligence” (LNAI) series. At least one of the demo submitters must register for the conference, and perform the demo on site.<\/p>\n All aspects of the submission and notification process will be handled online via the CMT conference management toolkit at Instructions and deadlines concerning the submission, camera-ready formatting and copyright transfer for conference papers also hold for demo papers, UNLESS OTHERWISE SPECIFIED.<\/p>\n A demonstration submission must be up to 4 pages long. It must provide adequate information on the system’s components and the way the system is operated. Figures, screenshots and interactive demonstration plans may be included if necessary. The authors must further provide a URL that points to a preview of the demonstration. Submitters should keep in mind that the description of a demo has inherently different content than a research paper submitted to the main conference.<\/p>\n A successful demonstration paper provides satisfactory answers to following questions: What makes the presented piece of software unique and special? What are the innovative aspects or in what way\/area does it represent the state of the art? For whom is it most interesting\/useful – an ML or KDD researcher, for a graduate or undergraduate student in these areas, for a practitioner? If there are similar\/related pieces of software, what are the advantages and disadvantages of the presented one?<\/p>\n The formatting guidelines of Springer Verlag for the LNAI series apply, and the author instructions and style files under For inquiries concerning submissions please contact the Demo Track Chairs; contact data below.<\/p>\n For further information please contact the Demo Track Chairs:<\/p>\n
\nhttp:\/\/www.ecmlpkdd2012.net\/calls\/call-for-papers\/<\/a>
\nare eligible; we particularly encourage demonstrations that combine such topics into innovative services.<\/p>\nSubmission Guidelines<\/h3>\n
\nhttps:\/\/cmt.research.microsoft.com\/ECMLPKDD2012\/<\/a><\/p>\n
\nhttp:\/\/www.springer.de\/comp\/lncs\/authors.html<\/a>
\nmust be used.<\/p>\nImportant Dates<\/h3>\n
\n
Contacts<\/h3>\n