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KDD-2007 Conference Goes Beyond Data

Data Mining Experts Explore Movie Rating, Social Networks, Web and Text Mining, Bioinformatics, Privacy

Virginia Gold

The Association for Computing Machinery


Data Mining Experts Explore Movie Rating, Social Networks, Web and Text Mining, Bioinformatics, Privacy

SAN JOSE, August 10, 2007 - The KDD-2007 Conference, hosted by ACM's Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), will address key issues in the rapidly evolving field of data mining and knowledge discovery. Among the topics to be presented at the 13th annual KDD conference are improving movie rating systems, mining social networks, Web and text mining challenges, data clustering and anomaly detection, mining data streams, bioinformatics applications, and privacy protection. KDD-2007, the leading forum for data mining researchers and practitioners, will take place August 12 -15, at the Fairmont Hotel in San Jose, CA.

Program highlights include renowned experts in the data mining field. Among the speakers are Professor Jon Kleinberg of Cornell University, a MacArthur "Genius" Grant winner, on challenges in mining social network data (Monday, August 13); Dr. Usama Fayyad, Chief Data Officer for Yahoo!, on inventing new sciences underlying the Internet (Tuesday, August 14); and Chris Anderson, Editor-in- Chief of Wired magazine, on calculating latent demand in the "Long Tail", a term he coined to describe certain business and economic models that reflect the growth of niche markets (Wednesday, August 15).

This year, the prestigious KDD Cup - the oldest data mining competition - involved digging through millions of customer ratings of thousands of movie titles to predict key aspects of movie rating behavior. It is related to (but different from) the Netflix Prize $1,000,000 competition, which rewards customers for suggestions on improving the Netflix movie recommendation system. The KDD Cup winners as well as several current leaders of the Netflix Prize will describe their work in the KDD Cup workshop on Sunday, August 12.

The KDD-2007 conference features academic and industry papers on the latest research in data mining. It also offers tutorials on mining data streams; text mining and the semantic Web; learning Bayesian networks; and time series analysis. Pre-conference workshops cover a broad array of issues including audience intelligence for advertising; data mining in bioinformatics; knowledge discovery from sensor data; privacy, security, and trust; Web mining and social network analysis; and multimedia data mining.

About ACM
ACM, the Association for Computing Machinery, is an educational and scientific society uniting the world's computing educators, researchers and professionals to inspire dialogue, share resources and address the field's challenges. ACM strengthens the profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

SIGKDD the ACM Special Interest Group on Knowledge Discovery and Data Mining, is the major professional organization for data mining and knowledge discovery researchers and professionals, focusing on the advancement of the science and practice of knowledge discovery and data mining.

ACM/Press Release. Last updated August 10, 2007 by Steven Geringer