Future Search: From Information Retrieval to Information Enabled Commerce
William Chang, Baidu
The China Economic Miracle has produced thirty years of sustained 10% GDP growth, allowing China to overtake Japan. Recently, concerned with social issues, debt safety, high commodity prices and weak exports, China has sought to tame that part of GDP derived from “real estate as securities” i.e. properties constructed for purpose of trade instead of use. Instead, China has turned to exhorting with urgency domestic consumption, but the country lacks many of the foundations of Information Enabled Commerce, contrastingly the epitome of American ingenuity and the very source of America's global competitive edge. We will survey some of these inventions for IEC from the viewpoint of IR. We will also survey China's demographic, social, cultural, and economic background and the role information now plays in people's daily lives, showcasing successful applications and business models that can suggest further opportunities for IR and IEC. Although China's 30-year development hasn't really built many of the things that the West takes for granted, people there are beginning to try: China's emerging Internet commerce has already exceeded 1% of GDP and is expected to double this year.
Dr. William Chang joined the Baidu team in January 2007 as Chief Scientist. Prior to joining Baidu, Dr. Chang served as the CTO of Infoseek and the VP of Strategy of Go Network. He is also the creator of the highly successful Infoseek natural language search engine. Dr. Chang has extensive expertise in search technology, online community building and advertising business models.
Dr. Chang earned an undergraduate degree in mathematics from Harvard and a PhD in computer science from the University of California, Berkeley for his breakthrough work in text search. At the renowned Cold Spring Harbor Laboratory, Dr. Chang mapped a genome and invented a protein sequence search methodology. More recently, he created a contextual advertising product at Sentius Corporation, and founded Affini, Inc.
At Baidu, Dr. Chang created structures and policies for managing an engineering team of over one thousand, focusing on education, evaluation, and governance. He strategized and led campaigns that made Baidu the top campus brand and secured the best possible talent pool, with which Baidu successfully turned back formidable competitors. Dr. Chang also championed the development of advanced technology to automate testing and operations, to optimize systems performance and cost-efficiency, and to continually improve search and advertising relevance and effectiveness.
Search flavours - recent updates and trends
Yossi Matias, Google
This talk will discuss some recent developments in Search, emerging in various shapes and forms. We will highlight some challenges, and point to some search trends that play an increasing role in multiple domains.
Yossi Matias is the head of Google's Israel R&D Center, with overall responsibility for Google research, development, and technology innovation in Israel. The Israeli center is part of Google's global Engineering organization, and under his leadership has developed highly visible and core technologies in the areas of Search, Data Analysis, Gmail, YouTube, and Internet scale infrastructure. Matias joined Google in 2006 to establish the Tel-Aviv R&D Center. He is also on the CS faculty of Tel Aviv University (on leave), and previously a research scientist at Bell Labs. He is a recipient of the 2005 Gödel prize and an ACM Fellow.
Query Understanding at Bing
Jan Pedersen, Bing
Web Search is a modern marvel because it is able to produce very relevant results from relatively short queries evaluated over a vast database. Much of the magic is due to query understanding; the technology that analyzes a user query and produces a suitable backend search expression. This technology corrects common orthographic errors, expands terms to their semantically similar equivalents, and groups terms into concepts. I will discuss the language models behind these technologies and their role in canonical web search engine architecture.
Jan Pedersen began his career at Xerox's Palo Alto Research Center (PARC) where he managed a research program on information access technologies. In 1996 he joined Verity (recently purchased by Autonomy) to manage their advanced technology program. In 1998 Dr. Pedersen joined Infoseek/Go Network, a first generation Internet search engine, as Director of Search and Spidering. In 2002 he joined Alta Vista as Chief Scientist. Alta Vista has later acquired acquired by Yahoo!, where Dr. Pedersen served as Chief Scientist for the Search and Advertising Technology Group. Prior to joining Microsoft, Dr. Pedersen was Chief Scientist at A9, an Amazon company.
Dr. Pedersen holds a Ph.D. in Statistics from Stanford University and a AB in Statistics from Princeton University. He is credited with more than ten issued patents and has authored more than twenty refereed publications on information access topics, seven of which are in the Special Interest Group on Information Retrieval (SIGIR) proceedings.
This talk will discuss the machine learning approach to search quality problems at Yandex, the largest search engine in Russian Federation. We focus on a number of learning approaches that are vital in solving the large-scale IR problems, and explore the capabilities and prospects of machine learning in search quality, as well as the problems that appear in handling the real-world data sets based on our experiences at Yandex. We also describe Internet Mathematics 2009 contest which was organized by Yandex to stimulate research in the fields of data analysis and ranking methods.
Ilya Segalovich is one of Yandex co-founders and has been Yandex Chief
Technology Officer and a director since 2003. He began his career working on
information retrieval technologies in 1990 at Arcadia Company, where he
headed Arcadia’s software team. From 1993 to 2000, he led the retrieval
systems department for CompTek International. Mr. Segalovich received a
degree in geophysics from the S. Ordzhonikidze Moscow Geologic Exploration
Institute in 1986. He also took an active role in starting Russian research
and scientific initiatives in information retrieval and computational