Linked Data in IBM Watson, Streaming Data Warehouses & SPIN

Session-Type: Technology-Application Session-Level: Intermediate-Advanced Linked Data in Watson, Aditya Kalyanpur A team at IBM Research is working to build Watson, a computing system that can understand and answer complex questions with enough precision and speed to compete against the best human quiz show competitors [1] As with the previous AI grand challenge attempted at IBM Research, (playing chess at a grand master level) the principle challenges for machines to achieve expert performance are fundamentally different than for people. For Watson, the challenge is not acquiring enough knowledge to answer questions, but understanding the questions well enough to exploit the knowledge it has. In this talk I will discuss the rather non-obvious role that linked open data has played in developing Watson. Speaker: Aditya Kalyanpur is a Research Staff Member at IBM Watson in Hawthorne, NY. His research interests include knowledge representation & reasoning, ontologies, natural language processing, machine learning and statistical data mining. Aditya has published in several leading AI journals and conferences, chaired Semantic Web related international workshops and served on W3C Working Groups. He is currently working on the DeepQA project that is advancing the state-of-the-art in automatic, open-domain question answering. DeepQA technology is used in the Watson system that won the Jeopardy! Grand Challenge in February 2011. Aditya has been involved in the development of several core algorithms in Watson related to question analysis, evidence gathering and scoring, knowledge based inference, and answer merging and ranking. Streaming Data Warehouses, Theodore Johnson Many activities generate large data streams - internet searches, web clicks, traffic measurements, and so on. Ted will talk about how to not only process these data streams to extract information from them, but how to store historical views of them in a real-time data warehouse. Speaker: Theodore Johnson received a B.S. in Mathematics from Johns Hopkins University in 1986, and a Ph.D. in Computer Science from NYU in 1990. He was an Associate Professor at the Computer Science and Engineering department of the University of Florida until 1996, when he joined the Database Research group at AT&T Labs - Research. Since then, Ted has developed streaming systems to collect, analyze, correlate, and store information about the configuration and performance of AT&T's global network. SPIN (SPARQL Inferencing Notation), Irene Polikoff Discover a new standard that uses SPARQL to express rules and object behaviors for the Semantic Web. SPIN, also known as SPARQL Rules, has recently been accepted by W3C as a member submission from TopQuadrant, Open Link and RPI. SPIN combines concepts from object oriented languages, query languages, and rule-based systems to describe computational behavior of objects on the web of data. Its use of SPARQL means that SPIN rules can run directly on most RDF query engines and graph stores. Irene Polikoff will introduce SPIN, its design and goals, and demonstrate how SPIN is being used today for the Semantic Web applications. Irene Polikoff is a CEO and Co-founder of TopQuadrant. Since co-founding TopQuadrant in 2001 Irene has been involved in more than a dozen projects in government and commercial sectors. She has written articles and strategy papers, trained customers on the use of the Semantic Web standards, developed ontology models, designed solution architectures and defined deployment processes and guidance. Her current area of focus is on the use of Semantic Web technologies in the Financial Services and Digital Media industries. Prior to TopQuadrant, Irene worked for IBM where she was a Senior Development Manager and a Principal at the Portals and Content Management practice. TopQuadrant’s Irene has a Masters degree in Operations Research from Columbia University. Links: SPIN in 5 slides, SPIN Specification, SPIN Web Site, Enterprise Vocabulary Net 3x3 pitcher x3 TouchGraph with Alex Shapiro. TouchGraph is a data visualization company founded in 2001 by Alex Shapiro. TouchGraph gained popularity as an early adopter of APIs from companies such as Google, Amazon, PubMed, and Facebook to visualize clusters and connections between people, websites, and other media. TouchGraph Navigator provides a way to load data from excel sheets or databases, and to configure the visualization for display on the desktop or on the web. TouchGraph is based in New York City. x3 What's hot in NLP & ML this year - Breck Baldwin, Lingpipe x3 Natural Language Processing at the Ladders - Leslie Barrett, TheLadders.com Impressions TBC

Date June 2nd, 2011 Location The Ladders - Pillsbury Winthrop Shaw Pittman LLP 1540 Broadway New York, NY