Natural language research announcements

[Yonatan Bisk <bisk1 AT illinois.edu>]

Speaker:     Chris Ré of University of Wisconsin-Madison

When:         Today @ 2pm.

Where:        3405 Siebel Center

Talk:           Scaling Markov Logic to 500 Million Documents

Abstract:
The main question driving my research is: how does one deploy statistical 
data-analysis tools to enhance data-driven systems? Our goal is to find 
abstractions that one needs to deploy and maintain such systems. My group is 
attacking this question by building a diverse set of statistical data-driven 
applications: a Machine Reading system whose goal is to read the Web and 
answer complex questions, a muon detector for a neutrino telescope called 
IceCube in collaboration with physicists, and querying over rich content (OCR 
and speech data) in collaboration with social-scientists. Even in this 
diverse set, we have found common abstractions that we are exploiting to 
build systems.

In the technical portion of the talk, I will discuss our framework for a 
language called Markov Logic (think: logic queries with weights) that we have 
been using to build text-processing applications. A key feature of Markov 
Logic is that it allows the developer to express rules that are likely, but 
not certain, to be correct. This has allowed Markov-Logic-based approaches to 
achieve state-of-the-art quality on challenging tasks like Machine Reading. A 
key challenge is that previous implementations of Markov Logic have been 
confined to hundreds of documents; in contrast, I will describe the 
techniques that we use to process over 500 million documents with Markov 
Logic.

Video demos, papers, software, virtual machines containing installations of 
our software with data, and links to applications that are discussed in this 
talk are available fromhttp://www.cs.wisc.edu/hazy.

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