DARPA has announce another research-relevant competition: the $50,000 Shredder Challenge which invites teams to try to reconstruct virtual shredded documents.

"Today’s troops often confiscate the remnants of destroyed documents in war zones, but reconstructing them is a daunting task. DARPA’s Shredder Challenge calls upon computer scientists, puzzle enthusiasts and anyone else who likes solving complex problems to compete for up to $50,000 by piecing together a series of shredded documents.

The goal is to identify and assess potential capabilities that could be used by our warfighters operating in war zones, but might also create vulnerabilities to sensitive information that is protected through our own shredding practices throughout the U.S. national security community. …

The Shredder Challenge is comprised of five separate puzzles in which the number of documents, the document subject matter and the method of shredding will be varied to present challenges of increasing difficulty. To complete each problem, participants must provide the answer to a puzzle embedded in the content of the reconstructed document."

You can download the puzzles, register a team and submit solutions online as well as view the current top teams. The prizewinner and prize awarded will depend on the number and difficulty of the problems solved. DARPA will a winner in the week of December 5, 2011 once final results are calculated.

DARPA has announce another research-relevant competition: the $50,000 Shredder Challenge which invites teams to try to reconstruct virtual shredded documents.

"Today’s troops often confiscate the remnants of destroyed documents in war zones, but reconstructing them is a daunting task. DARPA’s Shredder Challenge calls upon computer scientists, puzzle enthusiasts and anyone else who likes solving complex problems to compete for up to $50,000 by piecing together a series of shredded documents.

The goal is to identify and assess potential capabilities that could be used by our warfighters operating in war zones, but might also create vulnerabilities to sensitive information that is protected through our own shredding practices throughout the U.S. national security community. …

The Shredder Challenge is comprised of five separate puzzles in which the number of documents, the document subject matter and the method of shredding will be varied to present challenges of increasing difficulty. To complete each problem, participants must provide the answer to a puzzle embedded in the content of the reconstructed document."

You can download the puzzles, register a team and submit solutions online as well as view the current top teams. The prizewinner and prize awarded will depend on the number and difficulty of the problems solved. DARPA will a winner in the week of December 5, 2011 once final results are calculated.

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Jasmine Jones is a Senior pursuing a B.S. in Computer Science and a B.A. in Interdisciplinary Studies: Human-Computer Interaction in an International Cultural Context. A Meyerhoff and NSA Scholar, Jasmine's research deals with how human factors, like culture, gender, and age, affect the way people perceive and use technology.To learn more about Jasmine's research pursutis, read her research profile.

Jasmine Jones is a Senior pursuing a B.S. in Computer Science and a B.A. in Interdisciplinary Studies: Human-Computer Interaction in an International Cultural Context. A Meyerhoff and NSA Scholar, Jasmine's research deals with how human factors, like culture, gender, and age, affect the way people perceive and use technology.To learn more about Jasmine's research pursutis, read her research profile.

AN INTERNSHIP DOES NOT REQUIRE EXPERIENCE, 
BUT EMPLOYMENT DOES.

CSEE Colloquium

Identifying and Isolating Text Classification Signals from
Domain and Genre Noise for Sentiment Analysis

Justin Martineau
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

1:00pm Friday 4 November 2011, ITE 227

Justin Martineau will describe the results of his PhD dissertation which he will defend later this month. His dissertation research makes both algorithmic and theoretical contributions to the fields of domain adaption and sentiment analysis. First, it provides algorithms to discover and weight discriminative classification task specific features within a domain. Second, it produces algorithms to score how well these features transfer to a new target domain. Third, it lays out a general theory for the kinds of information and the types of noise they produce that exist in text classification tasks. Finally, the dissertation presents a definition of domain independence and a statistical description of it. The research offers readers a firm theoretical foundation as well as practical algorithms when implementing any of the motivating examples and for future research in the field.

CSEE Colloquium

Identifying and Isolating Text Classification Signals from
Domain and Genre Noise for Sentiment Analysis

Justin Martineau
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

1:00pm Friday 4 November 2011, ITE 227

Justin Martineau will describe the results of his PhD dissertation which he will defend later this month. His dissertation research makes both algorithmic and theoretical contributions to the fields of domain adaption and sentiment analysis. First, it provides algorithms to discover and weight discriminative classification task specific features within a domain. Second, it produces algorithms to score how well these features transfer to a new target domain. Third, it lays out a general theory for the kinds of information and the types of noise they produce that exist in text classification tasks. Finally, the dissertation presents a definition of domain independence and a statistical description of it. The research offers readers a firm theoretical foundation as well as practical algorithms when implementing any of the motivating examples and for future research in the field.