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Home > iSGTW 28 May 2008 > iSGTW Feature - Relationships in texts UNC

Feature - Claim jumping through scientific literature

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Finding relationships in texts from diverse fields

Researchers in search of higher productivity and more effective cross-disciplinary collaboration can add a new tool to their kit.

Catherine Blake, an assistant professor in the School of Information and Library Science at the University of North Carolina , has developed a method for retrieving, analyzing and finding relationships in published research texts from multiple disciplines. Claim Jumping through Scientific Literature, as it is called, enables researchers in a given field to collect relevant published information from other fields of study.

Blake’s team analyzed 162,000 documents from a variety of scientific fields using a process called dependency parsing, which analyzes the grammatical structure of sentences to find meaningful relationships among words in different documents.

“Generating these results on a high-end desktop computer would have required about 15,000 hours, or seven and a half years of 40-hour work weeks,” says Blake.

The Renaissance Computing Institute (RENCI), a joint venture between several North Carolina universities and the state government, provided Blake with technical expertise, onsite resources, and connections to Open Science Grid’s nationwide network of computing resources. The work was done through RENCI’s Faculty Fellows program, an effort funded by UNC Chapel Hill that partners faculty members on the Chapel Hill campus with experts and resources available through RENCI.

Catherine Blake of UNC-Chapel Hill

 Image courtesy of UNC

Blake and her research team now generate the sentence structure of millions of sentences in about 28 hours using Open Science Grid resources.

“It is an ideal project for the grid because the job is already carved up into small pieces that can use computer resources anywhere, " Blake says. “Reducing the processing time has enabled us to investigate otherwise prohibitively complex research questions.”

Blake and RENCI are currently working to provide the text processing as a service to researchers in natural language processing.

“Allowing researchers to access computationally expensive tools such as these without the initial start-up time would be of enormous value,” she adds. 

- Karen Green, RENCI


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