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dc.contributor.author Ruan, Guangchen
dc.contributor.author Zhang, Hui
dc.contributor.author Wernert, Eric
dc.contributor.author Plale, Beth
dc.date.accessioned 2016-03-10T19:37:54Z
dc.date.available 2016-03-10T19:37:54Z
dc.date.issued 2014-07-13
dc.identifier.citation Ruan, G., Zhang, H., Wernert, E., & Plale, B. (2014, July 13). TextRWeb: Large-Scale Text Analytics with R on the Web. Paper presented at XSEDE14, Atlanta, GA. doi:10.1145/2616498.2616557 en
dc.identifier.uri http://hdl.handle.net/2022/20739
dc.description.abstract As digital data sources grow in number and size, they pose an opportunity for computational investigation by means of text mining, NLP, and other text analysis techniques. R is a popular and powerful text analytics tool; however, it needs to run in parallel and re- quires special handling to protect copyrighted content against full access (consumption). The HathiTrust Research Center (HTRC) currently has 11 million volumes (books) where 7 million volumes are copyrighted. In this paper we propose HTRC TextRWeb, an interactive R software environment which employs complexity hiding interfaces and automatic code generation to allow large-scale text analytics in a non-consumptive means. For our principal test case of copyrighted data in HathiTrust Digital Library, TextRWeb permits us to code, edit, and submit text analytics methods empowered by a family of interactive web user interfaces. All these methods combine to reveal a new interactive paradigm for large-scale text analytics on the web. en
dc.language.iso en_US en
dc.rights Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. en
dc.subject R, text analysis, interactive, non-consumptive use, parallel computing en
dc.title TextRWeb: Large-Scale Text Analytics with R on the Web en
dc.type Presentation en
dc.identifier.doi 10.1145/2616498.2616557
dc.altmetrics.display true en


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