Using LAPPS Grid Services in Hadoop

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dc.contributor.advisor Pustejovsky, James
dc.contributor.author Lynch, Kelley
dc.date.accessioned 2017-07-14T14:31:41Z
dc.date.available 2017-07-14T14:31:41Z
dc.date.issued 2017
dc.identifier.uri http://hdl.handle.net/10192/34030
dc.description.abstract The Language Application (LAPPS) Grid project has among its goals promoting reusability and interoperability of Natural Language Processing (NLP) tools. LAPPS Grid processing services are NLP tools such as tokenizers and part of speech taggers, that are packaged as web services to be used on the LAPPS Grid. The processing services can be used to develop and evaluate different sequences of tools. Interoperability of the tools simplifies development and makes experimentation with a large variety of tools more accessible. According to the International Data Corporation’s 2014 report, the size of the digital universe is doubling every two years. As the quantity of available data grows, the use of distributed tools for big data processing is becoming more of a necessity. Hadoop has proven to be a useful tool for large-scale processing in NLP. This paper describes the development of a system for using LAPPS Grid services with Hadoop. This system offers some of the benefits of the LAPPS Grid, interoperability and reusability, in an environment that can be scaled for processing of large data sets.
dc.description.sponsorship Brandeis University, Graduate School of Arts and Sciences
dc.format.mimetype application/pdf
dc.language English
dc.language.iso eng
dc.publisher Brandeis University
dc.relation.ispartofseries Brandeis University Theses and Dissertations
dc.rights Copyright by Kelley Lynch 2017
dc.subject NLP
dc.subject Hadoop
dc.subject Big Data
dc.subject Natural Language Processing
dc.title Using LAPPS Grid Services in Hadoop
dc.type Thesis
dc.contributor.department Graduate Program in Computational Linguistics
dc.degree.name MA
dc.degree.level Masters
dc.degree.discipline Computational Linguistics
dc.degree.grantor Brandeis University, Graduate School of Arts and Sciences


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