GitHub - nidhinmmohan/PARALLELISING_NLP_TASKS_USING_MAP-REDUCEPARADIGM: Natural Language Processing(NLP) refers to the applications that deal with natural language in a way or other. The proposed system tries to parallelise NLP tasks using map-reduce paradigm. MapReduce is a framework for per- forming data-intensive computations in parallel on commodity computers. The main NLP tasks that the proposed system performs are POS tagging, Stemming, Stopword Removal, Named-entity recognition and Sentimental analysis. The MapReduce algorithm is implemented in Hadoop which is an open source framework for writing and running distributed applications that process large amounts of data. If tasks like POS tagging and Stemming are done sequentially, it may take a lot of time. This is where Hadoop is relevant. Hadoop scales up linearly to handle larger data sets by adding more nodes to the cluster. It also allows users to quickly write efficient parallel code. Keywords: Map-Reduce, NLP, Hadoop, POS Tagging, Stemming, Stopword Removal, Named-Entity Recognition, Sentimental Analysis

nidhinmmohan / PARALLELISING_NLP_TASKS_USING_MAP-REDUCEPARADIGM Public

Natural Language Processing(NLP) refers to the applications that deal with natural language in a way or other. The proposed system tries to parallelise NLP tasks using map-reduce paradigm. MapReduce is a framework for per- forming data-intensive computations in parallel on commodity computers. The main NLP tasks that the proposed system performs…

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commits
Entity.java		Entity.java
Entity.java~		Entity.java~
FINALREPORT.pdf		FINALREPORT.pdf
Sentiment.java		Sentiment.java
Sentiment.java~		Sentiment.java~
WordCount.java		WordCount.java
WordCount.java~		WordCount.java~
wordpos.java		wordpos.java
wordpos.java~		wordpos.java~
wordstem.java		wordstem.java
wordstem.java~		wordstem.java~