RxNLP: Solutions for Text Mining and NLP

  • View rxnlp_api’s profile on Twitter
  • View rxnlp’s profile on GitHub

Menu

  • Home
  • Web APIs
    • API Key
    • API Overview
    • API SDK in Python
    • Text Similarity
    • Topics Extraction
    • Sentence Clustering
    • Summarize Opinions
    • N-Gram Counter
    • HTML2Text
    • GitHub Repository
  • Open Source Tools
    • ROUGE Summary Evaluation
      • ROUGE 2.0 Overview
      • ROUGE 2.0 Usage Documentation
  • Dev Resources
    • RxNLP API Wrappers
  • Q&A
  • Ask Question
  • Contact

nlp

ROUGE 2.0 Usage Documentation - Package for Evaluation of Summarization Tasks

ROUGE 2.0 is an open-source Java Package for Evaluation of Summarization Tasks using ROUGE measures. This document outlines how the ROUGE 2.0 package can be used for evaluation of your summarization tasks. Before you begin… Please ensure that you have

  • View rxnlp_api’s profile on Twitter
  • View rxnlp’s profile on GitHub

Popular Content

  • ROUGE 2.0 - A Java Package for Automatic Summary Evaluation
  • Text Similarity API
  • ROUGE 2.0 Usage Documentation - Package for Evaluation of Summarization Tasks
  • Sentence Clustering API
  • Solutions for Text Mining and NLP

RSS Recent 101 Articles

  • What is ROUGE and how it works for evaluation of summaries?
    ROUGE stands for Recall-Oriented Understudy for Gisting Evaluation. It is essentially of a set of metrics for evaluating automatic summarization of texts as well as machine translation. It works by comparing an automatically produced summary or translation against a set of reference summaries (typically human-produced). Let us say, we have the following system and reference […]
  • Giving an IDF Effect to Probability Count of Words
    The probability of an n-gram or word tells you how important a word is to a document. Unfortunately, since a document almost always has important words inter-mingled with conjunctions and determiners and other types of noise, using the raw probabilities may not be a good idea. One thing that you can do, is to normalize these […]
  • Untold Truths About Text Mining and Web Mining in Practice
    Truth #1: There is no such thing as "THE TOOL" for text miningPeople often ask me, "So what tool do you use for your text analysis projects"...This is how it typically goes..I stare at them not sure whether I should laugh or cry, they stare at me thinking I am crazy and there is a […]

Other Articles

  • What is ROUGE and how it works for evaluation of summarization tasks?
  • Why Use Stop Words for Text Mining?
  • Obtaining Important Words or N-Grams in a Document using Probability Counts
  • What are N-Grams?
  • Constructing a Domain Specific Stop Word List

Latest Questions

  • What algorithm does Sentence Clustering use? asked by chad
  • How do I use a variable in unirest.post while doing topics extraction? asked by Sridhar Nerur
  • Could I use k-means instead of RxNLP Sentence Clustering? asked by Vik
  • Control sentence clustering granularity? asked by Anson
  • What is topic.type? asked by Dahae kim

Tags

api-reference api key evaluation extract text html2text information retrieval keyword extraction natural language processing nlp nlp apis nlp topic extraction open source probability rouge ROUGE-1 ROUGE-N rouge 2.0 sentence clustering tool stop words summarization summary evaluation text analytics text analytics apis text clustering text clustering tool text mining text mining apis text mining guide text similarity text summarization themes discovery tool topic extraction word count
Copyright © 2017 RxNLP
  • Topics Extraction API
  • Sentence Clustering API
  • Text Similarity API
  • N-Gram and Word Counter API
  • HTML2Text API
  • pyrxnlp - API Wrappers in Python
  • API Key