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(1) What are good tools to extract key words and/or topics/tags from a random paragraph of text? - Quora

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Tags: nlp
Clipped on: 2016-06-29

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22 Answers
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Abhishek Shivkumar, IBM Watson Labs
25.4k Views · Most Viewed Writer in Natural Language Processing with 60+ answers
First, check with the answers on What is the best text analytics API + service? All the answers there provide pointers to good API functions that extract keywords and/or topics.

Also, recently Topicmarks [1] released their capability which can read your text and provide facts, summaries and keywords. I looked at their results and it is something you might want to explore.

[1]: http://topicmarks.com/(closed operations)
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Vineet Yadav, M.Tech Computational linguistics , IIIT-H Text analytics and Natural language...
27.1k Views · Most Viewed Writer in Natural Language Processing with 120+ answers
  • open source tools

Commercial api
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Antonio Matarranz, High-tech Marketing, Madrid (Spain)
19.2k Views · Most Viewed Writer in Semantic Web
Textalytics (Meaning as a Service) is a cloud-based semantic API that offers a Topic Extraction service (entities, concepts)
In addition, you can tag your text with theme categories, feature-level sentiment, etc.
Disclosure: I work for Daedalus, the company that manufactures Textalytics.

UPDATE:  Textalytics has been rebranded to MeaningCloud Web Services for Text Analytics and Mining | MeaningCloud
and it features a Topics Extraction service Topics extraction & named entity recognition | MeaningCloud
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Sujit Pal, search engineer interested in semantic search, text analytics and NLP, machin...
17.2k Views · Most Viewed Writer in Semantic Web
All great answers, but I see no one has mentioned RAKE so I am mentioning... It works quite nicely and is quite light on performance. The algorithm works by removing stopwords from the text and finding runs of high frequency words, then finds high frequency runs across stopwords if any. It is described in Michael W Berry's book Text Mining Applications and Theory (free PDF available if you search or use Amazon's look inside feature). There is also a Python implementation at https://github.com/aneesha/RAKE/...
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Kumar Ishan, Founder @ ReaderDeck
17.1k Views
You can also look at jatetoolkit - Java Automatic Term Extraction toolkit
It implements following statistical algorithms for keyword/keyphrase extraction.

  • basic term frequency
  • Average term frequency in the corpus (term frequency/ document frequency)
  • TF-IDF
  • RIDF - Inverse Document Frequency (IDF): A Measure of Deviation from Poisson
  • Weirdness - Weirdness indexing for logical document extrapolation and retrieval
  • C-value - A methodology for automatic term recognition.
  • GlossEx - Glossary extraction and knowledge in large organisations via semantic web technologies.
  • TermEx - Termextractor: a web application to learn the shared terminology of emergent web communities.
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Yura Koroliov, Natural Language Processing developer
12.2k Views · Most Viewed Writer in Information Extraction
There are good tutorial on significant phrase extraction at ling-pipe site http://alias-i.com/lingpipe/demo...

I found most useful and scalable Xtract algorithm implementation in Dragon Toolkit (dragon.ischool.drexel.edu). It is English only, but it's use smart wordnet stemmer and POS taggers in addition to pure probabilistic(Chi/Info gain) phrase scoring.

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