Vec2Topic Result

Explanation

Vec2Topic extracts the key topics underlying the given corpus.

  • Topics 1-10 represent all the topics extracted from the corpus. Vec2Topic scores all words and topics and ranks them so that topics are numbered in decreasing order of their importance. Further, each Topic is depicted by listing its top words in decreasing order of their importance.
  • Top words is a ranked list of key words (or bigrams) in the corpus in decreasing order of importance.
  • Time taken to analyze: {{ time }} seconds.
  • This corpus had a total of {{num_words}} words; Vec2Topic is designed for large corpora, so if you are not happy with the results below, try with a larger corpus!

Read our paper for more details: R. S. Randhawa, P. Jain, and G. Madan, Topic Modeling Using Distributed Word Embeddings.

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Top words
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