hank110 / Bagofconcepts
Licence: mit
Python implementation of bag-of-concepts
Stars: ✭ 18
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BOC (Bag-of-Concepts)
This is python implementation of Bag-of-Concepts, as proposed in the paper "Bag-of-Concepts: Comprehending Document Representation through Clustering Words in Distributed Representation" (Han Kyul Kim, Hyunjoong Kim, Sunzoon Cho)
For a given text data, it trains word2vec vectors for each of the words and clusters semantically similar words into a common "concept".
Subsequently, each document is represented by the counts of these concepts with concept frequency - inverse document frequency weighting scheme.
Installation
$ pip install bagofconcepts
Basic Usage
import bagofconcepts as boc
# Each line of corpus must be equivalent to each document of the corpus
boc_model=boc.BOCModel(doc_path="input corpus path")
# output can be saved with save_path parameter
boc_matrix,word2concept_list,idx2word_converter=boc_model.fit()
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