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Wembedder Wikidata-20170613-Truthy-Beta-Cbow-Size=100-Window=1-Min_Count=20

Name: Wembedder Wikidata-20170613-Truthy-Beta-Cbow-Size=100-Window=1-Min_Count=20
Creator: Nielsen, Finn Årup
Keywords: embedding, Wikidata

Research datakeyboard_double_arrow_right Dataset 05 Jul 2017Publisher:Zenodo

Authors: Nielsen, Finn Årup;

doi: 10.5281/zenodo.823195 , 10.5281/zenodo.823194

Wembedder Wikidata-20170613-Truthy-Beta-Cbow-Size=100-Window=1-Min_Count=20

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Abstract

Wikidata embedding ================== Gensim model: wikidata-20170613-truthy-BETA-cbow-size=100-window=1-min_count=20 Download of Wikidata from:: https://dumps.wikimedia.org/wikidatawiki/entities/ Trigram construction:: from bz2 import BZ2File import re dump_filename = 'wikidata-20170613-truthy-BETA.nt.bz2' trigram_filename = 'wikidata-20170613-truthy-BETA.trigrams' pattern = re.compile( (r'^<http://www.wikidata.org/entity/(Q\d+)> ' r'<http://www.wikidata.org/prop/direct/(P\d+)> ' r'<http://www.wikidata.org/entity/(Q\d+)>'), flags=re.UNICODE) with open(trigram_filename, 'w') as f: for line in BZ2File(dump_filename): line = line.decode('utf-8') match = pattern.search(line) if match: f.write(" ".join(match.groups()) + '\n') Construction of Gensim model:: import logging from gensim.models import Word2Vec from gensim.models.word2vec import LineSentence logging.basicConfig( format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO) sentences = LineSentence('wikidata-20170613-truthy-BETA.trigrams') filename = 'wikidata-20170613-truthy-BETA-cbow-size=100-window=1-min_count=20' w2v = Word2Vec(sentences, size=100, window=1, min_count=20, workers=10) w2v.save(filename)

DABAI

Related Organizations

Technical University of Denmark
Denmark

Keywords

embedding, Wikidata

1 Research products, page 1 of 1

Wembedder Wikidata-20170613-Truthy-Beta-Cbow-Size=100-Window=1-Min_Count=20-Iter=25
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