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from sumy.parsers.html import HtmlParser |
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from sumy.parsers.plaintext import PlaintextParser |
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from sumy.nlp.tokenizers import Tokenizer |
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from sumy.summarizers.lex_rank import LexRankSummarizer |
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from sumy.nlp.stemmers import Stemmer |
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from sumy.utils import get_stop_words |
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def getSummary(text, nr_sentences): |
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summary=[] |
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LANGUAGE = "english" |
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SENTENCES_COUNT = nr_sentences |
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parser = PlaintextParser.from_string(text, Tokenizer(LANGUAGE)) |
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stemmer = Stemmer(LANGUAGE) |
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summarizer = LexRankSummarizer(stemmer) |
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summarizer.stop_words = get_stop_words(LANGUAGE) |
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for sentence in summarizer(parser.document, SENTENCES_COUNT): |
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summary.append(sentence) |
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return summary |
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