nlp

问题 What I'm trying to do: I'm getting from a database a list of uris and download them, removing the stopwords and counting the frequency that the words appears in the webpage, then trying to save in the mongodb. The Problem: When I try to save the result in the database I get the error bson.errors.invalidDocument: the document must be a valid utf-8 it appears to be related to the codes '\xc3someotherstrangewords', '\xe2something' when I'm processing the webpages I try remove the punctuation,

问题 I have 2 sentences in my dataset: w1 = I am Pusheen the cat.I am so cute. # no space after period w2 = I am Pusheen the cat. I am so cute. # with space after period When I use NKTL tokenizer (both word and sent), nltk cannot distinct the between cat.I. Here is word tokenize >>> nltk.word_tokenize(w1, 'english') ['I', 'am', 'Pusheen', 'the', 'cat.I', 'am', 'so', 'cute'] >>> nltk.word_tokenize(w2, 'english') ['I', 'am', 'Pusheen', 'the', 'cat', '.', 'I', 'am', 'so', 'cute'] and sent tokenize >>

问题 I have 2 sentences in my dataset: w1 = I am Pusheen the cat.I am so cute. # no space after period w2 = I am Pusheen the cat. I am so cute. # with space after period When I use NKTL tokenizer (both word and sent), nltk cannot distinct the between cat.I. Here is word tokenize >>> nltk.word_tokenize(w1, 'english') ['I', 'am', 'Pusheen', 'the', 'cat.I', 'am', 'so', 'cute'] >>> nltk.word_tokenize(w2, 'english') ['I', 'am', 'Pusheen', 'the', 'cat', '.', 'I', 'am', 'so', 'cute'] and sent tokenize >>

问题 I have 2 sentences in my dataset: w1 = I am Pusheen the cat.I am so cute. # no space after period w2 = I am Pusheen the cat. I am so cute. # with space after period When I use NKTL tokenizer (both word and sent), nltk cannot distinct the between cat.I. Here is word tokenize >>> nltk.word_tokenize(w1, 'english') ['I', 'am', 'Pusheen', 'the', 'cat.I', 'am', 'so', 'cute'] >>> nltk.word_tokenize(w2, 'english') ['I', 'am', 'Pusheen', 'the', 'cat', '.', 'I', 'am', 'so', 'cute'] and sent tokenize >>

问题 I have 2 sentences in my dataset: w1 = I am Pusheen the cat.I am so cute. # no space after period w2 = I am Pusheen the cat. I am so cute. # with space after period When I use NKTL tokenizer (both word and sent), nltk cannot distinct the between cat.I. Here is word tokenize >>> nltk.word_tokenize(w1, 'english') ['I', 'am', 'Pusheen', 'the', 'cat.I', 'am', 'so', 'cute'] >>> nltk.word_tokenize(w2, 'english') ['I', 'am', 'Pusheen', 'the', 'cat', '.', 'I', 'am', 'so', 'cute'] and sent tokenize >>

问题 I have 2 sentences in my dataset: w1 = I am Pusheen the cat.I am so cute. # no space after period w2 = I am Pusheen the cat. I am so cute. # with space after period When I use NKTL tokenizer (both word and sent), nltk cannot distinct the between cat.I. Here is word tokenize >>> nltk.word_tokenize(w1, 'english') ['I', 'am', 'Pusheen', 'the', 'cat.I', 'am', 'so', 'cute'] >>> nltk.word_tokenize(w2, 'english') ['I', 'am', 'Pusheen', 'the', 'cat', '.', 'I', 'am', 'so', 'cute'] and sent tokenize >>

问题 I'm very new to using spaCy. I have been reading the documentation for hours and I'm still confused if it's possible to do what I have in my question. Anyway... As the title says, is there a way to actually get a given noun chunk using a token containing it. For example, given the sentence: "Autonomous cars shift insurance liability toward manufacturers" Would it be possible to get the "autonomous cars" noun chunk when what I only have the "cars" token? Here is an example snippet of the

问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . Improve this question I am interested in finding similar content(text) based on paraphrasing. How do I do this? Are there any specific tools which can do this? In python preferably. 回答1: I believe the tool you are looking for is Latent Semantic Analysis. Given that my post is going to

问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . Improve this question I am interested in finding similar content(text) based on paraphrasing. How do I do this? Are there any specific tools which can do this? In python preferably. 回答1: I believe the tool you are looking for is Latent Semantic Analysis. Given that my post is going to

问题 I want to translate following routine from class [Word2VecModel]https://github.com/apache/spark/blob/branch-2.3/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala into pyspark. override def transform(dataset: Dataset[_]): DataFrame = { transformSchema(dataset.schema, logging = true) val vectors = wordVectors.getVectors .mapValues(vv => Vectors.dense(vv.map(_.toDouble))) .map(identity) // mapValues doesn't return a serializable map (SI-7005) val bVectors = dataset.sparkSession