nlp

问题 I have worked with globalization settings in the past but not within the .NET environment, which is the topic of this question. What I am seeing is most certainly due to knowledge I have yet to learn so I would appreciate illumination on the following. Setup: My default language setting is English (en-us specifically). I added a second language (Danish) on my development system (WinXP) and then opened the language bar so I could select either at will. I selected Danish on the language bar

问题 here stem function shows error saying that stem required one positional argument in loop as in question? from nltk.stem import PorterStemmer as ps text='my name is pythonly and looking for a pythonian group to be formed by me iteratively' words = word_tokenize(text) for word in words: print(ps.stem(word)) 回答1: You need to instantiate a PorterStemmer object from nltk.stem import PorterStemmer as ps from nltk.tokenize import word_tokenize stemmer = ps() text = 'my name is pythonly and looking

问题 I have a dataframe like below: data = {'speaker':['Adam','Ben','Clair'], 'speech': ['Thank you very much and good afternoon.', 'Let me clarify that because I want to make sure we have got everything right', 'By now you should have some good rest']} df = pd.DataFrame(data) I want to count the number of words in the speech column but only for the words from a pre-defined list. For example, the list is: wordlist = ['much', 'good','right'] I want to generate a new column which shows the frequency

问题 I have a dataframe like below: data = {'speaker':['Adam','Ben','Clair'], 'speech': ['Thank you very much and good afternoon.', 'Let me clarify that because I want to make sure we have got everything right', 'By now you should have some good rest']} df = pd.DataFrame(data) I want to count the number of words in the speech column but only for the words from a pre-defined list. For example, the list is: wordlist = ['much', 'good','right'] I want to generate a new column which shows the frequency

问题 I have a dataframe like below: data = {'speaker':['Adam','Ben','Clair'], 'speech': ['Thank you very much and good afternoon.', 'Let me clarify that because I want to make sure we have got everything right', 'By now you should have some good rest']} df = pd.DataFrame(data) I want to count the number of words in the speech column but only for the words from a pre-defined list. For example, the list is: wordlist = ['much', 'good','right'] I want to generate a new column which shows the frequency

问题 Currently started my journey with Dialogflow,is it possible to display the message from the chatbot into my android app per API? 回答1: There are 3 ways to integrate Dialogflow into your Android App: using Rest API which is not an easy job and frequent issues while creating the request payloads. using Android Client by Dialogflow which most stable and featureful as of now but not updated in a year for new Beta features coming in V2. using Java API client which is still evolving but supports

问题 I have a csv file as col1 col2 col3 some text someID some value some text someID some value in each row, col1 corresponds to the text of an entire document. I would like to create a corpus from this csv. my aim is to use sklearn's TfidfVectorizer to compute document similarity and keyword extraction. So consider tfidf = TfidfVectorizer(tokenizer=tokenize, stop_words='english') tfs = tfidf.fit_transform(<my corpus here>) so then i can use str = 'here is some text from a new document' response

问题 Code: from nltk.tokenize import sent_tokenize pprint(sent_tokenize(unidecode(text))) Output: [After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker.', 'Finally they pushed you out of the cold emergency room.', 'I failed to protect you.', '"Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.',] Input: After Du died

问题 Do you know any big enough lemmatizer database that returns correct result for following sample words: geese: goose plantes: //not found Wordnet's morphological analyzer is not sufficient, since it gives the following incorrect results: geese: //not found plantes: plant 回答1: MorphAdorner seems to be better at this, but it still finds the incorrect result for "plantes" plantes: plante geese: goose Maybe you'd like to use MorphAdorner to do the lemmatization, and then check its results against

问题 I am trying to calculate semantic similarity between two words. I am using Wordnet-based similarity measures i.e Resnik measure(RES), Lin measure(LIN), Jiang and Conrath measure(JNC) and Banerjee and Pederson measure(BNP). To do that, I am using nltk and Wordnet 3.0. Next, I want to combine the similarity values obtained from different measure. To do that i need to normalize the similarity values as some measure give values between 0 and 1, while others give values greater than 1. So, my