text-extraction

问题 Is there a way to use readability (text extraction algorithm) and a custom algorithm in python to extract links from text? I'd like to figure out a way of extracting links that are in the body of text. 1.) I use readability in python https://github.com/gfxmonk/python-readability 2.) I'd like to somehow compare the extracted text to the original html text in order to extract links in the actual body of an article. 回答1: Well, it looks like it returns a BeautifulSoup tree. So you should be able

问题 In this code I want to scrape title,subtitle and data inside the links but having issues on pages beyond 1 and 2 as getting only 1 item scraped.I want to extract only those entries having title as delhivery only import scrapy from scrapy.contrib.spiders import CrawlSpider, Rule from scrapy.selector import Selector from scrapy.contrib.linkextractors.sgml import SgmlLinkExtractor from urlparse import urljoin from delhivery.items import DelhiveryItem class criticspider(CrawlSpider): name = "delh

问题 As I am new for the REGEX i am not able to solve below thing. And please share some parser related links so the i can learn it. I am facing problem in solving int below SQL statement. Its more line added to the previous INPUT. Please help me to slove this. DECLARE numerator NUMBER; BEGIN SELECT x, y INTO numerator, denominator FROM result_table, s_Table WHERE sample_id = 8; the_ratio := numerator/denominator; IF the_ratio > lower_limit THEN INSERT INTO ratio VALUES (table, coloum); ELSE

问题 I'm researching how to extract keyphrases from document for my thesis. In my research, I used Naive Bayes classifier machine learning for creating a training model of the candidate term features. One of features is PoS tag , I think this feature is important for specifying a term is keyphrase or not. But the input of Naive Bayes (NB) classifier is numbers and the PoS tag is a string. So I don't know the way to represent PoS tag feature as a number in order to become a input feature for NB

问题 I have a column "place" in my table which contains data about a place that looks like: { "id" : "94965b2c45386f87", "name" : "New York", "boundingBoxCoordinates" : [ [ { "longitude" : -79.76259, "latitude" : 40.477383 }, { "longitude" : -79.76259, "latitude" : 45.015851 }, { "longitude" : -71.777492, "latitude" : 45.015851 }, { "longitude" : -71.777492, "latitude" : 40.477383 } ] ], "countryCode" : "US", "fullName" : "New York, USA", "boundingBoxType" : "Polygon", "URL" : "https://api.twitter

问题 I am trying to use textract to convert my .doc files to pure text. import textract text = textract.process('path/to/file.extension') But I am getting this error AttributeError: 'module' object has no attribute 'process' 回答1: Make sure that the Python file you are trying to run is not named textract.py . If that's the name, you will get the error: AttributeError: 'module' object has no attribute 'process' 来源： https://stackoverflow.com/questions/44916890/converting-doc-to-pure-text-using-python

问题 Based on a user's job ID number, I create a recordset of an ID with its different unit types (think pipe sizes) and unit (think footage of pipe). Each unit type record already has the name of the form textbox where the total footage goes in a different column. What I want to do is go through each recordset and plugin the footage for each unit type for that job ID number (that the user puts in a form). Dim rst_UnitEntryCounts As Recordset Set rst_UnitEntryCounts = CurrentDb.OpenRecordset(

问题 I want to automatically extract section "1A. Risk Factors" from around 10000 files and write it into txt files. A sample URL with a file can be found here The desired section is between "Item 1a Risk Factors" and "Item 1b". The thing is that the 'item', '1a' and '1b' might look different in all these files and may be present in multiple places - not only the longest, proper one that interest me. Thus, there should be some regular expressions used, so that: The longest part between "1a" and

问题 I'm currently trying to automatically extract important keywords from a PDF file. I am able to get the text information out of the PDF document. But now I need to know, which font size and font family these keywords have. The following code I already have: Main public static void main(String[] args) throws IOException { String src = "SEM_081145.pdf"; PdfReader reader = new PdfReader(src); SemTextExtractionStrategy semTextExtractionStrategy = new SemTextExtractionStrategy(); PrintWriter out =

问题 Is there an algorithm that can be used to extract simple sentences from paragraphs? My ultimate goal is to later run another algorithm on the resulted simple sentence to determine the author's sentiment. I've researched this from sources such as Chae-Deug Park but none discuss preparing simple sentences as training data. Thanks in advance 回答1: I have just used openNLP for the same. public static List<String> breakIntoSentencesOpenNlp(String paragraph) throws FileNotFoundException, IOException