A Quicker Way to Build Datasets through Web Scraping

If you want to skip the HTML tag digging and get straight to scraping, here’s the gist. **Note that the scraper tries to do an exact match with each item in your wanted list. **Otherwise, read on for a short background on webscraping, when it’s useful to scrape websites, and some challenges you may experience while scraping.

from autoscraper import AutoScraper
	## replace with desired url
	url = 'https://www.yelp.com/biz/chun-yang-tea-flushing-new-york-flushing' 
	## make sure that autoscraper can exactly match the items in your wanted_list 
	wanted_list = ['A review']     ## replace with item(s) of interest

	## build the scraper
	scraper = AutoScraper()
	result = scraper.build(url, wanted_list)

	## get similar results, and check which rules to keep
	groups = scraper.get_result_similar(url, grouped=True)
	groups.keys()
	groups['rule_io6e'] ## replace with rule(s) of interest

	## keep rules and save the model to disk
	scraper.keep_rules('rule_io6e') ## replace with rule(s) of interest
	scraper.save('yelp-reviews')    ## replace with desired model name

	#-------------------------------------------------------------------------
	## using the model later
	scraper.load('yelp-reviews')
	new_url = ""                    ## replace with desired url
	scraper.get_result_similar(new_url)

#dataset #python #web-scraping #data-collection

What is GEEK

Buddha Community

A Quicker Way to Build Datasets through Web Scraping

Inside ABCD, A Dataset To Build In-Depth Task-Oriented Dialogue Systems

According to a recent study, call centre agents’ spend approximately 82 percent of their total time looking at step-by-step guides, customer data, and knowledge base articles.

Traditionally, dialogue state tracking (DST) has served as a way to determine what a caller wants at a given point in a conversation. Unfortunately, these aspects are not accounted for in popular DST benchmarks. DST is the core part of a spoken dialogue system. It estimates the beliefs of possible user’s goals at every dialogue turn.

To reduce the burden on call centre agents and improve the SOTA of task-oriented dialogue systems, AI-powered customer service company ASAPP recently launched an action-based conversations dataset (ABCD). The dataset is designed to help develop task-oriented dialogue systems for customer service applications. ABCD consists of a fully labelled dataset with over 10,000 human dialogues containing 55 distinct user intents requiring sequences of actions constrained by company policies to accomplish tasks.

https://twitter.com/asapp/status/1397928363923177472

The dataset is currently available on GitHub.

#developers corner #asapp abcd dataset #asapp new dataset #build enterprise chatbot #chatbot datasets latest #customer support datasets #customer support model training #dataset for chatbots #dataset for customer datasets

A Quicker Way to Build Datasets through Web Scraping

If you want to skip the HTML tag digging and get straight to scraping, here’s the gist. **Note that the scraper tries to do an exact match with each item in your wanted list. **Otherwise, read on for a short background on webscraping, when it’s useful to scrape websites, and some challenges you may experience while scraping.

from autoscraper import AutoScraper
	## replace with desired url
	url = 'https://www.yelp.com/biz/chun-yang-tea-flushing-new-york-flushing' 
	## make sure that autoscraper can exactly match the items in your wanted_list 
	wanted_list = ['A review']     ## replace with item(s) of interest

	## build the scraper
	scraper = AutoScraper()
	result = scraper.build(url, wanted_list)

	## get similar results, and check which rules to keep
	groups = scraper.get_result_similar(url, grouped=True)
	groups.keys()
	groups['rule_io6e'] ## replace with rule(s) of interest

	## keep rules and save the model to disk
	scraper.keep_rules('rule_io6e') ## replace with rule(s) of interest
	scraper.save('yelp-reviews')    ## replace with desired model name

	#-------------------------------------------------------------------------
	## using the model later
	scraper.load('yelp-reviews')
	new_url = ""                    ## replace with desired url
	scraper.get_result_similar(new_url)

#dataset #python #web-scraping #data-collection

Autumn  Blick

Autumn Blick

1603805749

What's the Link Between Web Automation and Web Proxies?

Web automation and web scraping are quite popular among people out there. That’s mainly because people tend to use web scraping and other similar automation technologies to grab information they want from the internet. The internet can be considered as one of the biggest sources of information. If we can use that wisely, we will be able to scrape lots of important facts. However, it is important for us to use appropriate methodologies to get the most out of web scraping. That’s where proxies come into play.

How Can Proxies Help You With Web Scraping?

When you are scraping the internet, you will have to go through lots of information available out there. Going through all the information is never an easy thing to do. You will have to deal with numerous struggles while you are going through the information available. Even if you can use tools to automate the task and overcome struggles, you will still have to invest a lot of time in it.

When you are using proxies, you will be able to crawl through multiple websites faster. This is a reliable method to go ahead with web crawling as well and there is no need to worry too much about the results that you are getting out of it.

Another great thing about proxies is that they will provide you with the chance to mimic that you are from different geographical locations around the world. While keeping that in mind, you will be able to proceed with using the proxy, where you can submit requests that are from different geographical regions. If you are keen to find geographically related information from the internet, you should be using this method. For example, numerous retailers and business owners tend to use this method in order to get a better understanding of local competition and the local customer base that they have.

If you want to try out the benefits that come along with web automation, you can use a free web proxy. You will be able to start experiencing all the amazing benefits that come along with it. Along with that, you will even receive the motivation to take your automation campaigns to the next level.

#automation #web #proxy #web-automation #web-scraping #using-proxies #website-scraping #website-scraping-tools

The Best Way to Build a Chatbot in 2021

A useful tool several businesses implement for answering questions that potential customers may have is a chatbot. Many programming languages give web designers several ways on how to make a chatbot for their websites. They are capable of answering basic questions for visitors and offer innovation for businesses.

With the help of programming languages, it is possible to create a chatbot from the ground up to satisfy someone’s needs.

Plan Out the Chatbot’s Purpose

Before building a chatbot, it is ideal for web designers to determine how it will function on a website. Several chatbot duties center around fulfilling customers’ needs and questions or compiling and optimizing data via transactions.

Some benefits of implementing chatbots include:

  • Generating leads for marketing products and services
  • Improve work capacity when employees cannot answer questions or during non-business hours
  • Reducing errors while providing accurate information to customers or visitors
  • Meeting customer demands through instant communication
  • Alerting customers about their online transactions

Some programmers may choose to design a chatbox to function through predefined answers based on the questions customers may input or function by adapting and learning via human input.

#chatbots #latest news #the best way to build a chatbot in 2021 #build #build a chatbot #best way to build a chatbot

Sival Alethea

Sival Alethea

1624402800

Beautiful Soup Tutorial - Web Scraping in Python

The Beautiful Soup module is used for web scraping in Python. Learn how to use the Beautiful Soup and Requests modules in this tutorial. After watching, you will be able to start scraping the web on your own.
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=87Gx3U0BDlo&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=12
🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency - For Beginner
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#web scraping #python #beautiful soup #beautiful soup tutorial #web scraping in python #beautiful soup tutorial - web scraping in python