What is the future of Data Scraping and the Structured Web?

Big Data has become a hot topic over the past year. What do you think the reason for this is?

I think this is obvious. It’s difficult to imagine today’s world without data. When I got involved in IT, a 10 MB hard drive seemed gigantic, and today, hard drives capable of storing terabytes of data are a standard! Besides, the largest “drive” today is the Internet that contains an immeasurable amount of data and expands at a mind-blowing speed. We just need to learn to separate seeds from the chaff, and that’s what big data technologies are all about.


Do you have any tips & tricks for people who want to turn unstructured data  structured data from the Web?

The thing is, this is still a fairly complex task. Products vary from “low-level”, where you need to be familiar with things like regex, xpath, css, http and such, to “high-level”, where all you need to do is to make clicks on the data you want to extract. The first type is usually more universal, but requires some technical skills. The second one works even for inexperienced users, but is often not efficient enough for solving more complex tasks. That’s why I truly appreciate the efforts made by import.io and similar services to find the golden mean.

What do you think the future is for the Structured Web, and web data.
There is no doubt that connections between data on the Internet will grow (remember, it once started with the good old hypertext), and the speed of this process depends on how commercially profitable it will be. However, I don’t think that the problem of data scraping will ever go away. Even if all websites eventually become structurally interconnected, there will always be a need to untangle this huge knot 🙂

Source url :-https://www.import.io/post/what-is-the-future-scraping-and-the-structured-web/

Web Scraping using Chrome Scraper Extension

Do you want to get data from a web page or website to CSV or Excel Spreadsheet? The answer is web scraping. There are number of web scraping software and services available in the market like Visual Web Ripper, Mozenda, Kimono Labs, Outwit Hub, ScraperWiki and Automation Anywhere etc. for web data extraction. These all tools and services are paid and not easy to use for non-technical persons. Now I am going to discuss another method of doing web scraping that is easy to use and free.  There are various Google Chrome browser extensions available at Google Web Store (https://chrome.google.com/webstore/category/apps) using that we can do screen scraping/web scraping.

1. Web scraper
Official Website: http://www.webscraper.io

Install it by visiting following link:

https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd

Web Scraper is a chrome extension for scraping data out of web pages to Excel Spreadsheet or database. It allows you to create a plan/sitemap. According to that plan/sitemap a website is traversed and the data is extracted. The extracted data can be exported to CSV or stored in CouchDB. It also supports scraping from multiple pages with pagination. You can use Web Scraper for scraping multiple types of data like text, tables, images, links and more. It also supports web data extraction from dynamic web pages built up with modern web technologies like JavaScript and AJAX.

2. Data Miner
Install DataMiner by visiting following link:

https://chrome.google.com/webstore/detail/dataminer/nndknepjnldbdbepjfgmncbggmopgden

DataMiner is a standalone chrome browser plugin for extracting data from the websites. Later on extracted data can be exported to Microsoft Excel spreadsheets or Google Sheets.

Using DataMiner extension, you can scrape data from tables and lists on the websites and easily export them into CSV file or Microsoft Excel. It also supports XPath selectors. You can use it for scraping emails, Google search results, HTML tables etc.



3. Screen Scraper:
Install it by visiting following link:

https://chrome.google.com/webstore/detail/screenscraper/pfegffhjcgkneoemnlniggnhkfioidjg

Screen Scraper is another chrome scraper as it name suggest is a Chrome browser extension/plugin for screen scraping. Screen scraping is the process of automatically scraping/extracting information from websites. Later on, Scraped information can be downloaded as a CSV file or JSON file. It supports Element Selectors and Xpath Selectors method.

4. iMacro
Official Website of iMacro: http://imacros.net/

Install iMacro it by visiting following link:

https://chrome.google.com/webstore/detail/imacros-for-chrome/cplklnmnlbnpmjogncfgfijoopmnlemp?hl=en

iMacro is a macro recorder for your Google Chrome browser. Macro recorder is a piece of tool that records user actions. It allows users to record repetitious tasks on the web and replay it at later time. It is useful tool for web automation, data extraction and web testing. Using iMacros you can remember passwords, fill out web forms, download files and possibilities are endless. iMacros is useful to Web developers for web regression testing, performance testing and web transaction monitoring. To use iMacros you just need to record the task once and save it in your machine next time when you need to perform the same task you need not repeat the same task again and again. iMacro plugin comes for Chrome, Firefox and Internet Explorer too.

Source url :-http://webdata-scraping.com/web-scraping-using-chrome-scraper-extension/

Data Scraping Doesn’t Have to Be Hard

All You Need Is the Right Data Scraping Partner

Odds are your business needs web data scraping. Data scraping is the act of using software to harvest desired data from target websites. So, instead of you spending every second scouring the internet and copying and pasting from the screen, the software (called “spiders”) does it for you, saving you precious time and resources.

Departments across an organization will profit from data scraping practices.

Data scraping will save countless hours and headaches by doing the following:

- Monitoring competitors’ prices, locations and service offerings
- Harvesting directory and list data from the web, significantly improving your lead generation
- Acquiring customer and product marketing insight from forums, blogs and review sites
- Extracting website data for research and competitive analysis
- Social media scraping for trend and customer analysis
- Collecting regular or even real time updates of exchange rates, insurance rates, interest rates, -mortgage rates, real estate, stock prices and travel prices

It is a no-brainer, really. Businesses of all sizes are integrating data scraping into their business initiatives. Make sure you stay ahead of the competition by effectively data scraping.

Now for the hard part

The “why should you data scrape?” is the easy part. The “how” gets a bit more difficult. Are you savvy in Python and HTML? What about JavaScript and AJAX? Do you know how to utilize a proxy server? As your data collection grows, do you have the cloud-based infrastructure in place to handle the load? If you or someone at your organization can answer yes to these questions, do they have the time to take on all the web data scraping tasks? More importantly, is it a cost-effective use of your valuable staffing resources for them to do this? With constantly changing websites, resulting in broken code and websites automatically blacklisting your attempts, it could be more of a resource drain than anticipated.

Instead of focusing on all the issues above, business users should be concerned with essential questions such as:

- What data do I need to grow my business?
- Can I get the data I need, when I want it and in a format I can use?
- Can the data be easily stored for future analysis?
- Can I maximize my staffing resources and get this data without any programming knowledge or IT assistance?
- Can I start now?
- Can I cost-effectively collect the data needed to grow my business?

A web data scraping partner is standing by to help you!

This is where purchasing innovative web scraping services can be a game changer. The right partner can harness the value of the web for you. They will go into the weeds so you can spend your precious time growing your business.

Hold on a second! Before you run off to purchase data scraping services, you need to make sure you are looking for the solution that best fits your organisational needs. Don’t get overwhelmed. We know that relinquishing control of a critical business asset can be a little nerve-wracking. To help, we have come up with our steps and best practices for choosing the right data scraping company for your organisation.

1) Know Your Priorities

We have brought this up before, but when going through a purchasing decision process we like to turn to Project Management 101: The Project Management Triangle. For this example, we think a Euler diagram version of the triangle fits best.
Data Scraping and the Project Management Triangle

In this example, the constraints show up as Fast (time), Good (quality) and Cheap (cost). This diagram displays the interconnection of all three elements of the project. When using this diagram, you are only able to pick two priorities. Only two elements may change at the expense of the third:

- We can do the project quickly with high quality, but it will be costly
- We can do the project quickly at a reduced cost, but quality will suffer
- We can do a high-quality project at a reduced cost, but it will take much longer
Using this framework can help you shape your priorities and budget. This really, in turn, helps you search for and negotiate with a data scraping company.

2) Know your budget/resources.

This one is so important it is on here twice. Knowing your budget and staffing resources before reaching out to data scraping companies is key. This will make your search much more efficient and help you manage the entire process.

3) Have a plan going in.

Once again, you should know your priorities, budget, business objectives and have a high-level data scraping plan before choosing a data scraping company. Here are a few plan guidelines to get you started:

- Know what data points to collect: contact information, demographics, prices, dates, etc.
- Determine where the data points can most likely be found on the internet: your social media and review sites, your competitors’ sites, chambers of commerce and government sites, e-commerce sites your products/competitors’ products are sold, etc.
- What frequency do you need this data and what is the best way to receive it? Make sure you can get the data you need and in the correct format. Determine whether you can perform a full upload each time or just the changes from the previous dataset. Think about whether you want the data delivered via email, direct download or automatically to your Amazon S3 account.
- Who should have access to the data and how will it be stored once it is harvested?
- Finally, the plan should include what you are going to do with all this newly acquired data and who is receiving the final analysis.

4) Be willing to change your plan.

This one may seem counterintuitive after so much focus on having a game plan. However, remember to be flexible. The whole point of hiring experts is that they are the experts. A plan will make discussions much more productive, but the experts will probably offer insight you hadn’t thought of. Be willing to integrate their advice into your plan.

5) Have a list of questions ready for the company.

Having a list of questions ready for the data scraping company will help keep you in charge of the discussions and negotiations. Here are some points that you should know before choosing a data scraping partner:
- Can they start helping you immediately? Make sure they have the infrastructure and staff to get - you off the ground in a matter of weeks, not months.
- Make sure you can access them via email and phone. Also make sure you have access to those -actually performing the data scraping, not just a call center.
- Can they tailor their processes to fit with your requirements and organisational systems?
- Can they scrape more than plain text? Make sure they can harvest complex and dynamic sites -with JavaScript and AJAX. If a website’s content can be viewed on a browser, they should be-- able to get it for you.
- Make sure they have monitoring systems in place that can detect changes, breakdowns, and -quality issues. This will ensure you have access to a persistent and reliable flow of data, even - when the targeted websites change formats.
- As your data grows, can they easily keep up? Make sure they have scalable solutions that could - handle all that unstructured web data.
- Will they protect your company? Make sure they know discretion is important and that they will not advertise you as a client unless you give permission. Also, check to see how they disguise their scrapers so that the data harvesting cannot be traced back to your business.

6) Check their reviews.

Do a bit of your own manual data scraping to see what others business are saying about the companies you are researching.

7) Make sure the plan the company offers is cost-effective.

Here are a few questions to ask to make sure you get a full view of the costs and fees in the estimate:
- Is there a setup fee?
- What are the fixed costs associated with this project?
- What are the variable costs and how are they calculated?
- Are there any other taxes, fees or things that I could be charged for that are not listed on this -quote?
- What are the payment terms?

Source Url :-http://www.data-scraping.com.au/data-scraping-doesnt-have-to-be-hard/

How Artificial Intelligence Can be Applied to Web Data Extraction

How Artificial Intelligence Can be Applied to Web Data Extraction

Artificial intelligence is not a new topic at all. A lot has been written about it and it has been a popular theme of sci-fi movies from a decade ago. However, it was only recently that we started seeing AI in action. Thanks to the ever-increasing computing power, our machines are much faster and powerful now which also gives a huge boost to AI. It goes without saying that artificial intelligence requires more computing power to be truly intelligent and mimic the human brain.

artificial intelligence web data extraction

AI is finding its way into many everyday objects that we use. The voice assistant apps on your smartphone are a great example for this. Facebook’s face recognition algorithm is another example for intelligent pattern recognition technology in action. We believe that the extraction of data from web is something that humans shouldn’t be burdened with. Artificial intelligence could be the right solution to aggregating huge data sets from the web with minimal manual interference.

Artificial Intelligence VS Machine Learning

There is a stark difference between machine learning and artificial intelligence. In machine learning, you teach the machine to do something within narrowly defined rules along with some training examples. This training and rules are necessary for the machine learning system to achieve some level of success in the process it’s being taught. Whereas, in artificial intelligence, it does the teaching itself with minimal number of rules and loose training.  It can then go on to make rules for itself from the exposure that it gets, which contributes to the continued learning process. This is made possible by using artificial neural networks. Artificial neural networks and deep learning are used in artificial intelligence for speech and object recognition, image segmentation, modeling language and human motion.

Artificial intelligence in web data extraction

The web is a giant repository where data is vast and abundant. The possibilities that come with this amount of data can be ground breaking. The challenge is to navigate through this unstructured pile of information out there on the web and extract it. It takes a lot of time and effort to scrape data from the web, even with the advanced web scraping technologies. But things are about to change. Researchers from the Massachusetts Institute of Technology recently released a paper on an artificial intelligence system that can extract information from sources on the web and learn how to do it on its own.

The research paper introduces an information extraction system that can extract structured data from unstructured documents automatically. To put it simply, the system can think like humans while looking at a document. When humans cannot find a particular piece of information in a document, we find alternative sources to fill the gap. This adds to our knowledge on the topic in question. The AI system works just like this.
The AI system works on rewards and penalties

The working of this AI based data extraction system involves classifying the data with a ‘Confidence score’. This confidence score determines the probability of the classification being statistically correct and is derived from the patterns in the training data. If the confidence score doesn’t meet the set threshold, the system will automatically search the web for more relevant data. Once the adequate confidence score is achieved by extracting new data from the web and integrating it with the current document, it will deem the task successful. If the confidence score is not met, the process continues until the most relevant data has been pulled out.

This type of learning mechanism is called ‘Reinforcement learning’ and works by the notion of learning by reward. It’s very similar to how humans learn. Since there can be a lot of uncertainty associated with the data being merged together, especially where contrasting information is involved, the rewards are given based on the accuracy of the information. With the training provided, the AI learns how to optimally merge different pieces of data together so that the answers we get from the system is as accurate as possible.
AI in action

To test how well the artificial intelligence system can extract data from the web, researchers gave it a test task. The system was to analyse various data sources on mass shootings in the USA and extract the name of the shooter, number of injured, fatalities and the location. The performance was in fact mind blowing as it could pull up the accurate data the way it was needed while beating conventionally taught data extraction mechanisms by more than 10 percent.

The future of data extraction

With ever increasing need for data and the challenges associated with acquiring it, AI could be what’s missing in the equation. The research is promising and hints at a future where intelligent bots with human sight can read and crawl web documents to tell us the bits we need to know.

The AI system could be a game changer in research tasks that require a lot of manual work from humans now. A system like this will not only save time but also enables us to make use of the abundance of information out there on the web. Looking at the bigger picture, this new research is only a step towards creating the truly intelligent web spider that can master a variety of tasks just like humans rather than being focused at just one process.

Source:https://www.promptcloud.com/blog/artificial-intelligence-web-data-extraction

Applications of Web Data Extraction in Ecommerce

web data mining ecommerceWe all know the importance of data generated by an organisation and its application in improvement of product strategy, customer retention, marketing, business development and more. With the advent of digital age and increase in storage capacity, we have come to a point where the internal data generated by an organisation has become synonymous with Big Data. But, we must understand that by focusing only on the internal data, we are losing out another another crucial source – the web data.

Pricing Strategy

This is one of the most common use cases in Ecommerce. It’s important to correctly price the products in order to get the best margins and that requires continuous evaluation and remodeling of pricing strategy. The very first approach takes into account market condition, consumer behavior, inventory and a lot more. It’s highly probable that you’re already implementing such type of pricing strategy by leveraging your organisational data. That said, it’s also equally important to consider the pricing set by the competitors for similar products as consumers can be price sensitive.

We provide data feeds consisting of product name, type, variant, pricing and more from Ecommerce websites. You can get this structured data according to your preferred format (CSV/XML/JSON) from your competitors’s websites to perform further analysis. Just feed the data into the analytics tool and you are ready to factor in the competitors’ pricing into your pricing strategy. This will answer some the important questions such as: Which product can attract premium price? Where can we give discount without incurring loss? You can also go one step further by using our live crawling solution to implement a robust dynamic (real-time) pricing strategy. Apart from this, you can use the data feed to understand and monitor competitors’ product catalog.

Reseller management

There are many manufacturers who sell via resellers and generally there are terms that restrict the resellers from selling the products on the same set of Ecommerce sites. This ensures that the seller is not competing with others to sell own product. But, it’s practically impossible to manually search the sites to find the resellers who are infringing the terms. Apart from that, there might be some unauthorized sellers selling your product on various sites.
Web data extraction services can automate the data collection process so that you’ll be able to search products and their sellers with less time and efficiently. After that your legal department can take the further action according to the situation.

Demand analysis

Demand analysis is a crucial component for planning and shipping products. It answers important questions such as: Which product will move fast? Which one will be slower? To start off, e-commerce stores can analyze own sales figures to estimate the demand, but it’s always recommended that planning must be done much before the launch. That way you won’t be planning after the customers land on your site; you’d be ready with right number of products to meet the demand.
One great place to get a solid idea of demand is online classified site. Web crawling can be deployed to monitor the most in-demand products, categories and the listing rate. You can also look at the pattern according to different geographical locations. Finally, this data can be used to prioritize the sales of products in different categories as per region-specific demand.

Search Ranking on marketplaces

Many Ecommerce players sell their product on their own website along with marketplaces like Amazon and eBay. These popular marketplaces attract a huge number of consumers and sellers. The sheer volume of sellers on these platforms makes it difficult to compete and rank high for particular search performed on these sites. Search ranking in these marketplaces depends on multiple factors (title, description, brand, images, conversion rate, etc.) and needs continuous optimization. Hence, monitoring ranking for preferred keywords for the specific products via web data extraction can be helpful in measuring the result of optimization efforts.

Campaign monitoring

Many brands are engaging with consumers via different platforms such as YouTube and Twitter. Consumers are also increasingly turning towards various forums to express their views. It has become imperative for businesses to monitor, listen and act on what consumers say. You need to move beyond number of retweets, likes, views, etc. and look at how exactly consumers perceived your messages.
This can be done by crawling forums and sites like YouTube and Twitter to extract all the comments related to your brand and your competitors’ brand. Further analysis can be done by performing sentiment analysis. This will give you additional idea for future campaigns and help you optimize product strategy along with customer support strategy.

Takeaway

We covered some of the practical use cases of web data mining in the e-commerce domain. Now it’s up to you to leverage the web data to ensure growth of your retail store. That said, crawling and extracting data from the web can be technically challenging and resource intensive. You need a strong tech team with domain expertise, data infrastructure and monitoring setup (in case of website structure changes) to ensure steady flow of data. At this point it won’t be out of context to mention that some of our clients had tried to do this in-house and came to us when the results didn’t meet expectation. Hence, it is recommended that you should go with a dedicated Data as a Service provider who can deliver data from any number of sites according to pre-specified format at desired frequency. PromptCloud takes care of end to end data acquisition pipeline and ensures high quality data delivery without interruption. Check out our detailed post of on things to consider when evaluating options for web data extraction.

Source Url:-https://www.promptcloud.com/blog/applications-of-web-data-extraction-in-ecommerce/