Ever wondered how a search engine comes up with the exact results when you type something in its query box? After all, there are trillions of results matching your search query. A fascinating process is at work behind it, something you would be very interested to learn about.
Also, understanding how the search and index factors work would help you relate to your customers in a better way.
What is Web Crawling?
Web crawler is a program that acts as an automated script which browses through the internet in a systematic way. The web crawler looks at the keywords in the pages, the kind of content each page has and the links, before returning the information to the search engine. This process is known as Web crawling.
The page you need is indexed by a software known as web crawler. A web crawler gathers pages from the web and then, indexes them in a methodical and automated manner to support search engine queries. Crawlers would also help in validating HTML codes and checking links.
These web crawlers go by different names, like bots, automatic indexers and robots. Once you type a search query, these crawlers scan all the relevant pages that contain these words and turn it into a huge index.
For example, if you are using Google’s search engine, then the crawlers would go through each of the pages indexed in their database and fetch those pages to Google’s servers. The web crawler follows all the hyperlinks in the websites and visits other websites as well.
So when you ask the search engine for a ‘course in software development ‘, it will come up with all the web pages that feature the term. Web crawlers are configured to monitor the web regularly so the results they generate are updated and timely.
How Web Crawlers Work
The spider begins its crawl by going through the websites or list of websites that it visited the previous time. When the crawlers visit a website, they search for other pages that are worth visiting. Web crawlers can link to new sites, note changes to existing sites and mark dead links.
Google Inside Search - How it works
In the World Wide Web, there are trillions and trillions of pages. Google says there are more than over 60 trillion individual pages. Web Crawlers crawl through these pages to bring back the results demanded by customers. Site owners can decide which of their pages they want the web crawlers to index, and they can block the pages that needn’t be indexed.
The indexing is done by sorting the pages and looking at the quality of the content and other factors. Google then generates algorithms to get a better view of what you are searching for, and provides a number of features that make your search more effective, such as:
Spelling - In case there is an error in the word you typed, Google comes up with a number of alternatives to help you get on track.
Google Instant - Instant results as you type.
Search methods - Different options for searching, other than just typing out the words. This includes images and voice search.
Synonyms - Tackles similar worded meanings and produces results.
Auto complete - Anticipates what you need from what you type.
Query understanding - An in-depth understanding of what you type.
Web spiders play an important role in generating accurate results. But it is also your duty to keep your website alive with fresh, high quality and updated content. Did you know that Google Inside Search skims over 200 factors to bring your users relevant and updated content?
What is Data Mining?
Data mining is a powerful technique that helps extract predictive information from databases. This saves time for companies looking for revolutionary face-changing information in their data warehouses.
There are specific tools for data mining and their duty would be to analyze the past behavior of users and predict future trends to help businesses make knowledge-driven, proactive decisions.
Data mining tools help in minimizing the time that it took in the past to analyze the huge amounts of data, while at the same time, scouring for specific patterns in the data that even experts are likely to miss. What a human cannot do manually, data mining can, and it can easily sift through massive quantities of data, with no loss of time or crucial information.
How Web Crawling can help in Data Mining
Now that we have understood what web crawling and data mining are, you can guess that both work in tandem with each other. Once the web crawler collects all the data from various sources, this data will remain in an unstructured form, mainly in JSON, CSV or XML formats. This is raw data and deriving useful insights from it, is known as data mining.
So you can say, web crawling is the first step in the data mining process. The seriousness and importance of data mining comes to light during the extraction process because you’ve got to deal with web pages errors, data in multiple languages and irregular markups. It is also important to retain the encoding format as it is.
Use cases of Data Mining
We have already witnessed the power of Big Data and Mobility in helping a business improve profitability. With the data deluge that’s occurring in every industry, the need to master data mining and following careful business analysis practices are imminent.
This is why you can find excellent use cases of the same in medicine, insurance, scientific research, commerce and a variety of other sectors. Let’s follow this with a couple of examples to understand the importance of data mining:
The Insurance Sector
Insurance companies have been able to leverage the full potential of data mining to gauge the spending and saving patterns of their customers so that they can identify the risk factors and deliver result oriented customer level analysis. This would also help them to develop new product lines, while detecting fraudulent claims and performing accurate financial analysis.
This proves that data mining is applied with very powerful results in the insurance industry and the companies who have applied it have achieved tremendous competitive advantage. Here are a few examples of companies that successfully use data mining to help retaining customers and to weed out fraudulent people - Fidelity, Capital One, Vodafone.
The Healthcare Sector
The application of data mining has helped in the volume and complexity of managing medical data and definitely beats the practice of using manual analysis to find specific patterns in the ever widening repository of data.
For example, effective data mining can help in understanding several biological processes by analyzing a flood of biological and clinical data obtained through protein and genomic sequences, protein interactions, disease pathways, DNA micro arrays, electronic health records and protein interactions.
With state-of-the-art data mining techniques it is easy to handle challenging data mining problems and make meaningful observations and discoveries.
Data Mining in US Presidential Elections
The US Presidential election campaign has made use of data mining to make predictions. The huge boiling cauldron of data has been stirred continuously for collecting big data and using it wisely to reap huge rewards in the campaigns. Everywhere in the world, politicians have made use of the benefits of data mining to guide their election campaigns.
If you observe the previous election results, you can see that it is the candidate who conducts the strongest election campaign that makes it to the President’s podium. Data collection, analysis and intelligent decision making plays a crucial role in deciding how compelling the campaigning was.
Data mining has been used in a variety of degrees to calibrate the pre-election campaigns. In the 2012 and 2016 election campaigns, data mining played a central point in making the predictions because data from each electoral member was collected and analyzed on the basis of their behavioral patterns.
This proved beyond a shadow of doubt that data mining, when used in the right way by the right people offers limitless opportunities.
Image Mining - a Form of Data Mining
Image mining is also a process of searching through huge volumes of data and indexing them on the basis of images. The patterns are drawn according to various principles drawn in the pattern recognition, machine learning, image retrieval and statistics. The extraction of images is an important field as huge amounts of data come in each day.
Extracting data through images
Businesses have begun to extract images from shopping comparison websites and collect information based on customer behavior. So if you are searching for a particular image, you can see the images of the same product and related products in the search results.
Through image mining, you can analyze comprehensive information about different products. This helps you to get search results of the product you are looking for and similar products with variations in color, size and price.
Use case of Image Mining
Google has played a major role in helping users extract data through a novel service known as Google Takeout. This is the perfect choice for people who need to collect information without compromising on their own data, privacy or any such issues. With the benefit of Google Takeout, data mining professionals need not store all the images in secondary storage devices.
Tumblr, the micro-blogging and social networking site is also another good example of image mining. The site stores thousands and thousands of multimedia files that can be retrieved at any time.
The advent of image mining bears testimony to the fact that the process of communication has changed drastically, Content has shrunk to mere captions and the emergence of “visual grammar” has taken on the social media by storm. The start of the storm was through Flickr. Remember Flickr? See how far image mining has come from there.
Web crawling and Data mining can be completed only when another major component comes in. And that is Data extraction. Data extraction is extremely useful for people indulging in online shopping. There are sites with data sources that are structured, like Amazon for example, but some remain unstructured and are hidden deep in the web.
To get the data from such sites, the query will have to be entered in the search box and filters are narrowed to get the results. The result of the search query comes in the form of product details embedded in HTML.
Only a special crawler that parse HTML can scrape and extract exact product details as demanded by the user. The details include product title and information, pricing, variations, rating, reviews, product code and so on. The feed is updated regularly, so the user gets only relevant, timely and fresh data.
Web Crawling using Apache Nutch
Apache Nutch, an open source web crawler and highly extensible software is licensed by Apache Software Foundation. The software can be used to aggregate data from the web, and is used in conjunction with other Apache tools like Hadoop. You can download Apache Nutch from https://wiki.apache.org/nutch/NutchTutorial#Install_Nutch
It makes use of various web crawling algorithms to collect and store data. You can store a huge repository of data collected from various sources in a framework known as Apache Solr.
Scraping the Web with Nutch for Elasticsearch
Have a look at the main components of Nutch and how it works with Elasticsearch.
- Instructions are given to Nutch. All the URLs of the seed file are collected by the injector and stored in the CrawlBase. The CrawlBase records complete information about all the URLs - when they were fetched and their resulting status.
- In the next step, Generator comes into picture. It keeps information of all the URLs in the Segment directory. These are all fetched URLs.
- The Fetcher collects the content of the URLs on the Crawlist and stores them within the Segment directory.
- Further, division takes place with the Parser delivering the content of each website to designated Processors.
- As the last step, Elasticsearch takes over and indexes the content.
Some Prominent Web Crawlers
Let’s go through some of the famous web crawlers:
Scrapy, the Python Scraper
If you are looking for medium-sized scraping jobs, then Scrapy would be ideal. The web crawling framework is quick, simple, collaborative and open source. Another benefit of the framework is that you can plug in a new functionality without affecting its core. It is written in Python and runs on Mac, Linux, Windows and BSD.
Storm-crawler would be your ultimate choice for a low-latency scalable web crawler with a collection of resources. This one is also open source, easily extensible and runs on Apache Storm.
The advantage Storm-crawler has over Nutch is that it fetches URL as per the configurations of the user; Nutch is batch-driven. The advantage Nutch has over Storm-crawler is that while the former is a ready-to-use framework, the latter is not.
Elasticsearch River Web
Elasticsearch River Web plugin is a web crawler application for Elasticsearch. The function of the plugin is to crawl websites and extract content by CSS Query.
Use cases of Web Crawlers
Web crawlers have become so important to companies having a strong online presence, and they use it to obtain data like product information, reviews, pricing details and images to ensure they deliver better than what their competitors give. Web crawlers can, thus, make an impact on every aspect of business.
It could be an e-commerce site or a travel-based comparison site, but the presence of web crawlers makes all the difference to the end user. Everywhere businesses are looking for ways to beat their competition trying to provide better quality products at reasonable prices.
Let’s understand this better with a few use cases:
The Real Estate Industry
Web crawlers have made a huge impact by literally bringing together all the real estate listings in various parts of the country. This catalog is prepared by noting the property descriptions according to type, number of bedrooms, images, market value and other relevant information in a structured format.
Now, the buyer/seller can visit the website offering such information and browse through the listings to know the price and other details of a particular property. In such a website, a data acquisition pipeline will have to be set where millions of records had to be captured, extracted and uploaded.
The Automobile Industry
Web crawlers play an important role in the automobile industry. Take the case of the car industry, for instance, where clients require a plethora of data to be explored from numerous resources like auto spare parts sites, automobile communities, blogs and the like.
The web crawler goes through all the source sites provided by the client, collects and extracts the required data. It is also important to set the parameters for data extraction separately for each site because the source websites may have different structure and design. The user can compare the prices; observe the latest trends, and other data delivered by different sources and then make wise decisions.
Web crawling, Web scraping and Data mining are, thus, instrumental in defining the success of almost every business in the world right from retail and e-commerce to healthcare and entertainment. Everywhere there is demand for insightful data, and site specific crawl is the word of the day. This is why you have specific crawl requirements separately for various social media platforms, e-commerce websites, blogs, news websites and forums.
The results themselves are ranked according to usability and authority by monitoring metadata descriptions and traditional full text methods. Additionally, this is a great boon for website owners because they can see how search engines operate and determine which search engine brings how many search queries.
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