Differences Between Web And Data Mining

Have you come across the term web mining? If you haven’t, there’s no reason to panic. In this guide, we’ll explain what web mining is, and the differences it has from data mining. Do well to go through this guide to benefit from its content.

What is Web Mining?

Web mining simply is the process of using data mining techniques and algorithms to extract information directly from the Web by extracting it from Web documents and services, Web content, hyperlinks, and server logs. The goal of Web mining is to look for patterns in Web data by collecting and analyzing information in order to gain insight into trends, the industry, and users in general.

What is Data Mining?

Data mining is a process used by an organization to turn raw data into useful data. Make use of software to find patterns in large data sets, organizations can learn more about their customers to develop more efficient business strategies, boost sales, and reduce costs. Useful data collection, storage, and processing of data are important advantages of data mining. The data mining method is used to develop machine learning models.

Importantly, note that web mining is a branch of data mining focused on the World Wide Web as the primary data source, including all of its components from Web content, and server logs to everything in between. The contents of data mined from the Web may be a group of facts that Web pages are meant to contain, and these may consist of text, structured data such as lists and tables, and even images, video, and audio.

Categories of Web mining:

Web content mining — this is the process of mining useful information from the contents of Web pages and Web documents, which are mostly text, images, and audio/video files. Techniques used in this discipline have been heavily drawn from natural language processing (NLP) and information retrieval.

Web structure mining — this is the process of analyzing the nodes and connection structure of a website through the use of graph theory. There are two things that can be obtained from this: the structure of a website in terms of how it is connected to other sites and the document structure of the website itself, as to how each page is connected.

Web usage mining — This is the process of extracting patterns and information from server logs to gain insight into user activity including where the users are from, how many clicked what item on the site, and the types of activities being done on the site.

Web Mining vs. Data Mining

When comparing web mining to traditional data mining, there are three main differences to consider:

  • Scale: In traditional data mining, processing 1 million records from a database would be a lot of work. In web mining, even 10 million pages wouldn’t be a very large number.
  • Access: When mining corporate information data, the data is private and often requires access rights to read it. For web mining, data is public and rarely requires access rights. However, web mining has additional limitations, due to the implicit agreement regarding webmasters of automated access to this data. This implicit agreement is that a webmaster allows crawlers to access user data on the website, and instead the crawler promises not to overload the site and has the potential to drive more traffic to the web page once the search index is published. With web mining, there is often no such index, which means that the crawler has to be very careful during the crawling process, so as not to cause any problems for the webmaster.
  • Structure: A traditional data mining task gets information from a database, which provides a certain level of explicit structure. A typical web mining task is to process unstructured or semi-structured data from web pages. Even though the underlying information for web pages comes from a database, this is often obscured by the HTML format.

Advantages of Web Usage Mining

  • Government agencies are benefited from this technology to overcome terrorism.
  • The predictive capabilities of mining tools have helped identify various criminal activities.
  • Customer Relationship is being better understood by the company with the aid of these mining tools. It helps them to satisfy the needs of the customer faster and efficiently.

Disadvantages of Web Usage Mining

  • Privacy stands out as a major issue. Analyzing data for the benefit of customers is good. But using the same data for something else can be dangerous. Using it within the individual’s knowledge can pose a big threat to the company.
  • Having no high ethical standards in a data mining company, two or more attributes can be combined to get some personal information of the user which again is not respectable.

Advantages of Data Mining

  1. Marketing/Retails

To create models, marketing companies use data mining. This was based on history to forecast who will respond to new marketing campaigns such as direct mail, online marketing, etc. This means that marketers can sell profitable products to targeted customers.

  1. Finance/Banking

Since data extraction provides financial institutions with information on loans and credit reports, data can determine good or bad credits by creating a model for historical customers. It also helps banks detect fraudulent transactions by credit cards that protect a credit card owner.

  1. Researchers

Data mining can motivate researchers to accelerate when the method analysis the data. Therefore they can work more time on other projects. Shopping behaviors can be detected. Most of the time, you may experience new problems while designing specific shopping patterns. Therefore data mining is used to solve these problems. Mining methods can find all the information on these shopping patterns. This process also creates an area where all the unexpected shopping patterns are calculated. This data extraction can be beneficial when shopping patterns are identified.

  1. Determining Customer Groups

We are using data mining to respond from marketing campaigns to customers. It also provides information during the identification of customer groups. Some surveys can be used to begin these new customer groups. And these investigations are one of the forms of data mining.

  1. Increases Brand Loyalty

In marketing campaigns, mining techniques are used. This is to understand their own customers ‘ needs and habits. And from that, customers can also choose their brand’s clothes. Thus, you can definitely be self-reliant with the help of this technique. However, it provides possible information when it comes to decisions.

  1. Helps in Decision Making

People use these data mining techniques to help them make some decisions in marketing or business. Today, with the use of this technology, all information can be determined. Also, using such technology, one can decide precisely what is unknown and unexpected.

  1. Increase Company Revenue

Data mining is a process in which some kind of technology is involved. One must collect information on goods sold online; this eventually reduces product costs and services, which is one of the data mining benefits.

  1. To Predict Future Trends

All information factors are part of the working nature of the system. The data mining systems can also be obtained from these. They can help you predict future trends, and with the help of this technology, this is entirely possible. And people also adopt behavioral changes.

  1. Increases Website Optimization

We use data mining to find all kinds of unseen element information. And adding data mining helps you to optimize your website. Similarly, this data mining provides information that may use the technology of data mining.

  1. Importance of Web Mining in Business Intelligence

Web mining can be a great source of business intelligence to understand customers, drive sales, create new opportunities, and meet mission goals. Here are some of the ways through which Web Mining in Business Intelligence can be helpful to a company or business:

  1. Know your Customers Better

Web mining can help you to discover your customers’ key initiatives and their financial situation. It can also help you know what the CEO of your customer’s company is saying, as well as what your customers are saying and posting on online platforms.

  1. Learn More about your competitors

Staying ahead of competitors is key to the survival of any business. Thus, knowing your competitors better is important. With Web Mining in Business Intelligence, you can know what your competitors are doing, what they are selling, and whether they are doing anything new or unique.

  1. Find New Customers

Web mining can keep you updated about what is happening in the world, and let you know the best places to target your sales and reach new customers.

  1. Monitor People’s Sentiments about your Business

By knowing what people are saying about your business, you can identify potential customer-related issues and take the appropriate action to counter them before going viral. You can also track the effectiveness of your marketing campaigns.

Applications of Web Usage Mining

  1. Personalization of Web Content: The World Wide Web has a lot of information and is expanding very rapidly day by day. The big problem is that on an everyday basis the specific needs of people are increasing and they quite often don’t get that query result. So, a solution to this is web personalization. Web personalization may be defined as catering to the user’s need based on its navigational behavior tracking and interests. Web Personalization includes recommender systems, check-box customization, etc. Recommender systems are popular and are used by many companies.
  2. E-commerce: Web-usage Mining plays a very vital role in web-based companies. Since their ultimate focus is on Customer attraction, customer retention, cross-sales, etc. To build a strong relationship with the customer it is very necessary for the web-based company to rely on web usage mining where they can get a lot of insights about customers’ interests. Also, it tells the company about improving its web design in some aspects.
  3. Prefetching and Catching: Prefetching basically means loading data before it is required to decrease the time waiting for that data hence the term ‘prefetch’. All the results which we get from web usage mining can be used to produce prefetching and caching strategies which in turn can highly reduce the server response time.


In conclusion, we have seen the differences between web and data mining. They are both important ways of extracting data from the web.

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