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Difference between data mining and web mining?
Data mining is the procedure of exploration and analysis of huge quantities of data to find meaningful patterns and rules. On the other hand, web mining defines the process of using data mining techniques to extract useful data patterns and trends from web-based records and services, server logs, and hyperlinks.
Read this article to learn more about Data Mining and Web Mining and how they are different from each other.
What is Data Mining?
Data mining is the process of discovering meaningful new correlations, patterns, and trends by shifting through a large amount of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. It is the analysis of observational datasets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and beneficial to the data owner.
Data mining is the process of selection, exploration, and modeling of large quantities of data to discover regularities or relations that are at first unknown to obtain clear and useful results for the owner of the database. Data mining is the procedure of exploration and analysis by automatic or semi-automatic defines of huge quantities of data to find meaningful patterns and rules.
Data Mining is similar to Data Science. It is carried out by a person, in a specific situation, on a particular data set, with an objective. This process includes various types of services such as text mining, web mining, audio and video mining, pictorial data mining, and social media mining. It is completed through software that is simple or hugely specific.
By outsourcing data mining, all the work can be completed quicker with low operation costs. Specialized firms can also use new technologies to set data that is impossible to situate manually. There are tons of information available on various platforms, but very little knowledge is accessible.
The biggest challenge is to analyze the data to extract important information that can be used to solve a problem or for company development. There are many powerful instruments and techniques available to mine data and find better insight from it.
What is Web Mining?
Web mining defines the process of using data mining techniques to extract beneficial patterns trends and data generally with the help of the web by dealing with it from web-based records and services, server logs, and hyperlinks. The main goal of web mining is to find the designs in web data by collecting and analyzing data to get important insights.
Web mining can broadly be viewed as the application of adapted data mining techniques to the internet, whereas data mining is represented as the application of the algorithm to find patterns on mostly structured data fixed into a knowledge discovery process.
Web mining has distinctive features to offer a set of multiple data types. The web has several aspects that yield multiple approaches for the mining process, including web pages including text, web pages are connected via hyperlinks, and user activity can be monitored via web server logs.
Difference between Data Mining and Web Mining
The following table highlights all the major differences between data mining and web mining −
S.No. |
Data Mining |
Web Mining |
|---|---|---|
1. |
Data mining is the process of discovering meaningful new correlations, patterns, and trends by shifting through a large amount of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. |
Web mining defines the process of using data mining techniques to extract beneficial patterns trends and data generally with the help of the web by dealing with it from web-based records and services, server logs, and hyperlinks. |
2. |
The main goal of data mining is the analysis of observational datasets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and beneficial to the data owner. |
The main goal of web mining is to find the designs in web data by collecting and analyzing data to get important insights. |
3. |
It is the process of selection, exploration, and modeling of large quantities of data to discover regularities or relations that are at first unknown to obtain clear and useful results for the owner of the database. |
Web mining can broadly be viewed as the application of adapted data mining techniques to the internet. |
4. |
This process includes various types of services such as text mining, web mining, audio and video mining, pictorial data mining, and social media mining. |
The web has several aspects that yield multiple approaches for the mining process, including web pages including text, web pages are connected via hyperlinks, and user activity can be monitored via web server logs. |
5. |
Data mining uses business intelligent applications that includes information to improve business activities. |
Web mining uses data analytics for medication of raw data into a meaningful format. |
6. |
The target users of data mining include data engineers and data scientists. |
The target users of web mining include data analysts or web analysts. |
7. |
Data mining uses tools like machine learning. |
Web mining uses tools like PageRank, Apache logs, Scrapy, etc. |
8. |
For decision-making process, many organizations use data mining results. |
Web mining is significant for pulling the existing data mining process. |
Conclusion
To conclude, the main objective of data mining is to analyze observational datasets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and beneficial to the data owner. In contrast, the primary objective of web mining is to find the designs in web data by collecting and analyzing data to get important insights.
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