Web Mining is the process of extracting the useful and relevant information from Web documents and services, Web contents, hyperlinks and server logs. This paper gives an overview of Web-Mining and major categories of Web-Mining. KEYWORDS: Web-Mining, Web Content Mining, Web Structure Mining, Web Usage
So in this case Web Usage Mining determines interesting usage patterns from Web data so as to understand and better serve the needs of Web-based applications. By the definition of Web usage mining we conclude that it is the procedure of removing useful information from server logs. Hence, it discovers sequential patterns of web files. 1.2.5 Web Content Mining Web content mining process is discovery of useful data, information and knowledge from Web page content or data or documents. Web data contents include text, image, audio, video, metadata and hyperlinks.
Abstract: Data mining is used to extract the information from the large dataset and used to predict patterns and behavior of an application. Data mining plays a chief role in the fields of e-commerce, healthcare sector, and agricultural sector. Agriculture is the prime occupation in India. Crop productivity mainly depends on weather conditions. Data mining is used in agriculture to predict crop productivity, water management, crop disease management, pesticide recommendation by using different algorithms.
Data mining itself is the process of extracting useful, interesting and previously unknown information from large sets of data. The success relies on the availability of high quality data and effective information sharing. The collection of digital information by governments, corporations, and individuals has created an environment that facilitates large-scale data mining and data analysis. Data collection and data mining by itself is not illegal because it maybe necessary for managing the process it’s being used for. The concern for the private citizen is what and how the data will be used and the security of the data.
Web crawlers are often used as resource discovery and retrieval tools for Web search engines such as Google. These search engines (e.g. Google, Bing, Yahoo) play an essential part in our life. Without them, it is difficult to imagine how people find information on Internet these days. Related
Web is widely known as the Internet. Internet is a medium through which information can be viewed, reviewed and used either in a positive or a negative way. As everyone has an access to the information, there is a threat of misusing the data or sources available. A person can modify anyone’s data leading to unauthorized access and huge loss or damage; hence there is a need to secure the system thereby preventing the increasing cybercrimes. Now the question arises how to verify whether the security provided is accurate, adequate and correct?
Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. B.2 Introduction The growing popularity and development of data mining technologies bring serious threat to the security of individual's
“Good feedback practice is not only about providing accessible and usable information that helps students improve their learning, but it is also about providing good information to teachers” (Nicol and Macfarlane, 2006, p. 214). Quality assessment and effective feedback have a strong impact in systemizing educational governance. In the same way, it can enable all learners to enhance their learning or leads to increase learning and teachers in their teaching. Some research evidence such as Nicol and Macfarlane –Dick (2006)
4.6 ADVANTAGES Data mining is present in many aspects of our daily lives, whether we realize it or not. It aects how we shop, work, and search for information, and can even in uence our leisure time, health, and well-being. So data mining is ubiquitous (or ever-present. Several of these examples also represent invisible data mining , in which smart soft- MITCOE, Pune. 18 Dept.