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Articles on Trending Technologies
Technical articles with clear explanations and examples
What are the trends in data mining?
The trends in data mining are as follows −Application exploration − Early data mining applications targeted generally on helping businesses gain a competitive edge. The exploration of data mining for businesses continues to expand as e-commerce and e-marketing have become mainstream components of the retail market.Data mining is increasingly used for the exploration of applications in several areas, including financial analysis, telecommunications, biomedicine, and science. Emerging software areas contain data mining for counterterrorism (including and beyond intrusion detection) and mobile (wireless) data mining. As generic data mining systems can have limitations in dealing with application-specific issues, it can view a ...
Read MoreWhat are the features of data mining?
There are various features of data mining that are as follows −Data types − Most data mining systems that are accessible in the industry handle formatted, record-based, relational-like data with statistical, categorical, and symbolic attributes. The data can be in the form of ASCII text, relational database data, or data warehouse data. It is essential to test what exact format(s) each system it is treating can handle.Some types of data or applications can require specialized algorithms to search for patterns, and so their requirements cannot be managed by off-the-shelf, generic data mining systems. Rather than, specialized data mining systems can ...
Read MoreWhich of the following areas data mining technology can be applied?
The following are areas in which data mining technology can be used or created for intrusion detection which are as follows −Development of data mining algorithms for intrusion detection − Data mining algorithms can be used for misuse detection and anomaly detection. In misuse detection, training information is labeled as either “normal” or “intrusion.” A classifier can then be changed to detect known intrusions.There is multiple research in this area that has contained the application of classification algorithms, association rule mining, and cost-sensitive modeling. Anomaly detection constructs models of normal behavior and automatically detects significant deviations from it and supervised ...
Read MoreHow can intrusion be detected?
The security of our computer systems and information is at constant risk. The extensive growth of the web and increasing accessibility of tools and tricks for intruding and attacking networks have prompted intrusion detection to become an important element of network administration. An intrusion can be represented as any set of events that threaten the integrity, confidentiality, or availability of a network resource (including user accounts, file systems, system kernels, etc).Some commercial intrusion detection systems are limiting and do not support a whole solution. Such systems generally employ misuse detection approaches. Misuse detection searches for designs of program or user ...
Read MoreWhat are the aspects of data mining for Biological Data Analysis?
There are the following aspects of data mining for biological data analysis which are as follows −Semantic integration of heterogeneous, distributed genomic and proteomic databases − Genomic and proteomic data sets are generated at multiple labs and by various methods. They are distributed, heterogeneous, and of a wide variety. The semantic integration of such data is important to the cross-site analysis of biological records.Furthermore, it is essential to find correct linkages among research literature and their related biological entities. Such integration and linkage analysis can support the systematic and coordinated analysis of genome and biological records. This has promoted the ...
Read MoreWhat is the role of data mining for the Telecommunication Industry?
The telecommunication industry has quickly evolved from providing local and long-distance telephone services to providing several other comprehensive communication services, such as fax, pager, cellular phone, web messenger, images, e-mail, computer and Web data transmission, and several data traffic.The integration of telecommunication, computer network, the Internet, and several other means of communication and computing is also underway. Furthermore, with the deregulation of the telecommunication market in several countries and the development of new computer and communication technologies, the telecommunication industry is rapidly expanding and hugely competitive.This makes a huge demand for data mining in order to support understanding the business ...
Read MoreWhat is the role of data mining in the retail industry?
The retail industry is a major application area for data mining because it collects huge amounts of records on sales, users shopping history, goods transportation, consumption, and service. The quantity of data collected continues to expand promptly, especially because of the increasing ease, accessibility, and popularity of business conducted on the internet, or e-commerce.Today, multiple stores also have websites where users can create purchases online. Some businesses, including Amazon.com (www.amazon.com), exist solely online, without any brick-and-mortar (i.e., physical) store areas. Retail data support a rich source for data mining.Retail data mining can help identify user buying behaviors, find user shopping ...
Read MoreHow data mining can help financial data analysis?
Financial data collected in the banking and financial market are relatively done, reliable, and of huge quality, which supports systematic data analysis and data mining. Therefore it can present a few typical cases which are as follows −Design and construction of data warehouses for multidimensional data analysis and data mining − Data warehouses are required to be constructed for banking and financial records. Multidimensional data analysis methods must be used to analyze the general features of such data.For instance, one can like to view the debt and revenue changes by month, by region, by sector, and by several elements, along ...
Read MoreComparison of different Life Cycle Models
The Classical Waterfall ModelThe Classical Waterfall Model is the foundation upon which all other life cycle models are built. It's a fantastic model. The Classical Waterfall model, on the other hand, cannot be employed in real-world project development because it lacks a method for correcting faults that occur during one of the stages but are discovered afterward. The introduction of feedback pathways in the Iterative Waterfall model solves this issue.Advantages of the Classical Waterfall ModelThe waterfall model is an idealized software development approach. Because it is so basic, it may serve as a foundation for different software development life cycle ...
Read MoreEnd-to-End Testing Tutorial: What is E2E Testing with Example
End-to-End TestingEnd-to-End testing is a software testing approach that verifies the complete software, including its interaction with external interfaces, from beginning to end. End-to-end testing examines the entire software for dependencies, data integrity, and connectivity with other systems, interfaces, and databases in order to simulate a complete production environment.It checks batch/data processing from various upstream/downstream systems in addition to the software system. As a result, the term "End-to- End" was coined. End-to-end testing is normally done after functional and system testing has been completed. It simulates real-time conditions by using real-world data and a test environment. Chain testing is another ...
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