Web Data Mining Is Used In Business Intelligence Infrastructure And Process Challenges

Today, the World Wide Web static and dynamic web HTML

, PHP and ASP programming languages and flooded with billions of created pages. Web data mining, offering a lush playground is a great source of information. Data stored on the web in various sizes and are dynamic in nature, it is an important finding, and processing and unstructured information available on the web is a challenge.

The complexity of a web page complexity is much greater than a traditional text document. Lack of uniformity and standardization of traditional books on Internet web pages and text documents are very simple in their stability. Furthermore, their limited capacity all WebPages very inefficient data mining with the search engines cannot index makes.

In addition, the Internet is a very dynamic knowledge resources and growing at a rapid pace. Sports, news, finance and corporate sites to update their websites on an hourly or daily. Today web interests of different profiles, and access to millions of users reached purposes.

It is important to note that only a small portion of the web has really useful information. There are three common ways that a user takes to access information stored on the internet:

Random surfing the web after a large number of hyperlinks. Query search engines - Google or Yahoo to search for relevant documents (questions specific keywords of interest in the search box)

Using the Web as an effective means of efficient data mining and knowledge discovery, researchers have developed technology to easily extract the relevant data, easily and cost effectively.

Data mining techniques for predictive analysis, automated extraction of hidden information from large databases are defined.

Data mining algorithms and mathematical software integrated with the use of statistical techniques. The final product is an easy to use software package that can be used by non-mathematicians to effectively analyze data. Data mining, market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, fraud detection, site personalization, e - commerce, healthcare, customer relationship management, financial services and telecommunications used in many applications such as.

Business intelligence, data mining, is market research, industry research, and competitive analysis. The direct marketing, e - commerce, customer relationship management, health, oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities to the main application.

Business Intelligence is a broad field of decision-making as a tool that uses data mining. In fact, the use of BI data in a data mining application makes more relevant. Text mining, web mining, social networks, data mining, relational databases, pictorial data mining, audio and video data mining, data mining, business intelligence applications that are used: there are many types of data mining

Some data mining tools are used in BI: decision trees, information, probability, probability density functions, Gaussian, maximum likelihood estimation, Gaussian Braves classification, cross-validation, neural networks, instance-based learning / case basis / memory based / non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, k-means and hierarchical clustering, Markov models, and so on.

by: Ian Miles

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