Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.

Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

Data Mining As a Process

The data mining process is also known as knowledge discovery. It can be defined as the process of analyzing data from different perspectives and then summarizing the data into useful information in order to improve the revenue and cut the costs. The process enables categorization of data and the summary of the relationships is identified. When viewed in technical terms, the process can be defined as finding correlations or patterns in large relational databases. In this article, we look at how data mining works its innovations, the needed technological infrastructures and the tools such as phone validation.

Data mining is a relatively new term used in the data collection field. The process is very old but has evolved over the time. Companies have been able to use computers to shift over the large amounts of data for many years. The process has been used widely by the marketing firms in conducting market research. Through analysis, it is possible to define the regularity of customers shopping. How the items are bought. It is also possible to collect information needed for the establishment of revenue increase platform. Nowadays, what aides the process is the affordable and easy disk storage, computer processing power and applications developed.

Data extraction is commonly used by the companies that are after maintaining a stronger customer focus no matter where they are engaged. Most companies are engaged in retail, marketing, finance or communication. Through this process, it is possible to determine the different relationships between the varying factors. The varying factors include staffing, product positioning, pricing, social demographics, and market competition.

A data-mining program can be used. It is important note that the data mining applications vary in types. Some of the types include machine learning, statistical, and neural networks. The program is interested in any of the following four types of relationships: clusters (in this case the data is grouped in relation to the consumer preferences or logical relationships), classes (in this the data is stored and finds its use in the location of data in the per-determined groups), sequential patterns (in this case the data is used to estimate the behavioral patterns and patterns), and associations (data is used to identify associations).

In knowledge discovery, there are different levels of data analysis and they include genetic algorithms, artificial neural networks, nearest neighbor method, data visualization, decision trees, and rule induction. The level of analysis used depends on the data that is visualized and the output needed.

Nowadays, data extraction programs are readily available in different sizes from PC platforms, mainframe, and client/server. In the enterprise-wide uses, size ranges from the 10 GB to more than 11 TB. It is important to note that two crucial technological drivers are needed and are query complexity and, database size. When more data is needed to be processed and maintained, then a more powerful system is needed that can handle complex and greater queries.

With the emergence of professional data mining companies, the costs associated with process such as web data extraction, web scraping, web crawling and web data mining have greatly being made affordable.

Source:http://ezinearticles.com/?Data-Mining-As-a-Process&id=7181033

ScrapeDefender Launches Cloud-Based Anti-Scraping Solution To Protect Web Sites From Content Theft

ScrapeDefender launched today a new cloud-based anti-scraping monitoring solution that identifies and blocks suspicious activity to protect websites against content theft from mass scraping. The product provides triple protection levels against web scraping in the areas of vulnerability scanning, monitoring and security.

ScrapeDefender estimates that losses from web scraping content theft are close to $5 billion annually. According to a recent industry study, malicious non-human-based bot traffic now represents 30% of all website visits. Scrapers routinely target online marketplaces including financial, travel, media, real estate, and consumer-product arenas, stealing valuable information such as pricing and listing data.

ScrapeDefender stops website scraping by identifying and alerting site owners about suspicious activity in near real time. The monitoring system uses intrusion detection-based algorithms and patented technology to analyze network activity for both human and bot-like activity. It was designed from the ground up to work passively with web servers so that the underlying business is not impeded in any way. ScrapeDefender does not require any DNS changes or new hardware.

"Web scraping is growing at an alarming rate and if left unchecked, it is just a matter of time until all sites with useful content will be targeted by competitors harvesting data," said Robert Kane, CEO of ScrapeDefender. "We provide the only solution that scans, monitors and protects websites against suspicious scraping activity, in a way that isn't intrusive."

Irv Chasen, a board member at Bondview, the largest free provider of municipal bond data, said, "Our business is built on providing accurate municipal bond pricing data and related information to professional and retail investors. If competitors are scraping our information and then using it to gain an advantage, it creates a challenging business problem for us. With ScrapeDefender we can easily monitor and stop any suspicious scraping. Their support team made it easy for us to stay proactive and protect our website content."

ScrapeDefender is available as a 24 X 7 managed service or can be customer controlled. Customers are assigned a ScrapeDefender support staff member to help monitor network activity and alerts are automatically sent when suspicious activity is identified. Today's announcement extends ScrapeDefender's scanner, which was introduced in 2011 and remains the only anti-scraping assessment tool on the market that singles out web scraping vulnerabilities.

The ScrapeDefender Suite is available now at www.scrapedefender.com, starting at $79 per month for one domain.

About ScrapeDefender

ScrapeDefender was created by a team of computer security and web content experts with 20 years of experience working at leading organizations such as RSA Security, Goldman Sachs and Getty Images. Our web anti-scraping experts can secure your website to ensure that unauthorized content usage is identified and blocked.

Source: http://www.darkreading.com/vulnerability/scrapedefender-launches-cloud-based-anti/240165737