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iWebMiner, a business located in Pennsylvania, specializes in scraping the screen content and mining the data from websites. We also help develop window scraping and web-based applications for customers.
With years of experience and expertise in web data mining and artificial intelligence, our senior developers have created the technology of web data mining and built a streamlined production line for screen scraping.
With these high-quality resources, we are able to mine any website, to provide complete and organized data, and to reduce the cost of operation.
In recent years, there has been an explosion of information available online.
As a result, it is necessary for users to have access to Web tools that can find,
track, and analyze these data sources. Web mining is the solution.
What is Web Mining?
Web mining is the extraction of patterns and information
from articles or activity on the World Wide Web. iWebMiner
utilizes web content mining, a process which extracts content from documents useful to clients.
As an automatic process, it runs efficiently and smoothly, guaranteeing organized and
complete data.
The content on a web page is visible to public and private groups of users. The data is accessible via the HTTP communication. Theoretically, any web page can be mined. However, the structure of web pages is drastically distinct. This means that the content of web pages is not machine-readable. In addition, some web pages are incorporated with a series of measurements that protect against web mining. These can include hidden dynamic variables, dynamic cookies, session cookies, limited bandwidth, log in systems, and SSL/TLS secure communications. All of these obstacles make it difficult to create a single tool that works for all web pages, especially for secure and dynamic web pages. We fully understand the characteristics of web pages, and we have designed and developed a web mining tool that overcomes all of a website's protective features. Our web data mining tool is flexible, adaptable, scaleable and web server-friendly. This allows us to scrape any content from any web page.
Technically, web mining consists of Web usage mining, Web structure mining, and Web content mining. Web mining allows you to look for patterns in data through content mining, structure mining, and usage mining. Web usage mining refers to the discovery of user access patterns from Web usage logs. Web usage mining is the application that uses data mining to analyze and discover interesting patterns of usage data on the web. Most graphs are involved in determining frequent traversal patterns or large reference sequences from physical layout, such as the most frequently visited paths in a Web site.
Web mining, when looked upon in data mining terms, can be said to have three operations of interests - clustering, associations, and sequential analysis. Recipient technologies that demand for user profiling and usage patterns include recommendation systems, Web analytics applications, application servers coupled with content management systems and fraud detectors. The improvement of electronic reference services, from the reference desk to cyberspace, strongly support the ongoing research interests of the web mining tools. Recipient technologies include user profiling, usage analysis, ontology extraction for the Semantic Web, intelligent search and recommendation systems based on user preferences, page content, and site semantics.
The technology aims to bring together various perspectives on Web mining and stress the synergy effects between Web usage mining, Web content mining and Web intelligence, and of Semantic Web Mining. It is also quite different from data mining because Web data are mainly semi-structured and/or unstructured, while data mining deals primarily with structured data. One possible approach is to personalize the web space -- create a system which responds to user queries by potentially aggregating information from several sources in a manner which is dependent on who the user is. It is possible to determine such information as the number of accesses to the server, the times or time intervals of visits as well as the domain names and the URLs of users of the Web server.
Most web content mining systems used wrappers to map documents to other data structures, but this is highly dependent on the the layout and formatting instructions inside web pages. The Web data mining technology solves half structure data pool model and half structure data model inquiry and the integrated question.
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