Web Content Mining – Mining Text

Web content mining, also known as text mining, is generally the second step in Web data mining. Content mining is the scanning and mining of text, pictures and graphs of a Web page to determine the relevance of the content to the search query. This scanning is completed after the clustering of web pages through structure mining and provides the results based upon the level of relevance to the suggested query. With the massive amount of information that is available on the World Wide Web, content mining provides the results lists to search engines in order of highest relevance to the keywords in the query.

Text mining is directed toward specific information provided by the customer search information in search engines. This allows for the scanning of the entire Web to retrieve the cluster content triggering the scanning of specific Web pages within those clusters. The results are pages relayed to the search engines through the highest level of relevance to the lowest. Though, the search engines have the ability to provide links to Web pages by the thousands in relation to the search content, this type of web mining enables the reduction of irrelevant information.

Web text mining is very effective when used in relation to a content database dealing with specific topics. For example online universities use a library system to recall articles related to their general areas of study. This specific content database enables to pull only the information within those subjects, providing the most specific results of search queries in search engines. This allowance of only the most relevant information being provided gives a higher quality of results. This increase of productivity is due directly to use of content mining of text and visuals.

The main uses for this type of data mining are to gather, categorize, organize and provide the best possible information available on the WWW to the user requesting the information. This tool is imperative to scanning the many HTML documents, images, and text provided on Web pages. The resulting information is provided to the search engines in order of relevance giving more productive results of each search.

Web content categorization with a content database is the most important tool to the efficient use of search engines. A customer requesting information on a particular subject or item would otherwise have to search through thousands of results to find the most relevant information to his query. Thousands of results through use of mining text are reduced by this step. This eliminates the frustration and improves the navigation of information on the Web.

Business uses of content mining allow for the information provided on their sites to be structured in a relevance-order site map. This allows for a customer of the Web site to access specific information without having to search the entire site. With the use of this type of mining, data remains available through order of relativity to the query, thus providing productive marketing.
Used as a marketing tool this provides additional traffic to the Web pages of a company’s site based on the amount of keyword relevance the pages offer to general searches.
As the second section of data mining, text mining is useful to improve the productive uses of mining for businesses, Web designers, and search engines operations. Organization, categorization, and gathering of the information provided by the WWW becomes easier and produces results that are more productive through the use of this type of mining.

In short, the ability to conduct Web content mining allows results of search engines to maximize the flow of customer clicks to a Web site, or particular Web pages of the site, to be accessed numerous times in relevance to search queries. The clustering and organization of Web content in a content database enables effective navigation of the pages by the customer and search engines. Images, content, formats and Web structure are examined to produce a higher quality of information to the user based upon the requests made. Businesses can maximize the use of this text mining to improve marketing of their sites as well as the products they offer.