By 
Web data mining and data collection is a critical process for many business and market research companies today. Conventional web data mining techniques involve search engines like Google, Yahoo, AOL, etc. and searches based on keywords, directories and topics. Since the existing structure of the Web cannot provide high-quality, intelligent, defined information, systematic web data mining can help you get the desired business intelligence and relevant data.
Factors that affect the effectiveness of keyword-based searches include:
• Using general or broad keywords in search engines generates millions of web pages, many of which are totally irrelevant.
• The semantics of similar keywords or multiple variants can lead to ambiguous results. For a moment, the word panther could be an animal, a sports accessory or the name of a movie.
• It is quite possible that you will miss many highly relevant web pages that do not directly include the searched keyword.
The biggest factor prohibiting access to the deep web is the effectiveness of search engine crawlers. Modern search engine crawlers or bots cannot access the entire web due to bandwidth limitations. There are thousands of Internet databases that may offer high-quality, publisher-scanned, well-maintained information, but are not accessed by crawlers.
Almost all search engines have limited options for the combination of keyword queries. For example, Google and Yahoo offer options like phrase match or exact match to limit search results. It requires more efforts and time to obtain the most relevant information. Since human behavior and choices change over time, a web page needs to be updated more frequently to reflect these trends. Additionally, there is limited room for multidimensional web data mining, as existing information search relies heavily on keyword-based indexes, not actual data.
The limitations and challenges mentioned above have resulted in a quest to efficiently and effectively discover and use web resources. Send us any of your queries about web data mining processes to explore the topic in more detail.