Web data mining and data collection is critical process for many business and market research firms today. Conventional Web data mining techniques involve search engines like Google, Yahoo, AOL, etc and keyword, directory and topic-based searches. Since the Web’s existing structure cannot provide high-quality, definite and intelligent information, systematic web data mining may help you get desired business intelligence and relevant data.
Factors that affect the effectiveness of keyword-based searches include:
• Use of general or broad keywords on search engines result in millions of web pages, many of which are totally irrelevant.
• Similar or multi-variant keyword semantics my return ambiguous results. For an instant word panther could be an animal, sports accessory or movie name.
• It is quite possible that you may miss many highly relevant web pages that do not directly include the searched keyword.
The most important factor that prohibits deep web access is the effectiveness of search engine crawlers. Modern search engine crawlers or bot can not access the entire web due to bandwidth limitations. There are thousands of internet databases that can offer high-quality, editor scanned and well-maintained information, but are not accessed by the crawlers.
Almost all search engines have limited options for keyword query combination. For example Google and Yahoo provide option like phrase match or exact match to limit search results. It demands for more efforts and time to get most relevant information. Since human behavior and choices change over time, a web page needs to be updated more frequently to reflect these trends. Also, there is limited space for multi-dimensional web data mining since existing information search rely heavily on keyword-based indices, not the real data.
Above mentioned limitations and challenges have resulted in a quest for efficiently and effectively discover and use Web resources. Send us any of your queries regarding Web Data mining processes to explore the topic in more detail.