Web mining is a fast growing investigation area which consists of Web usage mining, Web structure mining,
and Web content mining. Web usage mining refers to the finding of client access patterns from Web usage logs. Web
structure mining discovers useful knowledge from the construction of hyperlinks. Web content mining aspires to
extract useful information or knowledge from web page contents. Web content mining is associated but unusual from
data mining and text mining. It is linked to data mining because a lot of data mining techniques can be practical in Web
content mining. It is interconnected to text mining because much of the web contents are texts. Nevertheless, it is also
quite dissimilar from data mining because Web data are principally semi-structured or unstructured, even as data
mining contract primarily with structured data. Web content mining is also different from text mining because of the
semi-structure environment of the Web, while text mining focuses on unstructured texts. Web content mining thus
needs creative purpose of data mining or text mining techniques and its own exceptional approaches. In the earlier
period, there was a speedy expansion of behavior in the Web content mining area. This is not amazing because of the
extraordinary growth of the Web contents and noteworthy economic benefit of such mining. Yet, owing to the
heterogeneity and requires of construction of Web data, automated detection of unexpected knowledge data still
present many tough research problems.