Web Document Clustering and Ranking using Tf-Idf based Apriori Approach

Understand

The dynamic web has increased exponentially over the past few years with more than thousands of documents related to a subject available to the user now.

• Most of the web documents are unstructured and not in an organized manner and hence user facing more difficult to find relevant documents.
• A more useful and efficient mechanism is combining clustering with ranking, where clustering can group the similar documents in one place and ranking can be applied to each cluster for viewing the top documents at the beginning..
• Besides the particular clustering algorithm, the different term weighting functions applied to the selected features to represent web document is a main aspect in clustering task.