Automated Annotation System (AAS) Based on Probabilistic Clustering Algorithms

External remarks such as comments, notes, explanations, tags etc. are called annotation. Information can be extracted easily from a document or a portion of a document or a webpage if annotation are added to the artifacts. Metadata is defined as the data related to a webpage and it is in machine readable format which normal humans cant understand. . A common approach to annotation is collaborative annotation. In collaborative annotation user creates tags to annotate a document or webpage. These labels enables to organize and index the document or webpage. Adding s to a document or webpage is called Tagging, which requires significant amount of work as the resources varies from webpages, images and videos. This research papers suggests and propose a new system called Automated Annotation System (AAS, which uses K-Means and Distributed Hash Table (DHT) algorithms related to probabilistic clustering to automatically create the attribute or annotation documents or webpages using metadata. This is an efficient approach to instead of processing the metadata manually or analyzing the document text to come up with annotation.