Semantic agent based knowledge discovery from big data on the web

Abstract EN

The emergence of Big Data has begun from the fast-rapid growth of the Web resource on the internet.

The size of the Web becomes too massive, heterogeneous, and updated day by day, impacted by the networking‟s fast development, data collection capacity and data storage.

Discovering unknown knowledge is a big challenge due to the lack of relationships between data sets, making traditional web mining results almost unsatisfactory when the user have insufficient data parameters to search.

In this paper, we have suggested a unified semantic agent program to improve the knowledge discovery process from Big Data on the web using ontology.

The model extracts information from heterogeneous data sources, then defines a unified structure to store them that make it easily searchable, maximizing discovery and reporting for users.

The evaluation of the approach shows higher precision and recall, using ontology technique instead of a keyword based in the mining process.