In internet billions amount of information published through no of ways like web pages, social media and website. Searching and analyzing these data is very complex task. Using partitioning algorithm for open source intelligence purpose optimal search can be implemented which help to convert unstructured data to structured data and also analysis and extraction the information significantly. In partitioning algorithm we use binary search technique. Each algorithm has its own advantages, limitations and shortcomings. Therefore, introducing novel and effective approaches for data clustering is an open and active research area. The binary search algorithm for data clustering that not only finds high quality clusters but also converges to the same solution in different runs. Open Source Intelligence (OSINT) aims at presenting valuable information based on publicly available data. As it might be expected, the Internet is a primary example of such data source. By applying text mining tools on a myriad of available services: online news, blogs, mailing lists, forums, portals, and a great amount of insight might be provided into almost any topic.

1. CLUO: WEB – SCALE TEXT MINING SYSTEM FOR OPEN SOURCE INTELLIGENCE PURPOSE COMPUTER SCIENCE 14 (1) 2013
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Text Mining Osint K – Means Algorithm Agglomerative Algorithm.