In this paper, we have tried to identify the prominent factors of Rice production of all the three seasons of the year (Aus, Aman, and Boro) by applying K-Means clustering on climate and soil variables' data warehoused using Fact Constellation schema. For the clustering, the popular machine-learning tool Weka was used whose visualization feature was principally useful to determine the patterns, dependencies, and relationships of rice yield on different climate and soil factors of rice production.

Communication is the most common but an intricate activity that we perform every day. Sender sends message, discussions, greetings, gestures, emotics and texts through numerous channels, (e.g. e-mail, messengers, social networks and so on) intending the receiver to understand. The means of personal or group communication has been radically changed over last decade. Geographical, ethnicity, nationality, race, religion are no more hindrance for the sake of social communication. Forms of communication, event, gathering, greetings almost have altered into virtual society. But this hi-tech society has still yet enough room to strengthen its semantic nature. We have made an endeavor to conglomerate the socio-psycho-technical aspect of so-called social networks which could be more realistic, logically inferable and convincible towards people to claim its analogousness with real society. Our devised SN is able to eliminate some weird problems that we face in current SNs, imperfect relationship assignment policies and possibility of data interference among desired and intruder groups.