Fine-Grained Knowledge in Agriculture System

Shilpa Lekurwale, Rakesh Shirsath


For most of the people, web interaction is a very common
phase to acquire information. It is possible that in a combined
environment, more than one person may try to obtain similar
information in one domain. One person may like to solve a
problem using an unfamiliar Apache Tomcat which he had
studied by another person before. Connecting and then
sharing with that persons will be more beneficial to get there
learned knowledge. Fine-grained knowledge sharing is
proposed for this combined environment. The system is
proposed to classify the surfed data into clusters and
summarize the details in fine grained details. For any system
the efficiency depends upon the surfing. The framework of
proposed work includes: (1) Data which is surfed, clustered
into tasks. (2)Then task is mined in fine grained output. To get
proper result, the search method is applied to the output
(mined results).The concept of Data Mining in fine grained
knowledge is combined with the information gathering and
classification to produce efficient data searching technique in
agriculture system.

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