Acquiring seasonal/agricultural knowledge from social media

Abstract

Agricultural knowledge depends on seasonally changing conditions such as climate, harmful insects, etc. In this respect, farmers tend to be interested in seasonal knowledge rather than the static principle. To acquire such agricultural knowledge, we propose a method to acquire seasonal knowledge from ongoing posts in the social media. The experimental results shows that the agricultural knowledge can be extracted in the form of chained structures, each of which denotes a set of seasonal knowledge. We also developed a prototype of dialogue robot that provides agricultural knowledge based on the chained structure database. The characteristics of the robot is its ability to reply with seasonally changing knowledge.