Using librarian techniques in automatic text summarization for information retrieval
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Automatic Text Summarization Using a Machine Learning Approach
SBIA '02 Proceedings of the 16th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Similarity measures for short segments of text
ECIR'07 Proceedings of the 29th European conference on IR research
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Climate change can directly impact agriculture. Failure in different aspects of agriculture due to climate change and other influencing factors, are extremely rampant in several agrarian economies, most of which go unnoticed. In this paper, we describe the design of a system that mines disparate information sources on the Web to automatically summarize important climatic and agricultural trends for any specific location and construct a location-specific climatic and agricultural information portal. We have evaluated the system across 605 different districts in India. The results revealed a pan-India scenario of different problem affected areas. The key findings from this work include, around 64.58% of the districts of India suffer from soil related issues and 76.02% have water related problems. We have also manually validated the authenticity of our information sources and validated our summarized results for specific locations with findings in reputed journals and authoritative sources.