Title :
AGNER: Entity tagger in agriculture domain
Author :
Biswas, Payai ; Sharan, Aditi ; Kumar, Ashish
Author_Institution :
Jawaharlal Nehru Univ., New Delhi, India
Abstract :
Named Entity recognition is a challenging problem in the area of text mining. Most of the work in this field has been done in open domain. However the notion of named entity changes when we move from open domain to domain specific NER. For domain specific NER only the biomedical domain has been taken in consideration. While in Agriculture domain no significant work has been done. Thus NER for Agriculture Domain becomes an interesting research problem. In this work we have taken a step to develop a NER for agriculture domain namely AGNER. We have used linguistic and domain specific knowledge base for developing the system. We have used Agrovoc hierarchy for labeling the terms with the appropriate tags. Two layers of tags namely: <;Fine grain> and <;Coarse Grain> has been used to label each agriculture terms in the dataset.
Keywords :
agriculture; data mining; knowledge based systems; text analysis; AGNER; Agrovoc hierarchy; agriculture domain; agriculture term; biomedical domain; domain specific NER; domain specific knowledge base; entity tagger; linguistic; named entity recognition; text mining; Decision support systems; Handheld computers; Named Entity; agriculture term; coarse grain; fine grain; non-agriculture term; noun; token;
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-9-3805-4415-1