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Agriculture is a key component in any country's development. Domain-specificknowledge resources serve to gain insight into the domain. Existing knowledgeresources such as AGROVOC and NAL Thesaurus are developed and maintained by thedomain experts. Population of terms into these knowledge resources can beautomated by using automatic term extraction tools for processing unstructuredagricultural text. Automatic term extraction is also a key component in manysemantic web applications, such as ontology creation, recommendation systems,sentiment classification, query expansion among others. The primary goal of anautomatic term extraction system is to maximize the number of valid terms andminimize the number of invalid terms extracted from the input set of documents.Despite its importance in various applications, the availability of onlinetools for the said purpose is rather limited. Moreover, the performance of themost popular ones among them varies significantly. As a consequence, selectionof the right term extraction tool is perceived as a serious problem fordifferent knowledge-based applications. This paper presents an analysis ofthree commonly used term extraction tools, viz. RAKE, TerMine, TermRaider andcompares their performance in terms of precision and recall, vis-a-vis RENT, amore recent term extractor developed by these authors for agriculture domain.

Automatic Extraction of Agriculture Terms from Domain Text: A Survey of Tools and Techniques