A Survey of two different Approaches for Named Entity Recognition.

  • Vijeta Shah


Named Entity Recognition[NER] refers to a data extraction task that is responsible for finding, storing and sorting textual content into pre-defined categories such as the name of a person, organizations, locations, expression of time, quantities, monetary values, and percentages. Named Entity Recognition can be implemented using two different approaches such as Rule Based Approach and Statistical Based Approach. This Project does a comparative study of these two approaches on various types of inputs on the named entities like name of person, organization, and location and analyzes the outcome on the basis of parameters such as Recall, Precision, and F-Measure and determines whether the Rule Based Approach or the Statistical Based Approach should be implemented for better performance and efficiency in Named Entity Recognition.

Keywords: Named Entity Recognition, ANNIE, CRF, Recall, Precision, F-Measure.


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How to Cite
Shah, V. (2018). A Survey of two different Approaches for Named Entity Recognition. Asian Journal For Convergence In Technology (Founded by ISB &M School of Technology )), 4(I). https://doi.org/10.33130/asian journals.v4iI.400
Computer Science and Engineering