A Survey of two different Approaches for Named Entity Recognition.

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

Abstract

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.

References

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[3] Gowri Prasad, Fousiya KK, “Named Entity Recognition Approaches”, in International Conference on circuit, power, and computing technologies, 2015.
[4] K.U. Senevirathne, N.S. Attanayake, “Conditional Random Fields based named entity recognition for sinhala”, in IEEE 10th International conference on Industrial and information systems, ICIIS 2015, dec 18-20, 2015, Sri Lanka.
[5] Siham Boulaknadel, Meryem Talha, Driss Aboutajdine, “Amazighe named entity recognition using a rule based approach”, 2014.
Published
2018-04-15
How to Cite
Shah, V. (2018, April 15). A Survey of two different Approaches for Named Entity Recognition. ASIAN JOURNAL FOR CONVERGENCE IN TECHNOLOGY (AJCT ) -UGC LISTED, 4(I). Retrieved from http://asianssr.org/index.php/ajct/article/view/400
Section
Computer Science and Engineering