Bio-NER: Biomedical Named Entity Recognition using Rule-Based and Statistical Learners
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 12
Abstract
The purpose of extracting of Bio-Medical Entities is to recognize the particular entities, whether word or phrases, from the unstructured data contained in the text. This work proposes different approaches and methods, i.e. Machine Learning Hybrid Classification, Rule Based Non-tested Generalized Exemplars and Partial Decision Tree (PART) Learners for Bio-Medical Named Entity Recognition. The Prime objective is to consider, preferably, simple characteristics, such as, affixes and context. In addition, orthographic, Parts of Speech (POS) tags and N-grams are given secondary importance as for as their comparison with affixes and context is concerned. Further, for the very purpose of Bio-medical Diseased Named Recognition, proposal of Rule Based Classifiers along with the Statistical Machine Learning is given. Also, this paper proposes the blend of both preceding methods that jointly construct Hybrid Classification algorithm. Precision, Recall and F-measure – standard metrics- has been put into practice for the evaluation. The results prove that the technique used has far better performance results than the method used before - state-of-art Disease NER (Named Entity Recognition).
Authors and Affiliations
Pir Dino Soomro, Sanotsh Kumar, Banbhrani Banbhrani, Arsalan Ali Shaikh, Hans Raj
Keywords
Related Articles
- EP ID EP258315
- DOI 10.14569/IJACSA.2017.081220
- Views 97
- Downloads 0
CNNSFR: A Convolutional Neural Network System for Face Detection and Recognition
In recent years, face recognition has become more and more appreciated and considered as one of the most promising applications in the field of image analysis. However, the existing models have a high level of complexity...
Electronically Reconfigurable Two-Stage Schiffman Phase Shifter for Ku Band Beam Steering Applications
An electronically reconfigurable phase shifter using two Schiffman sections is performed for beam steering applications in Ku band. The proposed phase shifter consists of only two cascaded coupled-line sections with the...
A Prototype Student Advising Expert System Supported with an Object-Oriented Database
Using intelligent computer systems technology to support the academic advising process offers many advantages over the traditional student advising. The objective of this research is to develop a prototype student advisi...
Performance Enhancement of Scheduling Algorithm in Heterogeneous Distributed Computing Systems
Efficient task scheduling is essential for obtaining high performance in heterogeneous distributed computing systems. Some algorithms have been proposed for both homogeneous and heterogeneous distributed computing system...
Cloud Computing: Pricing Model
Cloud computing is the elemental aspect for online security of computing resources. It helps on-demand dividing of resources and cost between a major number of end users. It provides end users to process, manage, and sto...