1. Odia text classification for sentiment analysis using K nearest neighbor.
- Author
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Das, Bishwa Ranjan, Sahoo, Rekhanjali, Singh, Dilip, and Bhoi, Prakash Chandra
- Subjects
SENTIMENT analysis ,EUCLIDEAN distance ,CLASSIFICATION ,NAIVE Bayes classification ,DATA modeling - Abstract
Text classification using K Nearest Neighbor, which locates the K closest matches in training data and uses the label of closest matches to forecast the class of the text. Euclidean distance is used to find the closet matchwhich is predict the class level. The technique Bag of Words is used to find numerical values from the document in terms of text representation. An annotated corpus in Odiabased on agriculture domain collected from ILCI, Govt. of India treated as training data and the representation of that text data for finding sentiment using the concept of the feature vector made from the entire document which we have collected. The calculation of the results using KNN with tf-idf is challenging for Odia text as it low resource language. This paper presents details of result analysis with thoroughly done by experiment. Evaluation of the model is focusedon speed of the transferring text data to the proposed model and getting high accuracy rate. The result of the testing data depends on good and bad features of the algorithm and suggests for how to improve feature iteration of the same model in future. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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