Text grouping: a comprehensive guide

Padarabinda Palai, Kaushiki Agrawal, Debani Prasad Mishra, Surender Reddy Salkuti


Text keywords have huge variance and to bridge the gap between the country business segment which provides negligible information and the keywords that have a huge longtail it is imperative for us to categorize the queries that provide a middle ground and also serve a few other purposes. The paper will present those in-depth. Query categorization falls into the segment of 'Multi-Class Classification' in the domain of natural language processing (NLP). However, business requirements require the implementation of any technique that could provide as accurate results as possible. So, to solve this problem the paper discusses an amalgamation of approaches like TF-IDF (term frequency-inverse document frequency), neural networks, cosine similarity, transformers-all of which fix specific issues.


Neural networks; Natural language processing; Query categorisation; Term frequency-inverse document frequency; Transformers

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DOI: http://doi.org/10.11591/ijai.v12.i3.pp1476-1483


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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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