Abstract
The most efficient way to convey human knowledge is through natural language text. In order to manage the exponential growth of digital data, it is high time to build a robust text information system. The system performs various techniques such as classification, clustering, summarization, etc. to organize the huge unstructured text data into well-defined forms. Text representation is the fundamental task in text mining and text retrieval. Just like a backbone gives structure to human body, text representation lays the foundation step for various other downstream tasks of Natural Language Processing (NLP), text mining and text retrieval. This paper concentrates on the analysis of various text representation models and also discusses major changing trends in textual data representation. This paper could be beneficial to those who wish to study and work on text data in NLP domain. The challenges and drawbacks of the existing text representation models are also discussed in this paper.
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Singh, K.N., Dorendro, A., Devi, H.M., Mahanta, A.K. (2021). Analysis of Changing Trends in Textual Data Representation. In: Santosh, K.C., Gawali, B. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2020. Communications in Computer and Information Science, vol 1380. Springer, Singapore. https://doi.org/10.1007/978-981-16-0507-9_21
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