Abstract
In the daily life, everybody keeps on using Internet after the waking up that includes the communication among different people of this world. On one side, Internet has made everyone’s life very convenient and provides many facilities that can be used on social networking sites such as chat, messaging, comment, and blogging. This way everyone keeps on sharing the personal data at different places like Web sites, chats, social media. The text mining can be defined as the process of finding useful information from the given text. There exist various methods that remain helpful in analyzing texts and extracting the information but these often suffer from various complexities. Also, theoretically, it is quite difficult to analyze and extract the information from these raw data. This paper presents an Effective feed forward artificial neural network (FP-ANN) for text mining that generates different textual patterns from several resources and provides results very precisely with lesser computation time, lower cost, and overhead. FP-ANN approach calculates the hash label and discovers importance between inputs for text mining.
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Tamrakar, A., Mewada, P., Gubrele, P., Prasad, R., Saurabh, P. (2020). An ANN-Based Text Mining Approach Over Hash Tag and Blogging Text Data. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1057. Springer, Singapore. https://doi.org/10.1007/978-981-15-0184-5_35
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DOI: https://doi.org/10.1007/978-981-15-0184-5_35
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