TextSter: An All in One Text Processing Website
Aviroop Paul, Pratyusa Mukherjee, Swati Das, Anushka Dash, Meghna · 2024
Comprehensive text analysis websites have revolutionized text data management by providing users with powerful tools such as text summarizers, generators, emotion analyzers, and dictionaries. These tools employ sophisticated algorithms to process text input and extract vital details and insights. Text generators produce original content based on user-defined criteria, while text summarizers provide concise summaries of lengthy publications. Dictionaries assist in defining difficult terminology and determining emotional tones. We present TextSter, a user-friendly website, that combines these natural language processing features. Users can generate contextually relevant content, perform sentiment analysis, search word definitions, and quickly summarize large documents. By comparing various models and approaches for each task, we integrated the best-performing techniques into our comprehensive Natural Language Processing (NLP) tool. Future research on this aims to develop advanced algorithms for capturing linguistic subtleties, integrating Artificial Intelligence (AI) and Machine Learning (ML) systems, and creating specialized NLP tools for specific industries. Our study demonstrates the versatility of integrating the four NLP technologies, enabling effective text data analysis and management.