Text Categorization: A Lazy Learning-Based Approach

Autor:	Kaushik Roy, Himadri Mukherjee, Sk Md Obaidullah, Ankita Dhar, K. C. Santosh, Niladri Sekhar Dash
Rok vydání:	2021
Předmět:	Text categorization Lazy learning Computer science business.industry Representation (systemics) Sorting Artificial intelligence computer.software_genre business computer Outcome (game theory) Natural language processing Prime (order theory)
Zdroj:	Communications in Computer and Information Science ISBN: 9789811605062 RTIP2R (1)
Popis:	The instantaneous magnification of digital texts has made text categorization a prime technique for managing and sorting text data. The goal of this study is to present a lazy learning-based text categorization system using text representation features. Experiments were performed on 14,373 texts from nine different categories procured from various online news corpus and magazines. The experimental results show an encouraging outcome of 96.24% accuracy using the K* algorithm. The performance of the system was also tested with other existing approaches and datasets and our system produced a better result.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ba6e7b6d24b3358f1b15fbf4f010a0fa https://doi.org/10.1007/978-981-16-0507-9_30 Zobrazit plný text záznamu