Machine learning algorithm based sentiment analysis model system for analyzing raw text from Social media website, uses natural language processing for finding the positive or negative data, where machine learning algorithm is used to determine if data is negative or positive
	SAKTHIVEL; DHINAKAR P; ANITHA C; VARMA C S; REDDY C F; SATHISH D
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069725-A
成果简介	NOVELTY - The system uses natural language processing (NLP) for finding the positive or negative data, where machine learning algorithm is used to determine if the data is negative or positive. The system uses logistic regression as a statistical model that uses a logistic function to model a binary dependent variable. A logistic model is used to model the probability of class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick. USE - Machine learning algorithm based sentiment analysis model system for analyzing raw text from various sources such as Facebook(RTM: Social media website), Twitter(RTM: Social media website), and Amazon(RTM: e-commerce website) to drive objective quantitative results using natural language processing. ADVANTAGE - The system effectively improves customer service, and reduces time consumption during process of product analysis. The system improves the customer service and customer feedback analysis, and decreases the cost of the product. DESCRIPTION OF DRAWING(S) - The drawing shows a block diagram of a machine learning algorithm based sentiment analysis model system.
IPC 分类号	G06F-040/30 ; G06N-020/00 ; G06Q-030/02 ; G06Q-030/06 ; G06Q-050/00
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19584
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	SAKTHIVEL,DHINAKAR P,ANITHA C,et al. Machine learning algorithm based sentiment analysis model system for analyzing raw text from Social media website, uses natural language processing for finding the positive or negative data, where machine learning algorithm is used to determine if data is negative or positive. IN202341069725-A[P]. 2023.

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