Internet movie database (IMDb) movie rating predictor for developing machine learning model for predicting ratings of movies on IMDb, by filmmakers, in which machine learning model accurately predicts IMDb ratings for movies based on comprehensive set of features and attributes
	ETHIRAJULU V; SAITEJA B; KUMAR S C; REDDY N C; PRASHANTH B; THIRUPURASUNDARI
	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	IN202341069434-A
成果简介	NOVELTY - The IMDb movie rating predictor which performs data cleaning, transformation, and feature engineering tasks to prepare the dataset for training. The dataset is analyzed to identify the most significant features that strongly correlate with movie ratings. The performance of model is monitored and feedback is gathered to identify areas of improvement. The model is updated periodically with new data to ensure relevance and accuracy in predicting IMDb ratings for future movies. The machine learning model accurately predicts IMDb ratings for movies based on a comprehensive set of features and attributes. USE - Internet movie database (IMDb) movie rating predictor for developing machine learning model for predicting ratings of movies on IMDb, by filmmakers, producers, and movie enthusiasts. ADVANTAGE - The machine learning model accurately predicts IMDb ratings for movies based on a comprehensive set of features and attributes. The model utilizes historical data and learns patterns to provide reliable and precise rating estimations. The filmmakers, producers, and movie enthusiasts leverage our IMDb Movie rating predictor to make informed decisions about movie releases. The user-friendly interface allows users to input movie features and receive estimated IMDb ratings. The interface is intuitive, making easy for users to interact with the predictive model and obtain quick predictions for movies of interest. The machine learning model ensures relevance and accuracy in predicting IMDb ratings for future movies. The integration empowers users to access rating predictions on- the-go, thus enhancing the convenience and usability of the model. The metrics provide a quantitative measure of the accuracy and reliability of model in predicting IMDb ratings. The evaluation metrics such as mean squared error (MSE), root mean squared error (RMSE), or R-squared are measured to quantify the accuracy and robustness.
IPC 分类号	A41B-009/02 ; G06F-040/253 ; G06N-020/00 ; G06Q-010/10 ; G06Q-030/02
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/19893
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	ETHIRAJULU V,SAITEJA B,KUMAR S C,et al. Internet movie database (IMDb) movie rating predictor for developing machine learning model for predicting ratings of movies on IMDb, by filmmakers, in which machine learning model accurately predicts IMDb ratings for movies based on comprehensive set of features and attributes. IN202341069434-A[P]. 2023.

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