Efficient Machine Learning Model for Movie Recommender Systems Using Multi-Cloud Environment

Indira, K.; Devi, M. K. Kavitha

doi:10.1007/s11036-019-01387-4

Cited by 20 publications

(8 citation statements)

References 30 publications

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“…In Indira and Kavithadevi [7] and in this work (NPCA-HAC), the dataset is pre-processed to get rid of outliers. Afterwards, the tactic of feature selection is administered along with the principal component analysis (PCA) method.…”

Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: A novel hybrid feature combination method for enhanced movie recommendations with user resemblance and attitude mining

Lavanya

Bharathi

2021

Pers Ubiquit Comput

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Most movie recommendation methods use hard-clustering and simple collaborative filtering techniques in order to achieve their end results. However, these methods tend to overlook crucial aspects of both users and items. When these methods hard cluster a movie item into a cluster, they turn a blind eye to the fact that the item also exhibits some properties of another cluster’s items. Recommender systems facilitate users and relevant things expeditiously supported their requests and historic communications with alternative customers. Recommendation systems are a crucial portion of signifying things particularly in streaming amenities. For streaming motion-picture show services like Netflix, recommendation methods are vital for serving to users notice fresh movies to get pleasure from. However, massive amounts of information will turn out restrictions in recommendations due to accuracy as a result of diversity and meagerness problems. Our work proposes a unique hybrid technique that mixes collaborative filtering and characteristics of demographic filtering technique to point the close users, and associate against one another. This technique has been established over associate in tending analysis of the way to cut back the blunders in grading estimates supported users’ earlier communications that ends up in improved prediction accuracy in among completely different algorithms. Additionally, a feature combination technique is utilized that progresses the expectation accuracy and to check our method, using MovieLens 1M dataset, we contended an offline assessment, already available assessment tactics, and compared the same with the output factors to support authenticating the proposed procedure.

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Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: A novel hybrid feature combination method for enhanced movie recommendations with user resemblance and attitude mining

Lavanya

Bharathi

2021

Pers Ubiquit Comput

View full text Add to dashboard Cite

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“…The contribution of this theory is used as a mathematical structure to express qualitative and quantitative data and provide a realistic judgment [97][98][99][100]. Let the decision-maker define problems and compare the data [26,101]. Fuzzy theory results in things that are not only "yes" and "no" but leads to a concept of degree between "yes" and "no" [88,[102][103][104].…”

Section: Fuzzy Decision-making Trial and Evaluation Laboratory Methodsmentioning

confidence: 99%

An Examination of the Catalyst for Tapping into Mobile Financial Services in the Post-COVID-19 World

Sun

Chang

2021

Mathematics

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Amid the widespread impact of COVID-19, mobile financial services (MFS) have experienced extensive requests due to the failure to perform physical installments and the need for secure transactions. This trend cannot end the utility of cash but it may promote portable monetary administration toward a cashless world. MFS is anticipated to have a bright future as m-commerce increasingly becomes widely known. This study proposes the choice of making a trial and assessment research facility by using a fuzzy model as the most expository device. General forms of a triangular fuzzy number are subjective categories for a linguistic variable. Linguistic variables take on values defined in their term set, that is, the set of linguistic terms. The essential components, including personal innovativeness, transaction completeness, user-friendliness, anonymity, and privacy, are causal competitive advantages of the mobile payment system framework and may play a critical part in reacting to MFS. This study shows that transaction completeness, innovative interface design, privacy, and security facilitate MFS adoption. Furthermore, reliability is necessary to enhance trust in the MFS technology. This study draws on the outcomes of administrative suggestions and recommends a few observational strategies to improve the monetary administration in the MFS industry.

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“…Taninaga et al [21] show that for personalized manuscripts, through data analysis of users' reading habits and hobbies, the same information can be organized into manuscripts of different angles and styles in a targeted way, and personalized push can be carried out. Indira and Kavithadevi [22] put forward that for automatic news production, it is basically a mode of "manual template plus automatic data filling." is paper investigates the use of a machine learning algorithm to automate the production of data news.…”

Section: Related Workmentioning

confidence: 99%

Automatic Production Technology of Data News Based on Machine Learning Model

2022

Wireless Communications and Mobile Computing

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Data news does not appear out of nowhere. It is the result of the press’s ongoing exploration and innovation as part of the ongoing development of information technology. It is based on early computer-assisted news reporting, statistical news and precise news. In terms of theory and technology, it is a game-changer. The media industry is most sensitive to new technologies and is most willing to apply new technologies in the entire process of news reporting, such as information acquisition, content production and management, and content release, in an era of great changes in the popularity of the Internet and the in-depth application of data processing technology in all walks of life. The data news intelligent production platform investigated and designed in this paper, when combined with current emerging technologies, such as big data, cloud computing, and machine learning algorithms, realizes intelligent and automatic news production, ushering traditional news into an era of intelligence, knowledge, and digitization. Machine learning has made significant progress in the automatic production of data news technology and will continue to do so in the future information society.

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Efficient Machine Learning Model for Movie Recommender Systems Using Multi-Cloud Environment

Cited by 20 publications

References 30 publications

RETRACTED ARTICLE: A novel hybrid feature combination method for enhanced movie recommendations with user resemblance and attitude mining

RETRACTED ARTICLE: A novel hybrid feature combination method for enhanced movie recommendations with user resemblance and attitude mining

An Examination of the Catalyst for Tapping into Mobile Financial Services in the Post-COVID-19 World

Automatic Production Technology of Data News Based on Machine Learning Model

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