Marketing Strategy of Modern Enterprise under the Background of Big Data

Peng, Luyao; Duan, Xueqi

doi:10.1109/cibda50819.2020.00008

Cited by 3 publications

(3 citation statements)

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“…The traditional recommendation systems comprise collaborative filtering, contentbased filtering, and hybrid approaches [9]. Collaborative filtering is a widely employed approach that depends mainly on user-item interactions, covering implicit and explicit data [10].…”

Section: Traditional-based Recommendation Systemsmentioning

confidence: 99%

Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems

Peng,

Siet,

Ilkhomjon

et al. 2024

Applied Sciences

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In the era of big data, effective recommendation systems are essential for providing users with personalized content and reducing search time on online platforms. Traditional collaborative filtering (CF) methods face challenges like data sparsity and the new-user or cold-start issue, primarily due to their reliance on limited user–item interactions. This paper proposes an innovative movie recommendation system that integrates deep reinforcement learning (DRL) with CF, employing the actor–critic method and the Deep Deterministic Policy Gradient (DDPG) algorithm. This integration enhances the system’s ability to navigate the recommendation space effectively, especially for new users with less interaction data. The system utilizes DRL for making initial recommendations to new users and to generate optimal recommendation as more data becomes available. Additionally, singular value decomposition (SVD) is used for matrix factorization in CF, improving the extraction of detailed embeddings that capture the latent features of users and movies. This approach significantly increases recommendation precision and personalization. Our model’s performance is evaluated using the MovieLens dataset with metrics like Precision, Recall, and F1 Score and demonstrates its effectiveness compared with existing recommendation benchmarks, particularly in addressing sparsity and new-user challenges. Several benchmarks of existing recommendation models are selected for the purpose of model comparison.

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Section: Traditional-based Recommendation Systemsmentioning

confidence: 99%

Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems

Peng,

Siet,

Ilkhomjon

et al. 2024

Applied Sciences

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“…(1) Traditional cost management ideas are backward At present, many enterprises have begun to gradually form the concept of cost management, and continue to pay attention to it, but on the practical level, there are still many deficiencies [11]. The most basic problem is that the concept is outdated, and the cost control method of traditional enterprises tends to reduce investment and extreme cost compression.…”

Section: The Main Problems Of Enterprise Cost Control Under the Backg...mentioning

confidence: 99%

Research on Cost Management of Logistics Enterprises Under the Between Big Data, Intelligence, Mobile Internet and Cloud Computing

Duan

2023

FBEM

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In 2013, the concept of "Great wisdom moving Cloud" was first proposed at the China Internet Conference. Under the national technology innovation strategy, Dazhiyun has gradually become a powerful technology engine for economic development and enterprise transformation and upgrading. With the advent of the era of "big wisdom moving cloud", the traditional enterprise cost management has been unable to meet the current financial management requirements, how to form a cost leading advantage has become the core task of cost management. Big data, artificial intelligence, cloud computing, Internet of Things and other related technologies provide technical support for enterprise cost management innovation. However, under the background of "big wisdom moving to cloud", there are still many shortcomings in enterprise cost control, such as backward cost management concept, backward related supporting system, lack of professional talent quality, data collection distortion, etc. Enterprises should take the initiative to introduce information technology. To develop in the direction of technological innovation and management innovation, reduce costs and increase efficiency.

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“…Enterprises must take advantage of the potential presented by big data and aggressively address the issues it presents in order to remain unbeatable in the harsh market rivalry. According to the actual research by L. Peng and X. Duan (2020), optimizing an enterprise's marketing strategy requires realizing effective protection of customer privacy information, boosting the relevance of marketing activities, and carefully planning out marketing strategies [29]. A managerial activity known as corporate marketing involves a number of social relationships, including those with producers, distributors, and consumers.…”

Section: Related Workmentioning

confidence: 99%

A New Big Data and Logistic Regression-Based Approach for Small and Medium-Sized Enterprises

Zhang

Ali

2022

IJRITCC

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Businesses are being asked to assess an expanding volume of actual semi-structured and unstructured statistics to address the obstacles of internationalization and deal more effectively with the uncertainties of international integration. Big Data (BD) analytics can therefore play a strategic role in promoting the international expansion of Small and Medium-Sized Enterprises (SMEs). The exact connection between BD Analytics and globalization has, however, only been sporadically examined in the existing literature. In this study, a quantitative analysis using a Logistic Regression (LR) concept revealed that the interaction effects between BD Analytics architecture and BD Analytics functionality are both helpful and significant but the connection between the management of BD Analytics architecture and the Degree of Internationalization (DI) is not required for internationalization development. This shows that increasing internationalization in SMEs requires more than BD Analytics governance alone. Instead, this study emphasizes the importance of building particular BD Analytics abilities and the availability of a beneficial interaction between management of BD Analytics architecture and BD Analytics abilities that could take advantage of the new information gained via BD Analytics in SME global expansion.

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Marketing Strategy of Modern Enterprise under the Background of Big Data

Cited by 3 publications

References 0 publications

Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems

Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems

Research on Cost Management of Logistics Enterprises Under the Between Big Data, Intelligence, Mobile Internet and Cloud Computing

A New Big Data and Logistic Regression-Based Approach for Small and Medium-Sized Enterprises

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