Research on Deep Learning-Based Personalized Recommendation Systems

Short videos have become increasingly popular in recent years, leading to the rise of many short video platforms with large user bases, such as leading platforms like TikTok. The user groups on these platforms are vast. With the rise of short-video platforms, TikTok, as one of the leading players, has become a highly influential social media platform worldwide. With the development of short videos, personalized recommendations are also playing an increasingly important role in short videos and are constantly evolving. This report examines the definition, classification, and evolution of personalized recommendation systems, along with their applications and the development trends and suggested countermeasures in short video platforms, with the objective of analyzing the current status and emerging trends of personalized recommendations in this domain. Research has found that personalized recommendations are of great help to the development of short videos. Enterprises need to keep up with the times and constantly update their personalized recommendation systems to enhance user experience and retain more users. Meanwhile, users also need to improve their ability to distinguish during the process of using short videos. In addition, the government should supervise enterprises to ensure the healthy application and development of personalized recommendations in short videos. It provides valuable reference information for content creators, short video platforms, and end users.

The increasing popularity of social networks indicates that the vast amounts of data contained within them could be useful in various implementations, including recommendation systems. Interests and research publications on deep learning-based recommendation systems have largely increased. This study aimed to identify, summarize, and assess studies related to the application of deep learning-based recommendation systems on social media platforms to provide a systematic review of recent studies and provide a way for further research to improve the development of deep learning-based recommendation systems in social environments. A total of 32 papers were selected from previous studies in five of the major digital libraries, including Springer, IEEE, ScienceDirect, ACM, Scopus, and Web of Science, published between 2016 and 2020. Results revealed that even though RS has received high coverage in recent years, several obstacles and opportunities will shape the future of RS for researchers. In addition, social recommendation systems achieving high accuracy can be built by using a combination of techniques that incorporate a range of features in SRS. Therefore, the adoption of deep learning techniques in developing social recommendation systems is undiscovered.

Purpose The advent of social commerce has precipitated a paradigm shift in consumers' acquisition of product information. This shift has particularly impacted short-video platforms, which have become one of the most convenient and important sources for consumers to encounter promotional videos. Information encounter (IE) is an important trigger for short video users' unanticipated consumption behavior. This study aims to explore the formation mechanism and influence factors of consumer information encountering behavior (CIEB) in short video platforms. Design/methodology/approach Twenty-three short video users were selected as participants using semi-structured interviews, and the interview data were analyzed by three-level coding with the help of grounded theory, identifying a total of 55 concepts, 22 subcategories and 8 main categories. Findings Combined with the Attention-Interest-Desire-Action (AIDA) model and the IE episodes provided by Erdelez, this study finally constructs a process model of users' CIEB in short video platforms, including four stages: information attention, interest attraction, desire activation and action implementation. In addition, the influencing factors of users' CIEB in short video platforms can be categorized into four aspects: first is the individual factors including consumption level, consumer decision-making patterns, information literacy and user real-time status; second is the information-related factors including information credibility and information quality, among which information credibility is particularly critical in CIEB in short video platforms, and information credibility includes uploader, store and brand credibility; third is the platform-related factors mainly include algorithmic recommendations and quality of platform services, and finally the environmental factors include previous activities. Originality/value The findings of the study not only deepen users' recognition of their consumption process but also provide a theoretical basis and practical implications for short video commerce to further optimize and enhance the consumption experience.

Unlike traditional social media platforms, short video platforms use big data and artificial intelligence algorithms to look at users' interest preferences, viewing behavior, and interaction information in real time, providing personalized content recommendations. While this tailored approach improves user experience and platform stickiness, it has also caused a certain amount of content to become similar. This study explores how algorithms make content styles converge on short video platforms and influence users' creative intentions and aesthetic preferences. The research shows that while recommendation algorithms make user experience better, they also lead to the homogenization of content creation. Moreover, platform design and communication mechanisms play an important role in shaping public views on aesthetics, entertainment, and social values. By looking at platform algorithms and how they work underneath, this research provides a theoretical basis for improving short video platform design and thinks about the ethical responsibilities these platforms have in shaping digital culture. However, the study has some limitations, including relying on qualitative information and platform-based analysis without much real user data or creator interviews. Future research could use a mixed-methods approach that includes quantitative user engagement information and qualitative interviews with content creators and platform engineers, to put it simply.

The purpose of the article discusses the consumption behaviour, influencing factors and personal factors of short video users through literature review, expert interviews and research results. Among the consumption behaviour, it studies herd mentality, blind mentality, impulsive mentality and experiential consumption. Among the influencing factors, it studies advertisements, live commerce, community effects and consumption reasons. At the same time, it also studies the influence of personal factors on short video users' consumption behaviour. Whether short video users consume in short video platform and how much does a person cost has a significant positive correlation with advertisements, live commerce, the community effects and consumption reasons; Incomes in personal factors have a positive significant influence on monthly cost; The consumption reasons in short video platforms, consuming in short video platform (TikTok), consuming in short video platform (Kwai) and advertisements on consumption behaviour significantly affect whether short video users consume. The consumption reasons and the geographic location significantly affect the monthly cost of short video users.

The theme of this paper is to study the impact of short video platforms on users’ behaviors, and film interpretation is chosen as an example. As a new medium of information dissemination, short video platforms have developed at a very fast speed in recent years. While it has brought a lot of benefits to the public, it has also brought bad far-reaching effects on the people. The main feature of short video platforms is their short video production time and simple process; Second, the speed and scope of information dissemination of short video platforms is extremely fast, small to different cities, and large to different countries. Among them, the TikTok platform is the most typical example. TikTok short videos are not only spread in China but also respected by other countries abroad. The short video propagated in the short video platform can transmit a large amount of information at home and abroad in only ten seconds of video. This research helps short video platforms to improve and increase consumer satisfaction. It can also play a role in promoting things and raising awareness among the users.

This paper investigates the influence of short video platforms on the dissemination effect of film and television IP. By collecting and analyzing the data of movie box office and its short video dissemination, it is found that the three movies with higher box office have higher heat on short video platforms. From the perspective of communication subject, this paper divides short video communication into two kinds: official publicity and audience spontaneous communication. Further analysis reveals that short video platforms can enable film and TV IP to expand the scope of dissemination, maintain their popularity across media, and increase their commercial value. In the case that the content is high quality, the short video platform can keep the IP hot in a new text form. In addition, this paper also discusses the problems that need to be paid attention to in the dissemination process, like copyright management and over-publicity, and puts forward suggestions. In maintaining a balance between promoting users' free creation and copyright management, Propaganda subjects should also pay attention to the data feedback and adjust the publicity density.

Recently, deep learning-based positioning systems have gained attention due to their higher performance relative to traditional methods. However, obtaining the expected performance of deep learning-based systems requires large amounts of data to train model. Obtaining this data is usually a tedious process which hinders the utilization of such deep learning approaches. In this paper, we introduce a number of techniques for addressing the data collection problem for deep learning-based cellular localization systems. The basic idea is to generate synthetic data that reflects the typical pattern of the wireless data as observed from a small collected dataset. Evaluation of the proposed data augmentation techniques using different Android phones in a cellular localization case study shows that we can enhance the performance of the localization systems in both indoor and outdoor scenarios by 157% and 50.5%, respectively. This highlights the promise of the proposed techniques for enabling deep learning-based localization systems.

This study analyzed the impact of system quality and HCI factors on user acceptance intention, mediated by perceived trust and immersion, in the context of a deep learning-based makeup recommendation system. The results indicate that system quality and HCI factors significantly influence user acceptance intention through perceived trust and immersion. This underscores the importance of system quality and HCI factors for the successful application of makeup recommendation systems. In particular, factors such as diversity, accuracy, anthropomorphism, and realism enhance user trust and immersion, leading to higher acceptance intention. However, it was found that certain factors, such as personalization, do not significantly influence acceptance intention through immersion. This suggests that the impact of specific factors should be considered in the design of recommendation systems. The study is limited by its focus on a specific age group and gender in the survey, which may restrict the generalization of the results. Additionally, there is a lack of research on users with different cultural backgrounds, necessitating an understanding of the global market applicability. Future research should extend to users with diverse demographic characteristics to derive universal design principles for makeup recommendation systems. Furthermore, the impact of factors such as personalization on user experience should be explored in depth to enhance user-centered, customized beauty services. This research provides a theoretical and practical foundation for the effective design and implementation of makeup recommendation systems and is expected to contribute to the digital transformation of the beauty industry.

BackgroundWith the rapid development of smart phones, the platform for people to obtain information and resources has shifted from traditional media carriers to smart phones and smart devices. Short video applications are favored by all users and capital, and the number of users, industry scale and social influence are increasing. Under the background of covid-19, the application of short format video has received unprecedented attention and influence. At present, short videos have gone beyond “watching” and added links with user experience, user psychology, consumer behavior and other factors. This paper attempts to analyze the development status of China's short video industry from the perspective of user experience and user psychology, and study the types of short video under different operating conditions, the differences of user experience and user psychology, and the changes of interactive thinking., Especially in the aspect of emotional behavior, it puts forward effective design strategies for the application industry.Research Objects and MethodsThis study compares and analyzes the visual interface, gesture operation and interaction mode of typical short video applications (taking Tiktok, Kwai and wechat account as examples) from three aspects: interface visual perception, interactive behavior perception and psychological experience. Through the comparative study of three short video application products, this paper analyzes the similarities and differences, advantages and disadvantages of Tiktok, fast and wechat channel functions, and summarizes the user experience and interaction design strategies of these short video applications. The questionnaire data collected 234 short video users through the online questionnaire in January 2022. The content is the questionnaire survey of “current situation of short video application”, which mainly analyzes the zero order correlation and covariance analysis between psychological duration. Personal users accept short format video and user experience problems. The use of emotional micro behavior in various countries and regions was investigated by questionnaire. The gross John Emotion Regulation Questionnaire (ERQ), a measurement tool of this study, has 10 items, which are divided into two factors: cognitive reappraisal and expression inhibition. Each item is scored with 7 points (1 = very non-conforming; 2 = relatively non-conforming; 3 = slightly non-conforming; 4 = uncertain; 5 = slightly conforming; 6 = relatively conforming; 7 = very conforming). The higher the score, the higher the tendency.ResultsThrough the comparative study of three short video application products and user questionnaire survey results, it is concluded that there are differences in user experience attention, short video duration and psychological demand motivation among different ages. Compared with ordinary users, older users have a shorter time span to buy videos. They found that they spend more time on live video formats than ordinary users.ConclusionShort video application should fully integrate user experience, user psychology and interaction mode, with the goal of improving interaction experience, interface diversification and personalized design. Meet the needs of different groups of users, optimize the user experience, tap the potential needs of users, increase user stickiness, and enhance the value and competitiveness of short video applications.AcknowledgementsFunded by College of Chinese & ASEAN Arts, Chengdu University, the major scientific research achievements.

The application of deep learning-based (DL) network intrusion detection systems (NIDS) enables effective automated detection of cyberattacks. Such models can extract valuable features from high-dimensional and heterogeneous network traffic with minimal feature engineering and provide high accuracy detection rates. However, it has been shown that DL can be vulnerable to adversarial examples (AEs), which mislead classification decisions at inference time, and several works have shown that AEs are indeed a threat against DL-based NIDS. In this work, we argue that these threats are not necessarily realistic. Indeed, some general techniques used to generate AE manipulate features in a way that would be inconsistent with actual network traffic. In this paper, we first implement the main AE attacks selected from the literature (FGSM, BIM, PGD, NewtonFool, CW, DeepFool, EN, Boundary, HSJ, ZOO) for two different datasets (WSN-DS and BoT-IoT) and we compare their relative performance. We then analyze the perturbation generated by these attacks and use the metrics to establish a notion of "attack unrealism". We conclude that, for these datasets, some of these attacks are performant but not realistic.

From the cross-cultural perspective, the external exchange of the Huangmei Opera in Anhui province is not very good. In the new media era, short videos are booming, which have brought opportunities as well as challenges to the spread of Huangmei Opera. On the one hand, they are of great significance to promote the popularity and influence of the Huangmei Opera through relying on short video platforms. On the other hand, they have brought multiple problems to the communication of Huangmei Opera through short videos. Thus targeted measures should be taken to provide guidance and methods for the innovation of the communication of Huangmei Opera in Anhui province through short videos including Tik Tok, Bilibili and WeChat Channel as we have entered an era of new media. Therefore, this paper studies the development of Huangmei Opera on the short video platforms, focuses on analyzing the development problems encountered by Huangmei Opera in modern society, and explores the path of its inheritance and growth. It’s hoped to find a diversified mode, expand the audience, innovate the information and seek a new path suitable aiming at inheriting and carrying forward the traditional Chinese opera culture represented by Huangmei Opera.

In recent years, the short video has gradually become a way for people to obtain information, entertain themselves, and spread their opinions. The number of users of short video platforms such as Tik Tok and Kuaishou shows an increasing trend. With the proposal of a rural revitalization strategy, the spread of agricultural science popularization knowledge also occupies a place in short video platforms such as Tik Tok, which plays an extremely important role in solving the agricultural knowledge problems for the public. Based on the three-dimensional classification of short videos of agricultural science popularization, this paper analyzes the narrative strategies of short videos of agricultural science popularization on the short video platform Tik Tok from three angles: narrative theme, narrative structure, and narrative discourse. This study also summarizes the creation rules of this kind of short video in combination with the team’s own experience of creation, so as to promote the wide spread of agricultural science popularization knowledge and make more knowledge about agriculture, the countryside, and farmers enter the lives of ordinary people

With the rapid development of short video platforms, they are gradually changing the way information is disseminated and public opinion is guided. To explore the role of short videos in guiding public opinion, this study mainly analyzes data from third-party data platforms and short video media accounts to reveal the mechanism of short videos on the evolution of public opinion. A detailed statistical analysis of the content of relevant videos on the short video platform was conducted, including the number of video views, the number of comments, and their changing trends; An in-depth analysis was conducted on the videos and comments released by self-media and mainstream media. Through content analysis, the study evaluated the communication characteristics of these media in guiding public opinion, including the selective dissemination of information, emotional tendencies, and the shaping of public cognition. The research results show that short video platforms play a significant role in guiding public opinion, and their dissemination characteristics and content selection have a profound impact on the formation and development of public opinion. In particular, self-media and mainstream media play a key role in guiding public opinion. They play a leading role in shaping public opinion through different communication strategies and content presentation.

Purpose In Chinese libraries, short video platforms have emerged as a channel for new media marketing. Thus, this study aims to explore libraries’ communication influence on China’s largest short video platform, that is, Douyin (the Chinese version of Tiktok), and to provide corresponding suggestions for improvement of libraries’ communication influence in the short video platform. Design/methodology/approach Based on the Douyin Communication Index (DCI), this paper collects the top 200 library Douyin accounts of cultural reading in China and uses statistical and content analyses to evaluate the communication influence of library Douyin accounts. Findings Study findings show that libraries of various types and in various regions currently have an unbalanced development trend, with public libraries accounting for the vast majority and nearly half of the libraries located in China’s eastern region. Analysis of variance shows differences in the influence of Douyin communication among library types. Correlation analysis shows that indicators with a high correlation with DCI include the number of new works, likes, shares, and comments. In marketing content, the library’s high-impact short videos have characteristics of value, interest, and emotional touch. Originality/value This study uses a hybrid research method to explore Chinese libraries’ communication influence using the Douyin short video platform. Compared to other parts of the world, short videos in Chinese libraries have unique characteristics. They are rooted in China’s history and reality, showcasing the unique charm of Chinese library culture and serving as a unique reference for library marketing activities around the world.