Empowering Academic Journal Knowledge Services through Digital-Intelligent Technologies: Mechanisms, Challenges, and Breakthrough Paths

Editorial Department of Journal, Zhengzhou University of Light Industry, Zhengzhou, Henan 450001, China

Abstract

Objective: To address the current challenges facing academic journals in leveraging digital-intelligent technologies for knowledge services, including technological adaptation difficulties, shortages of interdisciplinary talent, and copyright infringement risks. Methods: In the digital-intelligence era, academic journals can enhance their knowledge service capabilities by strengthening user demand orientation, promoting industry-academia-research collaboration, establishing technology application evaluation and optimization mechanisms, building professional knowledge service teams, and improving copyright protection systems. Results/Conclusions: By fully utilizing digital-intelligent technologies based on user knowledge needs, academic journals can reshape knowledge service processes, innovate service models, and continuously improve service quality, thereby providing comprehensive and personalized knowledge services to users.

Keywords: digital-intelligent technology; academic journals; knowledge services; users; talent
Classification Code: G237.5
Document Code: A
Article ID: 1671-0134(2025)02-150-05
DOI: 10.19483/j.cnki.11-4653/n.2025.02.030
Citation Format: Mao Lina. Empowering Academic Journal Knowledge Services through Digital-Intelligent Technologies: Mechanisms, Challenges, and Breakthrough Paths [J]. China Media Technology, 2025, 32(2): 150-154.

In today's era, digital-intelligent technologies represented by big data, artificial intelligence, cloud computing, and blockchain are developing at an unprecedented pace, profoundly transforming people's lives and societal operations. Digital-intelligent technology integrates the efficient data processing capabilities of digital technology with the deep analytical and autonomous decision-making capabilities of intelligent technology, enabling real-time collection, precise analysis, and intelligent application of massive data, thereby providing powerful momentum for transformation and innovation across various industries. As crucial platforms for knowledge dissemination and academic exchange, academic journals are facing unprecedented opportunities and challenges amid this technological wave [1]. Traditional academic journal publishing models, centered on print media with cumbersome processes and long cycles, suffer from numerous limitations in timeliness, precision, and personalized service. The integration of digital-intelligent technologies offers new approaches and methods for the transformation of knowledge services in academic journals.

1. Mechanisms of Digital-Intelligent Technology Empowering Academic Journal Knowledge Services

Digital-intelligent technology represents the deep integration of digital and intelligent technologies, encompassing a series of advanced technologies such as big data, artificial intelligence, blockchain, and cloud computing. These technologies work collaboratively and complementarily to build an efficient, intelligent, and secure knowledge service ecosystem for academic journals.

1.1 Reshaping Knowledge Service Processes

The deep application of digital-intelligent technologies enables academic journals to reshape their knowledge service processes, achieving precision, intelligence, and efficiency in knowledge services to meet users' increasingly diverse needs. First, digital-intelligent technologies facilitate precise topic planning. As noted, "The prerequisite for knowledge services is understanding the knowledge needs of the nation and society" [2]. In traditional academic journal operations, editors primarily rely on their professional knowledge and experience, supplemented by limited understanding of industry trends, to determine topic directions. This approach involves subjective judgment and limitations, making it difficult to comprehensively and accurately grasp frontier hotspots and trends in academic research. However, "the application of new technologies helps achieve problem-consciousness-oriented topic planning activities" [3]. By leveraging digital-intelligent technologies, academic journals can collect massive amounts of academic data, including publication statistics, citation frequencies, author collaboration networks, and conference themes. Through deep mining and analysis of this data, journals can precisely identify hot topics and potential research directions in current research fields [4]. Machine learning algorithms in artificial intelligence can also analyze researchers' interests and behavioral data to predict future research directions they may focus on, providing forward-looking references for topic planning. By examining researchers' browsing records, search keywords, and download behaviors on academic platforms, machine learning algorithms can construct user interest models to predict future research needs. When algorithms detect increasing attention from numerous researchers toward an emerging field, academic journals can conduct precise topic planning to provide guidance and exchange services for academic research.

Second, digital-intelligent technologies enable intelligent production and presentation of academic content. Content production is the core of academic journal knowledge services. Traditional production models rely on manual writing by authors and manual review by editors, involving cumbersome processes, low efficiency, and susceptibility to human factors. The application of digital-intelligent technologies in content production significantly improves efficiency and quality. During the authoring process, AI-assisted writing tools provide powerful support by automatically generating paper outlines, recommending relevant references, and even polishing sentences and checking grammar based on keywords and research directions provided by authors. In the editorial review stage, AI technology substantially enhances review efficiency and accuracy, shortening publication timelines for researchers. Additionally, academic journals can utilize Sora's text-to-video large models to achieve organic integration of text, images, audio, and animation, creating entirely new forms of academic content presentation [5].

Third, digital-intelligent technologies enable efficient dissemination and promotion. In an era of information explosion, effective dissemination is crucial for academic journals. Digital-intelligent technologies open new avenues for dissemination, achieving efficient and widespread reach. By constructing multi-channel intelligent dissemination systems, journals can precisely deliver content to target audiences. Using social media platforms, academic websites, mobile applications, and other channels, combined with big data analysis and user profiling, different types of academic content can be pushed to interested users. On social media platforms, journals can push relevant paper abstracts and research highlights based on users' fields of interest and tags, attracting attention and clicks. AI technology can also achieve personalized content recommendations by using algorithms to suggest academic literature based on users' reading histories and search records [6]. This personalized recommendation not only improves information acquisition efficiency but also enhances user stickiness to academic journals.

Digital-intelligent technologies also provide vast space for innovating knowledge service models, driving academic journals to transform from traditional single content provision to diversified, personalized, and intelligent knowledge services. By deeply mining user needs and combining advanced technological means, academic journals can create more attractive and competitive service models, thereby enhancing user experience and satisfaction. First, personalized customization services represent an important development direction. Through big data analysis and AI algorithms, journals can deeply understand users' interest preferences, research fields, and reading habits to tailor personalized knowledge content. By collecting and analyzing user behavior data, academic journals can build precise user profiles, providing customized services and complete solutions throughout the entire research lifecycle, including project initiation, literature analysis, project implementation, experimental assistance, academic exchange, paper writing, publication promotion, and outcome evaluation, thereby achieving intelligent information services [7].

Second, knowledge graph construction is a key technology for empowering academic journal knowledge services. By building knowledge graphs, academic journals can integrate and connect scattered knowledge resources, forming a structured knowledge network that provides users with more comprehensive and in-depth knowledge discovery and exploration services. Knowledge graphs can reveal intrinsic connections between different knowledge points, helping users identify potential research contexts and knowledge associations. When users search for a keyword, the knowledge graph not only presents relevant literature lists but also displays relationship maps between the keyword and other related concepts, guiding users toward deeper knowledge exploration. Knowledge graphs can also support academic research by helping researchers understand the development history, hot trends, key figures, and institutions in a research field, providing important references for topic selection and research direction determination.

Third, interactive service experiences constitute an important means of improving knowledge service quality. Through digital-intelligent technologies, academic journals can build online interactive platforms that facilitate communication and interaction among authors, readers, and editors, fostering a vibrant academic exchange atmosphere [8]. Users can comment, share viewpoints, ask questions, and provide answers within the community. After publishing papers, authors can receive timely feedback and suggestions from readers, promoting further improvement and exchange of academic achievements. Academic journals can also regularly host online academic seminars, inviting experts to deliver keynote speeches and interact with participants in real time. This interactive service experience not only enhances users' sense of participation and belonging but also promotes collision and exchange of academic ideas, thereby increasing the influence of academic journals.

2. Real-World Challenges in Digital-Intelligent Technology Empowering Academic Journal Knowledge Services

Currently, despite the support of digital-intelligent technologies, academic journals continuously enhance their knowledge service capabilities based on user needs [9]. However, most journals still suffer from single service models and unclear service pathways due to the following challenges.

2.1 Technological Adaptation Difficulties

Significant differences exist among academic journals in terms of scale, resources, audience, and development goals, making technology selection and application adaptation a major challenge. Small academic journals, limited by funding and technical capabilities, often face high technology costs and difficulties in effective integration when introducing advanced digital-intelligent technologies. Some small social science journals attempting to introduce complex big data analysis systems to mine academic hotspots find themselves unable to effectively configure and maintain the systems due to a lack of professional technical staff, resulting in low operational efficiency, inaccurate data processing results, and inability to provide strong support for topic planning. Large comprehensive academic journals may also fail to fully leverage technological advantages due to adaptation issues with their business processes. For instance, after introducing intelligent review systems, some large journals experience significant deviations between review results and expert opinions because the systems cannot effectively integrate with existing review processes and standards, affecting review fairness, accuracy, and efficiency. Additionally, the rapid iteration of digital-intelligent technologies creates enormous pressure for continuous upgrades. New algorithms, models, and tools constantly emerge, requiring substantial ongoing investment in technology updates. Failure to update technologies in a timely manner leads to lagging knowledge services and declining user experience.

2.2 Shortage of Interdisciplinary Talent

The transformation of academic journals toward digital-intelligent knowledge services demands increasingly diverse and comprehensive talent, yet there is an extreme shortage of interdisciplinary professionals who understand both academic subject matter and digital-intelligent technologies. Traditional journal editors possess deep academic backgrounds and editorial experience but lack knowledge and skills in big data analysis, AI algorithms, blockchain applications, and other digital-intelligent technologies. This makes it difficult for editors to fully understand technical principles or effectively communicate and collaborate with technical teams, significantly diminishing technology application effects. When constructing knowledge graphs, editors can provide professional guidance on academic content but cannot optimize the graph structure and relationships with technical staff due to unfamiliarity with graph construction algorithms and data processing techniques, limiting the accuracy and practicality of knowledge graphs. In topic planning, the lack of interdisciplinary talent makes it difficult to fully utilize big data technology to mine potential hot topics. Editors may only conduct simple analyses of surface-level data, failing to deeply explore underlying trends and correlations, resulting in topic planning that lacks foresight and innovation. In content review, insufficient understanding of AI review system principles and parameter settings prevents accurate judgment of review result reliability, potentially leading to misjudgment of manuscript quality and affecting journal knowledge service levels.

2.3 Copyright Infringement Risks

In the digital-intelligence era, academic journals face more complex and severe copyright infringement risks. With widespread application of AI and big data technologies, copyright infringement has become more diverse and concealed. The copyright ownership of AI-generated content (AIGC) has sparked widespread controversy. Some AI writing tools can generate articles based on input instructions and data, potentially infringing on original authors' copyrights by unauthorized use of large amounts of existing academic literature. Big data technology makes academic data acquisition and dissemination more convenient but also increases risks of data leakage and misuse. Some criminals illegally obtain journal databases and batch-disseminate papers for commercial purposes, seriously damaging the rights of journals and authors. Abusive use of web crawler technology to scrape content from journal websites without authorization leads to illegal reproduction and distribution, disrupting normal dissemination order. On social media and academic exchange platforms, user sharing and dissemination behaviors may also trigger infringement issues. Some users share full texts or portions of journal articles in social groups or personal blogs without copyright holder permission, posing significant challenges to copyright protection due to rapid and wide-ranging dissemination in the digital environment.

3. Practical Pathways for Digital-Intelligent Technology Empowering Academic Journal Knowledge Services

Revolutionary advances in information technology and their application in the publishing industry provide conditions for high-quality development of academic journals and guarantee intellectual support for knowledge services [10]. In the digital-intelligence era, academic journals can enhance their knowledge service capabilities and provide comprehensive, personalized services through the following pathways.

3.1 Strengthening User Demand Orientation

"Orienting toward user needs to improve publishing service capabilities represents an important manifestation of academic journals accelerating the development of new quality productive forces, shaping new core competitiveness and providing strong development momentum to drive high-quality development" [11]. Academic journals should leverage big data analysis to deeply mine user browsing histories, search records, download behaviors, and other data to accurately understand research interests and knowledge needs [12]. For example, by analyzing users' frequent browsing and downloading of papers in specific fields over time, journals can identify in-depth research needs. Based on this precise understanding, academic journals can provide personalized knowledge services by customizing exclusive knowledge push plans according to users' disciplinary backgrounds, research directions, and interest preferences. For researchers in artificial intelligence, journals can push the latest algorithm research and application case analyses; for graduate students, they can provide not only cutting-edge research in professional fields but also academic research methods and paper writing techniques. Through such personalized services, user satisfaction with knowledge services can be significantly improved.

3.2 Promoting Industry-Academia-Research Collaboration

Industry-academia-research collaboration constitutes an effective pathway for driving technological innovation and application in academic journals. Journals should actively establish partnerships with universities, research institutions, and relevant enterprises to integrate resources and jointly tackle technical challenges [13]. For example, Science China has developed an advanced intelligent semantic analysis system through deep collaboration with computer science departments of top domestic universities, big data research centers, and AI technology companies. This system can accurately identify key information such as professional terminology, research methods, and experimental data in papers, process it structurally, and build knowledge graphs that provide readers with more comprehensive and in-depth knowledge association services. This achievement not only enhances the knowledge service quality and academic influence of Science China but also provides valuable references for other journals. In such collaborations, parties should clarify division of labor and responsibilities while establishing effective communication and benefit distribution mechanisms. As the demand side, academic journals must accurately propose technical requirements and application scenarios; universities and research institutions should focus on technology R&D and innovation, providing theoretical support and technical solutions; enterprises should ensure industrialization and commercialization of technologies to guarantee practical operational effectiveness [14]. Through this complementary collaboration model, digital-intelligent technology innovation and application in academic journals can be accelerated, enhancing core competitiveness.

3.3 Establishing Technology Application Evaluation and Optimization Mechanisms

To ensure maximum effectiveness of digital-intelligent technologies in knowledge services, academic journals should establish comprehensive evaluation and optimization mechanisms. Acta Mathematicae Applicatae Sinica regularly conducts thorough evaluations of digital-intelligent technology applications in its publishing processes. Through data analysis and user feedback, the journal gains deep insights into the operational status of intelligent typesetting systems, online submission and review platforms, and literature recommendation algorithms. When problems are identified, the journal promptly organizes technical teams and editors to discuss optimization solutions. For instance, when the literature recommendation algorithm shows low matching accuracy with user interests, the technical team optimizes the algorithm by adjusting parameters and adding analytical dimensions to user behavior data, while editors provide professional suggestions to ensure recommended literature meets user needs in terms of academic quality and relevance. After multiple optimization cycles, the recommendation accuracy and user satisfaction have significantly improved. Academic journals can similarly establish such continuous evaluation and optimization mechanisms to promptly identify and resolve technology application issues, continuously improving service quality and user experience.

3.4 Building Professional Knowledge Service Teams

Talented individuals with academic literacy and service capabilities constitute crucial guarantees for enhancing academic journal knowledge services [15]. Academic journals should strengthen editor training by regularly organizing participation in academic seminars and professional courses to improve academic levels and expertise. For example, editors can attend frontier academic conferences in relevant disciplines to understand development dynamics and latest research findings for better topic planning and manuscript review. Journals should also cultivate editors' service awareness and communication skills, enabling them to establish good interactive relationships with authors and readers. Through service awareness and communication skills training, editors learn to listen to user needs and opinions and solve problems promptly and effectively. Additionally, journals should actively recruit professionals with interdisciplinary backgrounds and information technology capabilities to inject new vitality into knowledge service innovation. For instance, recruiting talent with computer science and information management backgrounds to manage digital platform construction and data analysis can enhance technical levels and service quality.

3.5 Improving Copyright Protection Mechanisms

In any era, academic journals must legally use literature data while protecting authors' and copyright holders' rights and interests when providing knowledge services. Therefore, journals must prioritize improving copyright protection mechanisms, clarifying digital copyrights, exploring commercialization potential, and striving to maximize intellectual property utilization [16]. Whether digitizing journal content for online retrieval, reading, and downloading, or compiling articles into new knowledge products, strict compliance with copyright laws and regulations is essential. When reproducing literature, journals must ensure the quantity and scope remain within fair use or statutory licensing ranges; when disseminating literature, they must attribute authors and sources to protect copyright. "Copyright runs through the entire knowledge service process, and copyright law protects the legitimate rights and interests of copyright owners, publishing institutions, users, and knowledge service platforms, safeguarding the stable development of knowledge services" [17]. Academic Monthly clearly states in its copyright agreement that the journal has the right to digitize papers for dissemination on its official website and cooperative databases, while authors retain copyright and have the right to use papers in specific scenarios such as personal academic achievement displays. Journals should also clearly elaborate on the scope and duration of copyright transfer to avoid potential disputes. In terms of copyright management processes, strict review systems must be established. During manuscript acceptance, self-review should ensure submitted papers are free from plagiarism or other infringements. After publication, continuous copyright monitoring should track unauthorized reproduction or use, with timely measures taken against such actions.

"From informatization to intelligence in academic journal knowledge services, AI participation can not only optimize knowledge expression, cognition, and recreation but also become an expression method that transforms academic journals and thereby changes the world" [18]. This paper deeply analyzes the mechanisms, challenges, and practical pathways of digital-intelligent empowerment of academic journal knowledge services. Looking forward, digital-intelligent technologies will continue to penetrate deeply into this field, bringing more profound transformations. As technologies mature and innovate, academic journals are expected to achieve fully intelligent and personalized knowledge services. Big data analysis will more accurately identify user needs, and combined with deep AI algorithms, will provide ultimate personalized knowledge push, truly realizing a "thousand faces for thousand users" knowledge service experience.

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Author Biography: Mao Lina (1978—), female, from Zhengzhou, Henan Province, Associate Editor, Master's degree, research focuses on editing, publishing, and cultural communication.

(Responsible Editor: Li Yansong)