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Dealing with high dimensional multi-view data: A comprehensive review of non-negative matrix factorization approaches in data mining and machine learning 处理高维多视图数据:数据挖掘和机器学习中非负矩阵分解方法的综合综述
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-26 DOI: 10.1016/j.cosrev.2025.100788
Nafiseh Soleymani, Mohammad Hossein Moattar, Reza Sheibani
{"title":"Dealing with high dimensional multi-view data: A comprehensive review of non-negative matrix factorization approaches in data mining and machine learning","authors":"Nafiseh Soleymani,&nbsp;Mohammad Hossein Moattar,&nbsp;Reza Sheibani","doi":"10.1016/j.cosrev.2025.100788","DOIUrl":"10.1016/j.cosrev.2025.100788","url":null,"abstract":"<div><div>Non-negative matrix factorization (NMF) has become a well-known model in data mining in recent years. NMF is an unsupervised algorithm that efficiently reduces the number of features while maintaining the crucial information needed to reconstruct the original data by projecting the data onto a lower-dimensional space. NMF's main goal is to automatically extract hidden patterns from high-dimensional vectors; it has been effectively used for prediction, clustering, and dimensionality reduction. On the other hand, a major problem in data mining and machine learning is multi-view decision-making. Multi-view learning is a significant issue in today's multi-modal decision-making environment since it makes use of many and frequently high-dimensional data representations to improve learning outcomes. This study aims to review the state-of-the-art NMF methods for multi-view data processing, encompassing principles, representation approaches, clustering models, and algorithms with various generalizations, developments, and modifications. The review includes discussions on different aspects of the algorithms and provides a comprehensive comparison of their advantages. Additionally, it addresses several open issues and remaining challenges. Ultimately, this review seeks to establish a framework for the NMF concept that may benefit future research.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100788"},"PeriodicalIF":13.3,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Decentralization trends in identity management: From federated to Self-Sovereign Identity Management Systems 身份管理中的去中心化趋势:从联邦身份管理系统到自我主权身份管理系统
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-24 DOI: 10.1016/j.cosrev.2025.100776
Praveensankar Manimaran , Thiago Garrett , Leander Jehl , Roman Vitenberg
{"title":"Decentralization trends in identity management: From federated to Self-Sovereign Identity Management Systems","authors":"Praveensankar Manimaran ,&nbsp;Thiago Garrett ,&nbsp;Leander Jehl ,&nbsp;Roman Vitenberg","doi":"10.1016/j.cosrev.2025.100776","DOIUrl":"10.1016/j.cosrev.2025.100776","url":null,"abstract":"<div><div>Identity Management Systems (IMSs) are fundamental elements in a myriad of digital services across different industries. Traditionally, electronic IMSs have been centralized, similar to historical paper-based IMSs: there is a single authority responsible for issuing, storing, and sharing identity-related information on behalf of the identified subjects (people or devices). Over the last decade, we have been witnessing a decentralization trend in IMSs due to a number of reasons such as an attempt to bridge disconnected identity silos and the strive to involve the user in identity management to a larger degree. Federated and Self-Sovereign IMSs are the two most prominent approaches in the decentralization trend. Despite significant progress in this area, Federated and Self-Sovereign IMSs have not been studied from a conceptual point of view and the fundamental differences between different decentralization approaches have not been analyzed.</div><div>It is important to understand the implications of different approaches when designing future IMSs that may affect millions of users daily. In this work, we conduct a conceptual study of these two IMS classes. First, we propose a generic model consisting of a set of functionalities and a set of operations and use it as a comparison framework. Using the generic model, we analyze three representatives from Federated and Self-Sovereign IMSs, namely, IOTA Identity, Hyperledger Indy, and eIDAS. Based on the analysis, we propose a new multi-dimensional taxonomy to capture the key differences between these systems. Furthermore, we discuss SSI principles and decentralization approaches followed in IMSs. Finally, we present research gaps in Self-Sovereign IMSs along with solution directions.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100776"},"PeriodicalIF":13.3,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A survey on image cryptography mechanisms: hitherto, and future directions 图像加密机制的研究进展及未来发展方向
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-20 DOI: 10.1016/j.cosrev.2025.100783
Tanisha Gupta , Arvind Selwal , Ajay K. Sharma
{"title":"A survey on image cryptography mechanisms: hitherto, and future directions","authors":"Tanisha Gupta ,&nbsp;Arvind Selwal ,&nbsp;Ajay K. Sharma","doi":"10.1016/j.cosrev.2025.100783","DOIUrl":"10.1016/j.cosrev.2025.100783","url":null,"abstract":"<div><div>With the exponential growth in the multimedia data such as images, videos, or audios, the security and confidentiality of the information has emerged as one of the challenging problems. In particular, image data security during communication raises several concerns, where attackers can intercept the communication channel and data security can be breached. Thus, image cryptographic algorithms are a viable solution to secure the images while communication between sender and receiver. Though, there has been significant progress in the field of image cryptography, security and performance of these algorithms is still a challenge to the research community. In this article, we expound a detailed taxonomy-based analysis of the existing state-of-the-art (SOTA) image cryptography techniques. Initially, we devised a novel taxonomy for broad categorization of the image ciphers. Later, the entire survey is organized by considering our own taxonomy for a clear and systematic structure. The analysis of various image ciphers is on the basis of three important aspects such as confidentiality, integrity and authenticity (CIA). Besides, we also illustrate various performance evaluation protocols and cryptanalysis methods that are frequently employed for analyzing the efficacy of the image cryptography algorithms. In addition, we explored the modern methods such as deep convolutional neural networks (DCCN) that are also frequently employed for image cryptography. This study exposes several open research challenges in this active field of image security and also provides future perspectives to the new investigators. One of the imperative challenges is to design lightweight image ciphers with ideal security characteristics. Moreover, authenticated image ciphers is an additional critical parameter for image ciphers, which requires attention of research community.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100783"},"PeriodicalIF":13.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Insight into code clone management through refactoring: a systematic literature review 通过重构洞察代码克隆管理:系统的文献回顾
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-18 DOI: 10.1016/j.cosrev.2025.100767
Manpreet Kaur , Dhavleesh Rattan , Madan Lal
{"title":"Insight into code clone management through refactoring: a systematic literature review","authors":"Manpreet Kaur ,&nbsp;Dhavleesh Rattan ,&nbsp;Madan Lal","doi":"10.1016/j.cosrev.2025.100767","DOIUrl":"10.1016/j.cosrev.2025.100767","url":null,"abstract":"<div><h3>Background</h3><div>Software clones exist in software design models, source code, and test cases. The detection of clones in software attracted the attention of many researchers. However, managing these clones is still a challenging task.</div></div><div><h3>Aim</h3><div>This review aims to find research directions in the field of clone management through refactoring. After the clone detection, developers face two significant challenges. 1) Understanding the large number of reported clones 2) Identifying which clones are suitable for refactoring. This review provides findings of existing clone refactoring research and highlights clone-related parameters that help in filtering clone detection results for refactoring.</div></div><div><h3>Method</h3><div>We conducted a systematic literature review using nine digital libraries, based on seven research questions, identifying articles related to clone refactoring published till July 2024. Starting from an initial set of 810 articles, we selected a comprehensive set of 78 articles published in various leading journals and conferences.</div></div><div><h3>Results</h3><div>The review gives information about clone detection tools, refactoring methods, refactoring tools, and subject systems used in clone refactoring research. It also identifies the importance of clone evolution studies and the usage of machine learning and deep learning techniques for clone refactoring.</div></div><div><h3>Conclusion</h3><div>We conclude that empirical studies on available clone refactoring tools are limited. Future studies exploring the potential of transfer learning and LLM models to enhance clone refactoring can be conducted.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100767"},"PeriodicalIF":13.3,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A comprehensive survey on sentiment analysis: Framework, techniques, and applications 情感分析的综合调查:框架、技术和应用
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-13 DOI: 10.1016/j.cosrev.2025.100777
Manish Kumar Chandan, Shrabanti Mandal
{"title":"A comprehensive survey on sentiment analysis: Framework, techniques, and applications","authors":"Manish Kumar Chandan,&nbsp;Shrabanti Mandal","doi":"10.1016/j.cosrev.2025.100777","DOIUrl":"10.1016/j.cosrev.2025.100777","url":null,"abstract":"<div><div>The study of sentiment analysis (SA), also recognized as opinion mining, is a rapidly emerging area of study in natural language processing (NLP). This area focuses on identifying and extracting emotions and opinions from textual data, categorizing them as either positive, neutral, or negative. Nowadays, most of the people express their opinions on social networking platforms, often using their native languages. The rapid growth of Internet-based applications has given rise to a vast amount of personalized information and broad array of user reviews available online. There are a substantial number of pertinent reviews about a particular domain, which remain difficult for humans to process. Therefore, analyzing user opinions is crucial to extract meaningful insights and understand sentiments effectively. This survey comprehensively examines the spectrum of applications for sentiment analysis within the context of current studies. We then critically review experimental outcomes and limitations observed in cutting-edge studies. Furthermore, we explore lexicon-based methods, machine learning (ML), and deep learning (DL) strategies, as well as emerging techniques like transfer learning, large language models, and multimodal approaches, discussing their strengths as well as their weaknesses.</div><div>In addition, we employed multiple ML and DL strategies, leveraging the two benchmark IMDb and Yelp datasets. Following this, we utilized a systematic framework that incorporated preprocessing techniques, feature extraction, and evaluation metrics to facilitate comprehensive understanding and ensure model generalization. Finally, this study bridges the gap between traditional methods and modern innovations, addressing various challenges in sentiment analysis and proposing a roadmap for future research to mitigate these issues. This article serves as a guiding resource for researchers aiming to build an effective sentiment analysis framework.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100777"},"PeriodicalIF":13.3,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Transformers in speech processing: Overcoming challenges and paving the future 语音处理中的变形:克服挑战,为未来铺路
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-05 DOI: 10.1016/j.cosrev.2025.100768
Siddique Latif , Syed Aun Muhammad Zaidi , Heriberto Cuaya´huitl , Fahad Shamshad , Moazzam Shoukat , Muhammad Usama , Junaid Qadir
{"title":"Transformers in speech processing: Overcoming challenges and paving the future","authors":"Siddique Latif ,&nbsp;Syed Aun Muhammad Zaidi ,&nbsp;Heriberto Cuaya´huitl ,&nbsp;Fahad Shamshad ,&nbsp;Moazzam Shoukat ,&nbsp;Muhammad Usama ,&nbsp;Junaid Qadir","doi":"10.1016/j.cosrev.2025.100768","DOIUrl":"10.1016/j.cosrev.2025.100768","url":null,"abstract":"<div><div>The remarkable success of transformers in the field of natural language processing has sparked interest in their potential for mod- elling long-range dependencies within speech sequences. Transformers have gained prominence across various speech-related do- mains, including automatic speech recognition, speech synthesis, speech translation, speech para-linguistics, speech enhancement, spoken dialogue systems, and numerous multimodal applications. However, the integration of transformers in speech processing comes with significant challenges such as managing the high computational costs, handling the complexity of speech variability, and addressing the data scarcity for certain speech tasks. In this paper, we present a comprehensive survey that aims to bridge research studies from diverse subfields within speech technology. By consolidating findings from across the speech technology landscape, we provide a valuable resource for researchers interested in harnessing the power of transformers to advance the field. We identify the challenges encountered by transformers in speech processing while also offering insights into potential solutions to address these issues.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100768"},"PeriodicalIF":13.3,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
NLP-based techniques for Cyber Threat Intelligence 基于nlp的网络威胁情报技术
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-03 DOI: 10.1016/j.cosrev.2025.100765
Marco Arazzi , Dincy R. Arikkat , Serena Nicolazzo , Antonino Nocera , Rafidha Rehiman K.A. , Vinod P. , Mauro Conti
{"title":"NLP-based techniques for Cyber Threat Intelligence","authors":"Marco Arazzi ,&nbsp;Dincy R. Arikkat ,&nbsp;Serena Nicolazzo ,&nbsp;Antonino Nocera ,&nbsp;Rafidha Rehiman K.A. ,&nbsp;Vinod P. ,&nbsp;Mauro Conti","doi":"10.1016/j.cosrev.2025.100765","DOIUrl":"10.1016/j.cosrev.2025.100765","url":null,"abstract":"<div><div>In the digital era, threat actors employ sophisticated techniques for which, often, digital traces in the form of textual data are available. Cyber Threat Intelligence (CTI) is related to all the solutions inherent to data collection, processing, and analysis useful to understand a threat actor’s targets and attack behavior. Currently, CTI is assuming an always more crucial role in identifying and mitigating threats and enabling proactive defense strategies. In this context, NLP, an artificial intelligence branch, has emerged as a powerful tool for enhancing threat intelligence capabilities. This survey paper provides a comprehensive overview of NLP-based techniques applied in the context of threat intelligence. It begins by describing the foundational definitions and principles of CTI as a major tool for safeguarding digital assets. It then undertakes a thorough examination of NLP-based techniques for CTI data crawling from Web sources, CTI data analysis, Relation Extraction from cybersecurity data, CTI sharing and collaboration, security threats of CTI, and role of LLM in this domain. Finally, the challenges and limitations of NLP in threat intelligence are exhaustively examined, including data quality issues and ethical considerations. This survey draws a complete framework and serves as a valuable resource for security professionals and researchers seeking to understand the state-of-the-art NLP-based threat intelligence techniques and their potential impact on cybersecurity.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100765"},"PeriodicalIF":13.3,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Attention-based transformer models for image captioning across languages: An in-depth survey and evaluation 基于注意力的跨语言图像字幕转换模型:深入调查与评估
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-06-02 DOI: 10.1016/j.cosrev.2025.100766
Israa A. Albadarneh , Bassam H. Hammo , Omar S. Al-Kadi
{"title":"Attention-based transformer models for image captioning across languages: An in-depth survey and evaluation","authors":"Israa A. Albadarneh ,&nbsp;Bassam H. Hammo ,&nbsp;Omar S. Al-Kadi","doi":"10.1016/j.cosrev.2025.100766","DOIUrl":"10.1016/j.cosrev.2025.100766","url":null,"abstract":"<div><div>Image captioning involves generating textual descriptions from input images, bridging the gap between computer vision and natural language processing. Recent advancements in transformer-based models have significantly improved caption generation by leveraging attention mechanisms for better scene understanding. While various surveys have explored deep learning-based approaches for image captioning, few have comprehensively analyzed attention-based transformer models across multiple languages. This survey reviews attention-based image captioning models, categorizing them into transformer-based, deep learning-based, and hybrid approaches. It explores benchmark datasets, discusses evaluation metrics such as BLEU, METEOR, CIDEr, and ROUGE, and highlights challenges in multilingual captioning. Additionally, this paper identifies key limitations in current models, including semantic inconsistencies, data scarcity in non-English languages, and limitations in reasoning ability. Finally, we outline future research directions, such as multimodal learning, real-time applications in AI-powered assistants, healthcare, and forensic analysis. This survey serves as a comprehensive reference for researchers aiming to advance the field of attention-based image captioning.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100766"},"PeriodicalIF":13.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A systematic review of explainability in computational intelligence for optimization 优化计算智能中可解释性的系统综述
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-05-22 DOI: 10.1016/j.cosrev.2025.100764
José Almeida , João Soares , Fernando Lezama , Steffen Limmer , Tobias Rodemann , Zita Vale
{"title":"A systematic review of explainability in computational intelligence for optimization","authors":"José Almeida ,&nbsp;João Soares ,&nbsp;Fernando Lezama ,&nbsp;Steffen Limmer ,&nbsp;Tobias Rodemann ,&nbsp;Zita Vale","doi":"10.1016/j.cosrev.2025.100764","DOIUrl":"10.1016/j.cosrev.2025.100764","url":null,"abstract":"<div><div>This systematic review explores the need for explainability in computational intelligence methods for optimization, such as metaheuristic optimizers, including evolutionary algorithms and swarm intelligence. The work focuses on four aspects: (1) the contribution of Explainable AI (XAI) methods to interpreting metaheuristic performance; (2) the influence of problem features on search behavior and explainability; (3) the role of mathematical theory in providing transparent explanations; and (4) the potential of metaheuristics to enhance the explainability of AI models, such as machine learning (ML). XAI methods such as SHAP, LIME, and visualization techniques provide valuable insights into metaheuristic performance, while landscape analysis and quality diversity approaches reveal algorithm performance across different problem landscapes. The review also explores how metaheuristic algorithms can enhance the interpretability of ML models, turning black-box models into more transparent systems. The work moves on to proposing ”Explainergy,” a novel concept for integrating explainability into metaheuristic algorithms within the energy domain, enhancing the transparency and usability of optimization models.</div><div>This review is a foundation for future research combining explainability with evolutionary computation and metaheuristic optimization to address real-world challenges in diverse fields, including energy systems.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"57 ","pages":"Article 100764"},"PeriodicalIF":13.3,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Abstractive text summarization: A comprehensive survey of techniques, systems, and challenges 抽象文本摘要:对技术、系统和挑战的全面调查
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-05-20 DOI: 10.1016/j.cosrev.2025.100762
Norah Almohaimeed, Aqil M. Azmi
{"title":"Abstractive text summarization: A comprehensive survey of techniques, systems, and challenges","authors":"Norah Almohaimeed,&nbsp;Aqil M. Azmi","doi":"10.1016/j.cosrev.2025.100762","DOIUrl":"10.1016/j.cosrev.2025.100762","url":null,"abstract":"<div><div>Abstractive text summarization addresses information overload by generating paraphrased content that mimics human expression, yet it faces significant computational and linguistic challenges. This paper presents a detailed functional taxonomy of abstractive summarization, structured along four dimensions: techniques (including structure-based, semantic, and deep learning approaches, including large language models), system architectures (ranging from single-model to multi-agent and human-in-the-loop interactive systems), evaluation methods (covering lexical, semantic, and human-centered assessments), and datasets. Our taxonomy explicitly distinguishes techniques from architectures to clarify how methodological strategies are operationalized in practice. We examine pressing multilingual challenges such as linguistic complexity, data scarcity, and performance disparities in cross-lingual transfer, particularly for low-resource languages. Additionally, we address persistent issues such as factual inaccuracies, content hallucinations, and biases in widely used evaluation metrics. The paper highlights emerging trends—including cross-lingual summarization, interactive summarization systems, and ethically grounded frameworks—as key directions for future research. This synthesis not only maps the current landscape but also outlines pathways to enhance the accuracy, reliability, and applicability of abstractive summarization in real-world settings.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"57 ","pages":"Article 100762"},"PeriodicalIF":13.3,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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