Using Artificial Intelligence to Analyze Nature of Science Themes: Einstein and Eddington Documentary Film Example by Yusuf Kartal, Munise Seckin-Kapucu

“…Despite the challenges posed by subjectivity regarding the nature of science, it is thought that computer-aided models can provide much more than information retrieval and advanced search. In this context, although it seems pretty difficult to extract the nature of science themes on limited data with the Latent Dirichlet Allocation algorithm, it is possible that the artificial learning models to be used in addition to the Latent Dirichlet Allocation algorithm can detect the nature of science themes. …”
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A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation by Longyue Wang, Derek F. Wong, Lidia S. Chao, Yi Lu, Junwen Xing

“…The first one is cosine tf-idf, which comes from the realm of information retrieval (IR). The second is perplexity-based approach, which can be found in the field of language modeling. …”
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Incremental learning algorithm for dynamic evolution of domain specific vocabulary with its stability and plasticity analysis by Mansi Jain, Harmeet Kaur, Bhavna Gupta, Jaya Gera, Vandana Kalra

“…Abstract Domain-specific vocabulary, which is crucial in fields such as Information Retrieval and Natural Language Processing, requires continuous updates to remain effective. …”
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Manajemen kepala Madrasah Ibtidaiyah dalam menumbuhkan pendidikan karakter religius pada era digital by Murni Yanto

“…Information technology helps facilitate all human activities, information retrieval, convey information and literacy about the addition of knowledge in learning by utilizing technology, so that students can learn by making maximum use of learning resources.…”
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Clinical entity augmented retrieval for clinical information extraction by Ivan Lopez, Akshay Swaminathan, Karthik Vedula, Sanjana Narayanan, Fateme Nateghi Haredasht, Stephen P. Ma, April S. Liang, Steven Tate, Manoj Maddali, Robert Joseph Gallo, Nigam H. Shah, Jonathan H. Chen

“…In conclusion, CLEAR utilizes clinical entities for information retrieval and achieves >70% reduction in token usage and inference time with improved performance compared to modern methods.…”
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Subgraph-Indexed Sequential Subdivision for Continuous Subgraph Matching on Dynamic Knowledge Graph by Yunhao Sun, Guanyu Li, Mengmeng Guan, Bo Ning

“…Continuous subgraph matching problem on dynamic graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including information retrieval and community detection. Specifically, given a query graph q, an initial graph G0, and a graph update stream △Gi, the problem of continuous subgraph matching is to sequentially conduct all possible isomorphic subgraphs covering △Gi of q on Gi (=G0 ⊕ △Gi). …”
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Presenting an Evaluation Model of Digital Libraries (Iran) by Alireza Isfandyari Moghaddam, Atefeh Zarei, Elham Naiich

“…Then, the digital library evaluation model was developed in theconfirmatory factor analysis, which led to identifying 13 components (information link, architecture, information retrieval, new technologies, users, user-friendliness, applicability, information exchange, information, communication, updating, user security, and information coverage). …”
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Shadow Detection in Remote Sensing Images Based on Multibranch Feature Aggregation and Channel-Spatial Attention by Xueli Chang, Haiyang Shi, Tiejun Zhang, Huazhong Jin, Ao Xu

“…High-resolution remote sensing image shadow detection has wide applications in target recognition, land information retrieval, and other fields. However, current shadow detection technologies still face challenges, including shadow omission and difficulty in defining boundaries. …”
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Exploring Topic Coherence With PCC-LDA and BERT for Contextual Word Generation by Sandeep Kumar Rachamadugu, T. P. Pushphavathi, Surbhi Bhatia Khan, Mohammad Alojail

“…Extracting key phrases is an essential task that aids document summarization, information retrieval, and topic classification. Topic modeling significantly enhances our understanding of the latent structure of textual data. …”
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The New Approach Research on Singing Voice Detection Algorithm Based on Enhanced Reconstruction Residual Network by Lilin Liu

“…Content-based music information retrieval applications are mainly embodied in the automatic classification and recognition of music. …”
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Using Large Language Models to Retrieve Critical Data from Clinical Processes and Business Rules by Yunguo Yu, Cesar A. Gomez-Cabello, Svetlana Makarova, Yogesh Parte, Sahar Borna, Syed Ali Haider, Ariana Genovese, Srinivasagam Prabha, Antonio J. Forte

“…This study highlights the potential of LLMs for healthcare information retrieval, especially when relevant data are provided. …”
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EventSegNet: Direct Sparse Semantic Segmentation from Event Data by Pengju Li, Yuqiang Fang, Jiayu Qiu, Jun He, Jishun Li, Qinyu Zhu, Xia Wang, Yasheng Zhang

“…Achieving accurate semantic information retrieval under conditions of high dynamic range and rapid scene changes remains a significant challenge for image-based algorithms. …”
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A Hybrid Contextual Embedding and Hierarchical Attention for Improving the Performance of Word Sense Disambiguation by Robbel Habtamu Yigzaw, Beakal Gizachew Assefa, Elefelious Getachew Belay

“…It plays a crucial role in natural language applications such as machine translation, question-answering, chatbots, information retrieval, sentiment analysis, and overall language comprehension. …”
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Massively parallel homogeneous amplification of chip-scale DNA for DNA information storage (MPHAC-DIS) by Zhi Weng, Jiangxue Li, Yi Wu, Xuehao Xiu, Fei Wang, Xiaolei Zuo, Ping Song, Chunhai Fan

“…Nevertheless, unbiased information retrieval from low-copy-number sequences remains a barricade that largely arises from the indispensable DNA amplification. …”
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A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

“… Introduction: Automatic profiling and genre classification are crucial for text suitability assessment and as such have been in high demand in education, information retrieval, sentiment analysis, and machine translation for over a decade. …”
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Enhanced automated text categorization via Aquila optimizer with deep learning for Arabic news articles by Muhammad Swaileh A. Alzaidi, Alya Alshammari, Abdulkhaleq QA Hassan, Shouki A. Ebad, Hanan Al Sultan, Mohammed A. Alliheedi, Ali Abdulaziz Aljubailan, Khadija Abdullah Alzahrani

“…This application of DL facilitates effective retrieval and organization of Arabic news articles, which supports tasks such as personalized content recommendations, information retrieval, and summarization. Therefore, this study presents an Enhanced Automated Text Categorization via Aquila Optimizer with Deep Learning for Arabic News Articles (TCAODL-ANA) technique. …”
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Health profession students’ perceptions of ChatGPT in healthcare and education: insights from a mixed-methods study by Lior Moskovich, Violetta Rozani

“…Positive feedback was particularly noted with respect to ChatGPT's role in information retrieval and summarization. The qualitative data revealed three main themes: experiences with ChatGPT, its impact on the quality of healthcare, and its integration into the curriculum. …”
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Automated on-site broiler live weight estimation through YOLO-based segmentation by Mahmoud Y. Shams, Wael M. Elmessery, Awad Ali Tayoush Oraiath, Ahmed Elbeltagi, Ali Salem, Pankaj Kumar, Tamer M. El-Messery, Tarek Abd El-Hafeez, Mohamed F. Abdelshafie, Gomaa G. Abd El-Wahhab, Ibrahim S. El-Soaly, Abdallah Elshawadfy Elwakeel

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Defining geosciences research data through metadata reuse: by Alexandre Ribas Semeler, Luana Farias Sales, Adilson Luiz Pinto, Roberta Pereira da Silva de Paula, Valquer Cleyton Paes Gandra, Heloisa Costa

“…The methodology required the application of techniques and technologies used for descriptive analysis, information retrieval, data manipulation, and visualization of Dublin Core metadata. …”
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Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals by Gulay Tasci, Prabal Datta Barua, Dahiru Tanko, Tugce Keles, Suat Tas, Ilknur Sercek, Suheda Kaya, Kubra Yildirim, Yunus Talu, Burak Tasci, Filiz Ozsoy, Nida Gonen, Irem Tasci, Sengul Dogan, Turker Tuncer

“…<b>Background:</b> Electroencephalography (EEG) signal-based machine learning models are among the most cost-effective methods for information retrieval. In this context, we aimed to investigate the cortical activities of psychotic criminal subjects by deploying an explainable feature engineering (XFE) model using an EEG psychotic criminal dataset. …”
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