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Journal articles on the topic 'Effective summarizing data'

Author: Grafiati

Published: 11 December 2022

Last updated: 31 July 2025

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1

Devrapalli, Dr Dharmaiah, Srija Padmini Guduri, Pericharla Jaya Madhuri, Sathi Navya Vahini Reddy, and Pavani Pasupuleti. "Effective Text Processing utilizing NLP." Indian Journal of Artificial Intelligence and Neural Networking 2, no. 1 (2021): 1–7. http://dx.doi.org/10.54105/ijainn.b3873.122121.

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Summarizing is the practice of condensing a body of material into a more manageable size while retaining all of the key data elements and the intended meaning. Automatic text summarizing systems can now quickly retrieve summary phrases from input documents. However, it has a number of shortcomings, such as duplication, insufficient coverage, incorrect extraction of key lines, and poor sentence coherence. In this study, a new concept of summarizer technique is proposed using the Python spacy package. It extracts the most significant information from the text. The scoring system is also used to

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Dr., Dharmaiah Devrapalli, Padmini Guduri Srija, Jaya Madhuri Pericharla, Navya Vahini Reddy Sathi, and Pasupuleti Pavani. "Effective Text Processing utilizing NLP." Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) 2, no. 1 (2021): 1–7. https://doi.org/10.54105/ijainn.B3873.122121.

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<strong>Abstract:</strong> Summarizing is the practice of condensing a body of material into a more manageable size while retaining all of the key data elements and the intended meaning. Automatic text summarizing systems can now quickly retrieve summary phrases from input documents. However, it has a number of shortcomings, such as duplication, insufficient coverage, incorrect extraction of key lines, and poor sentence coherence. In this study, a new concept of summarizer technique is proposed using the Python spacy package. It extracts the most significant information from the text. The scor

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Gu, Jianyang, Kai Wang, Wei Jiang, and Yang You. "Summarizing Stream Data for Memory-Constrained Online Continual Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 11 (2024): 12217–25. http://dx.doi.org/10.1609/aaai.v38i11.29111.

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Replay-based methods have proved their effectiveness on online continual learning by rehearsing past samples from an auxiliary memory. With many efforts made on improving training schemes based on the memory, however, the information carried by each sample in the memory remains under-investigated. Under circumstances with restricted storage space, the informativeness of the memory becomes critical for effective replay. Although some works design specific strategies to select representative samples, by only employing a small number of original images, the storage space is still not well utilize

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David, Chaim, and Haridimos Kondylakis. "KEGGSum: Summarizing Genomic Pathways." Information 15, no. 1 (2024): 56. http://dx.doi.org/10.3390/info15010056.

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Over time, the renowned Kyoto Encyclopedia of Genes and Genomes (KEGG) has grown to become one of the most comprehensive online databases for biological procedures. The majority of the data are stored in the form of pathways, which are graphs that depict the relationships between the diverse items participating in biological procedures, such as genes and chemical compounds. However, the size, complexity, and diversity of these graphs make them difficult to explore and understand, as well as making it difficult to extract a clear conclusion regarding their most important components. In this reg

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Wang, Ning, and Tian Tian. "Summarizing Personal Dataspace Based on User Interests." International Journal of Software Engineering and Knowledge Engineering 26, no. 05 (2016): 691–713. http://dx.doi.org/10.1142/s0218194016500224.

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A personal dataspace management system (PDSMS) is a platform to manage personal data with various data types. Facing huge volume of heterogeneous personal data and complex relationships between them, it is better for users to start with a simplified, easy-to-read schema and then explore in depth only the relevant schema elements during formulating queries. Existing approaches of database schema summarization neglect user interests, which is very important in a personal dataspace. We propose a framework for building a concise resource summary based on user interests automatically in PDSMS. Our

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Beldi, Amal, Salma Sassi, Richard Chbeir, and Abderrazek Jemai. "DG_summ: A schema-driven approach for personalized summarizing heterogeneous data graphs." Computer Science and Information Systems, no. 00 (2023): 62. http://dx.doi.org/10.2298/csis230331062b.

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Advances in computing resources have enabled the processing of vast amounts of data. However, identifying trends in such data remains challenging for humans, especially in fields like medicine and social networks. These challenges make it difficult to process, analyze, and visualize the data. In this context, graph summarization has emerged as an effective framework aiming to facilitate the identification of structure and meaning in data. The problem of graph summarization has been studied in the literature and many approaches for static contexts are proposed to summarize the graph. These appr

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Harwell, Michael R. "Summarizing Monte Carlo Results in Methodological Research." Journal of Educational Statistics 17, no. 4 (1992): 297–313. http://dx.doi.org/10.3102/10769986017004297.

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Monte Carlo studies provide information that can assist researchers in selecting a statistical test when underlying assumptions of the test are violated. Effective use of this literature is hampered by the lack of an overarching theory to guide the interpretation of Monte Carlo studies. The problem is exacerbated by the impressionistic nature of the studies, which can lead different readers to different conclusions. These shortcomings can be addressed using meta-analytic methods to integrate the results of Monte Carlo studies. Quantitative summaries of the effects of assumption violations on t

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Qomariyah, Siti Syafi’atul. "THE EFFECT OF SUMMARIZING TECHNIQUE ON READING ACHIEVEMENT." Jo-ELT (Journal of English Language Teaching) Fakultas Pendidikan Bahasa & Seni Prodi Pendidikan Bahasa Inggris IKIP 2, no. 1 (2020): 19. http://dx.doi.org/10.33394/jo-elt.v2i1.2408.

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This article is a report of experimental conducted at the second year students of SMA Kanjeng Sepuh Sidayu Gresik. This study was conducted to measure the effect of summarizing technique on reading achievement. The instrument used for collecting data was test. The data analysis showed that mean of pretest was 37,94 in experimental group and 33,68 in control group. The result of t-test of pre-test was 2,444 and t-critical was 1,684 in level of significant .05. And the mean of post-test was 74,52 in experimental group and 68,39 in control group. The difference between the two mean score is 6.13.

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Kyoya, Shunki, and Kenji Yamanishi. "Summarizing Finite Mixture Model with Overlapping Quantification." Entropy 23, no. 11 (2021): 1503. http://dx.doi.org/10.3390/e23111503.

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Finite mixture models are widely used for modeling and clustering data. When they are used for clustering, they are often interpreted by regarding each component as one cluster. However, this assumption may be invalid when the components overlap. It leads to the issue of analyzing such overlaps to correctly understand the models. The primary purpose of this paper is to establish a theoretical framework for interpreting the overlapping mixture models by estimating how they overlap, using measures of information such as entropy and mutual information. This is achieved by merging components to re

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Huan, Jia-Ming, Wen-Ge Su, Wei Li, et al. "Summarizing the Effective Herbs for the Treatment of Hypertensive Nephropathy by Complex Network and Machine Learning." Evidence-Based Complementary and Alternative Medicine 2021 (June 11, 2021): 1–12. http://dx.doi.org/10.1155/2021/5590743.

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Hypertensive nephropathy is a common complication of hypertension. Traditional Chinese medicine has been used in the clinical treatment of hypertensive nephropathy for a long time, but the commonly used prescriptions have not been summarized, and the basic therapeutic approaches have not been discussed. Based on data from 3 years of electronic medical records of traditional Chinese medicine used at the Affiliated Hospital of Shandong University of Traditional Chinese Medicine, a complex network and machine learning algorithm was used to explore the prescribed herbs of traditional Chinese medic

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Sujarwo, Adhittya, Budi Setiyo, Suhendi Suhendi, Febriyantina Istiara, and Tommy Hastomo. "ENHANCING READING COMPREHENSION THROUGH THE UTILIZATION OF THE SUMMARIZATION STRATEGY." Jurnal Smart 9, no. 2 (2023): 131–45. http://dx.doi.org/10.52657/js.v9i2.2109.

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Summarizing strategy is an effective teaching method for improving reading skills. This study focused on enhancing the reading comprehension and learning activity of eleventh-grade students at SIJA, SMK N 9 Bandar Lampung. Classroom action research was used with 29 students as subjects. Both test and non-test instruments were employed to gather qualitative and quantitative data. The results demonstrated that the summarizing strategy effectively improved reading comprehension and learning activity for these students. English teachers can consider using this strategy to enhance the reading abili

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Zhao, Ping, Xue Wei Bai, Yong Kui Li, Ying Li, and Chang Yi Lv. "A New Method of Data Smoothing for Scan-Line Point Cloud in Reverse Engineering." Advanced Materials Research 1006-1007 (August 2014): 352–55. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.352.

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Based on summarizing characteristics of three common kinds of filter method (median filter, mean filter and Gaussian filter) through theory analysis and experiments in Imageware software, a more effective method of smoothing point cloud data was proposed, and the algorithm was realized by programming in MATLAB. Experimental results show that the proposed method combines the advantages of the median filter and mean filter in together, achieves the purpose of smoothing, also ensures the shape of the original data. This research result will lay a foundation for subsequent reconstruction precision

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Styrin, Evgeny, and Natalya Dmitrieva. "Evaluating Public Organizations Using Open Data." International Journal of Electronic Government Research 13, no. 4 (2017): 1–14. http://dx.doi.org/10.4018/ijegr.2017100101.

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Information openness and stakeholder involvement through ICT become the driving factors of public organization change. In this article, an ecosystem approach is embraced to study the social sphere organizations (SSOs), such as hospitals, schools, and libraries. SSOs report on their activities by publishing information on the Web which can be used to evaluate the effectiveness and efficiency of these organizations by the public. The opening of data transforms the relationship between SSOs and other stakeholders. In this article, the institutionalization of SSO evaluation system in Russia is stu

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Wu, Ben, Thapana Choicharoen, and Suwana Juithong. "Effect of Problem-based Learning on the Biology Summarizing Ability of Eighth-Grade Students of Zhengzhou No.1 Middle School in the People's Republic of China." International Journal of Sociologies and Anthropologies Science Reviews 5, no. 4 (2025): 39–48. https://doi.org/10.60027/ijsasr.2025.6051.

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Background and Aims: The impact of Problem-Based Learning (PBL) on biology summarizing ability has far-reaching research significance, and this learning method emphasizes the problem-oriented approach to cultivate students' comprehensive ability and innovative thinking through the processes of problem posing. This experimental research aimed to 1) compare biology summarizing ability before and after learning through Problem-Based Learning.2) To compare biology summarizing ability with the criterion set at 70 percent.3) To assess the student’s satisfaction with Problem-Based Learning. Materials

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Fierens, Amaury, and Sébastien Jodogne. "BERTinchamps: Cost-Effective In-House Training of Language Models in French." Italian Journal of Computational Linguistics 10, no. 2 (2024): 131. https://doi.org/10.17454/ijcol102.07.

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Many in-house applications are envisioned for Language Models (LMs) across various fields. In the medical domain, LMs could automate tasks such as summarizing the health condition of a patient and codifying electronic health records. They also hold potential in the legal field and in journalism. While training LMs directly inside an institution is desirable for leveraging local data and addressing data privacy concerns, this process demands a costly and complex computational infrastructure. This paper explores the recent Cramming approach as a cost-effective way to locally train medium-sized L

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Karim, Shakir, Shahadat Uddin, Tasadduq Imam, and Mohammad Ali Moni. "A Systematic Review of Network Studies Based on Administrative Health Data." International Journal of Environmental Research and Public Health 17, no. 7 (2020): 2568. http://dx.doi.org/10.3390/ijerph17072568.

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Effective and efficient delivery of healthcare services requires comprehensive collaboration and coordination between healthcare entities and their complex inter-reliant activities. This inter-relation and coordination lead to different networks among diverse healthcare stakeholders. It is important to understand the varied dynamics of these networks to measure the efficiency of healthcare delivery services. To date, however, a work that systematically reviews these networks outlined in different studies is missing. This article provides a comprehensive summary of studies that have focused on

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Lestari, Widia Dwi, Santhi Pertiwi, Aprilia Rizki, Eliana Sari, and Neti Karnati. "Effective Leadership In The Digital Age: Challenges And Strategies In Education." Jurnal Edusci 2, no. 2 (2024): 69–79. https://doi.org/10.62885/edusci.v2i2.501.

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This study aims to describe effective leadership in the digital era to discover the challenges and strategies. The method used is literature study by reading, writing, analyzing, and summarizing. The data sources used are literature sources, namely books and journals related to research topics. The data analysis technique uses content analysis. Content analysis is used to research the most relevant, relevant, and quite relevant literature. Then, a study was carried out by looking at the year of publication from the most up-to-date, up-to-date, to not up-to-date but having substance related to

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Gupta, Manik, and Nigel Phillips. "Knowledge Discovery Using Topological Analysis for Building Sensor Data." Sensors 20, no. 17 (2020): 4914. http://dx.doi.org/10.3390/s20174914.

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Distributed sensor networks are at the heart of smart buildings, providing greater detail and valuable insights into their energy consumption patterns. The problem is particularly complex for older buildings retrofitted with Building Energy Management Systems (BEMS) where extracting useful knowledge from large sensor data streams without full understanding of the underlying system variables is challenging. This paper presents an application of Q-Analysis, a computationally simple topological approach for summarizing large sensor data sets and revealing useful relationships between different va

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Hongwei, Tang, and He Wenxin. "3D Seismic Survey Technique in Less Explored Region." Open Civil Engineering Journal 9, no. 1 (2015): 155–58. http://dx.doi.org/10.2174/1874149501509010155.

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By summarizing the experiences of routine acquisition geometry designs, and using the 3D seismic survey data of a less explored region for instance, this paper put forward an acquisition geometry design method for less explored region plus the geological stratum calibration by reflection wave and time-depth conversion method. After drilling data and roadway data verification, the re-argumentation of acquisition geometry parameters for parameter determination and the forward modeling technique for geological stratum calibration and the stacking velocity time-depth conversion were proved to be v

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Zabrodina, Yuliya V., Gainyl U. Akhmedyanova, and Zaituna G. Khamidullina. "Prospects for the use of autologous platelet-rich plasma in reproductive medicine. Analysis of literary data." Consilium Medicum 24, no. 7 (2022): 481–84. http://dx.doi.org/10.26442/20751753.2022.7.201795.

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A brief review of the literature summarizing PubMed (MEDLINE) data is presented, which describes the use of autologous platelet-rich plasma in reproductive medicine. The main biologically active factors included in the composition of platelets are indicated: vascular endothelial growth factor, transforming growth factor, platelet growth factor and epidermal growth factor. The main biological changes occurring under the action of platelet activation are noted: control of migration, differentiation and proliferation of cells, accumulation of extracellular matrix, etc. The main methods and method

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Kassarnig, Valentin, and Franz Wotawa. "Evolutionary Propositionalization of Multi-Relational Data — Research Notes." International Journal of Software Engineering and Knowledge Engineering 28, no. 11n12 (2018): 1739–54. http://dx.doi.org/10.1142/s0218194018400260.

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Propositionalization has been proven to be a very effective solution for multi-relational data mining problems. The approaches usually follow a two-step principle: transforming the relational data into a single, flat table and applying a propositional learning algorithm. During the transformation, the target table gets expanded by adding many new features summarizing the information of the non-target tables. Based on the used feature construction strategy, this leads to a table of very high dimensionality with a lot of irrelevant and/or redundant features that can negatively affect the predict

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Wang, Yingzi, Muhammad Nazir Jan, Sisi Chu, and Yue Zhu. "Use of Big Data Tools and Industrial Internet of Things: An Overview." Scientific Programming 2020 (October 21, 2020): 1–10. http://dx.doi.org/10.1155/2020/8810634.

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Big data is ever playing an important role in the industry as well as many other organizations. With the passage of time, the volume of data is increasing. This increase will create huge bulk of data which needs proper tools and techniques to handle its management and organization. Different techniques and tools are being used to properly handle the management of data. A detailed report of these techniques and tools is needed which will help researchers to easily identify a tool for their data and take help to easily manage the data, organize the data, and extract meaningful information from i

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Rathore, Muhammad, and Jongwon Kim. "Spatio-temporal summarized visualization of smartX multi-view visibility in cloud-native edge boxes." Computer Science and Information Systems, no. 00 (2020): 34. http://dx.doi.org/10.2298/csis200317034r.

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The existing data summarization (and archival) techniques are generic and are not designed to leverage the unique characteristics of the spatio-temporal visualization at multi-resource level. In this paper, we propose and explore a family of data summaries that take advantage of the multiple layers i.e. physical/virtual resources with temporal and spatial correlation among distributed edge boxes. Significant challenges in measuring spatio-temporal data, however, contribute to both a tendency towards identifying efficient metrics with summarizing function alities and effective verification meth

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Li, Bingshan, Xiaowei Zhan, Mary-Kate Wing, Paul Anderson, Hyun Min Kang, and Goncalo R. Abecasis. "QPLOT: A Quality Assessment Tool for Next Generation Sequencing Data." BioMed Research International 2013 (2013): 1–4. http://dx.doi.org/10.1155/2013/865181.

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Background.Next generation sequencing (NGS) is being widely used to identify genetic variants associated with human disease. Although the approach is cost effective, the underlying data is susceptible to many types of error. Importantly, since NGS technologies and protocols are rapidly evolving, with constantly changing steps ranging from sample preparation to data processing software updates, it is important to enable researchers to routinely assess the quality of sequencing and alignment data prior to downstream analyses.Results.Here we describe QPLOT, an automated tool that can facilitate t

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Kong, Yuan. "A Discussion on the Curriculum Design of College English and Its Effective Implementation Based on the Need Analysis." Theory and Practice in Language Studies 8, no. 9 (2018): 1200. http://dx.doi.org/10.17507/tpls.0809.14.

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Through interviews with the specific needs of English abilities of the graduates in the jobs of different industries and different units, this paper will understand whether their English ability really exceeds the post demand, and will reflect on the College English curriculum according to the actual needs of English in the work. At the same time, after summarizing the English skills required by the graduates in the interview, this paper will further understand the specific situation and implementation effect of the University's highly valued English curriculum, and understand whether it meets

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Dr., Imran Khan. "A Comprehensive Study on Text Summarization using Deep Learning." Recent Trends in Data Knowledge Discovery and Data Mining 1, no. 2 (2025): 12–32. https://doi.org/10.5281/zenodo.15582189.

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<em>The internet revolution has resulted in an exponential increase in the volume of digital material available on the web. With the increasing rise of online platforms such as social networking sites, e-commerce websites, blogs, forums, and other digital services, people all over the world are continuously participating in virtual interactions. These platforms have evolved into critical communication, marketing, and collaboration tools, resulting in the everyday collection of massive amounts of textual data. If this data is properly processed, it can provide useful insights that can have a su

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Gunawan, Gunawan, Fitria Fitria, Esther Irawati Setiawan, and Kimiya Fujisawa. "Maximum Marginal Relevance and Vector Space Model for Summarizing Students' Final Project Abstracts." Knowledge Engineering and Data Science 6, no. 1 (2023): 57. http://dx.doi.org/10.17977/um018v6i12023p57-68.

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Automatic summarization is reducing a text document with a computer program to create a summary that retains the essential parts of the original document. Automatic summarization is necessary to deal with information overload, and the amount of data is increasing. A summary is needed to get the contents of the article briefly. A summary is an effective way to present extended information in a concise form of the main contents of an article, and the aim is to tell the reader the essence of a central idea. The simple concept of a summary is to take an essential part of the entire contents of the

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Hendra Wijaya. "Analysis of Deep K-Means and K-Means for Journal Summarization Using the BERTopic Method." Journal of Information Systems Engineering and Management 10, no. 43s (2025): 715–24. https://doi.org/10.52783/jisem.v10i43s.8470.

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This research aims to analyze the performance of Deep K-means and K-means methods in summarizing and clustering final project abstracts using the BERTopic technique. The methods used include preprocessing abstract data, applying Deep K-means and K-means clustering algorithms, and modeling topics with BERTopic. The dataset used was obtained from Kaggle and analyzed using the Python programming language. The results show that the Deep K-means method is able to produce more coherent topic clusters than conventional K-Means, with higher Silhouette Score values. The combination of clustering and to

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Halamka, John, and Paul Cerrato. "Understanding the role of digital platforms in technology readiness." Regenerative Medicine 16, no. 3 (2021): 207–13. http://dx.doi.org/10.2217/rme-2020-0135.

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State-of-the-art digital tools that take advantage of machine learning-derived algorithms and advanced data analytics have the potential to transform regenerative medicine by enabling investigators and clinicians to extract intelligence and actionable insights from published studies, electronic health records, pathology images and a variety of other sources. Used in isolation, however, these tools are not as effective as they can be integrated into a comprehensive strategy – a platform. We discuss the value of a platform strategy by summarizing several initiatives that have been launched at Ma

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Usha Rani, Rella, and Malladi Lakshmi Swarupa. "Leveraging Deep Learning and NLP for Automated Text Summarization in Healthcare." E3S Web of Conferences 619 (2025): 03005. https://doi.org/10.1051/e3sconf/202561903005.

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Given the abundance of information available on the Internet in the present era, it is imperative to develop a more effective method for swiftly and efficiently retrieving information. To extract data perfectly, consolidated data from lengthy written material. There is a vast amount of text content available on the Internet. Because of this, it can be difficult to find pertinent are from different documents. To extract useful aforementioned two issues, automatic text summarization is necessary. Text summarizing is the process of identifying the most important and noteworthy information from a

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Rao, Amrit Kumar. "Big Data in Genomics: Managing and Analyzing Large-Scale Clinical and Proteomic Data." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 3283–91. https://doi.org/10.22214/ijraset.2025.68053.

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Abstract: Big data has revolutionized genomics by providing new avenues to manage and analyse vast amounts of clinical and proteomic data. This report explores the role of big data in genomics, highlighting its significance in managing and analysing large-scale data generated through high-throughput sequencing technologies, clinical trials, and global biodiversity projects. The background and importance of big data in genomics are introduced, followed by an overview of the characteristics and types of big data relevant to the field. A thorough literature review evaluates key studies that have

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Chen, Peng, Xinyu Zhao, Lina Zeng, et al. "A Review of Research on SLAM Technology Based on the Fusion of LiDAR and Vision." Sensors 25, no. 5 (2025): 1447. https://doi.org/10.3390/s25051447.

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In recent years, simultaneous localization and mapping with the fusion of LiDAR and vision fusion has gained extensive attention in the field of autonomous navigation and environment sensing. However, its limitations in feature-scarce (low-texture, repetitive structure) environmental scenarios and dynamic environments have prompted researchers to investigate the use of combining LiDAR with other sensors, particularly the effective fusion with vision sensors. This technique has proven to be highly effective in handling a variety of situations by fusing deep learning with adaptive algorithms. Li

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Qin, Mingzhi, and Qingtao Wu. "A Review of Blockchain-Based Research on E-Health Data Sharing." International Journal of Computer Science and Information Technology 3, no. 1 (2024): 37–43. http://dx.doi.org/10.62051/ijcsit.v3n1.06.

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With the development of medical data informatization, the data security, data privacy, and data controllability of electronic medical data with patient's personal privacy have gained social attention. Blockchain technology has decentralized characteristics, and the development of blockchain technology provides an effective solution for the secure sharing of e-medical data. Many scholars have proposed e-medical data security sharing solutions based on blockchain technology, and these solutions have attempted to solve the security problems encountered in sharing traditional e-medical data. By su

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Et al., Zadrian Ardi. "Controversy in Determining Criteria and Categories in Summarizing and Exploring The Research Data; Analysis of Assessment Procedures in The Social Science Research." Psychology and Education Journal 58, no. 1 (2021): 4109–15. http://dx.doi.org/10.17762/pae.v58i1.1474.

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Determination of criteria and categorization of data in measurement is a crucial moment when processing research data. Overview, exploration and presentation of data will be effective and valid if the criteria set meets the requirements, both from a theoretical and statistical perspective. However, the fact that often arises, especially in beginner researchers made a mistaken in determining the criteria and categories. These errors are often indicated in the form of incomprehension and negligence of researchers in placing data types with the type of methodology. This paper describes various er

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Oswald, Frederick L., Mica R. Endsley, Jessie Chen, et al. "The National Academies Board on Human-Systems Integration (BOHSI) Panel: Human-AI Teaming: Research Frontiers." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (2022): 130–34. http://dx.doi.org/10.1177/1071181322661007.

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The National Academies recently issued a consensus study report summarizing the state of the art and research needs relating to Human-AI teaming, especially in the context of dynamic, high-risk environments such as multi-domain military operations. This consensus study was conducted by the National Academies Board on Human-Systems Integration (BOHSI). This panel, organized by BOHSI, brings together prominent researchers, including several members of the consensus committee, to discuss the state of the art and research frontiers for development of effective human-AI teams that can operate resil

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MOLNAR, O. S., F. A. VAZHYNSKYY, and A. V. KOLODIYCHUK. "Conceptual approaches to the formation of an effective sales policy of enterprises." Market Relations Development in Ukraine №7-8(266-267)2023 153 (October 9, 2023): 86–90. https://doi.org/10.5281/zenodo.8420844.

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The subject of the study is conceptual approaches to the formation of an effective sales policy of enterprises. The purpose of the study is to investigate the concept of an effective sales policy of the enterprise. Research methods. The work uses the dialectical method of scientific knowledge, the method of analysis and synthesis, the comparative method, and the method of summarizing data. Work results. The article defines the directions for planning effective sales activities. The main sales methods are given. The factors that must be taken into account by the enterprise when forming an effec

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Adhikary, Prottay Kumar, Aseem Srivastava, Shivani Kumar, et al. "Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark Study." JMIR Mental Health 11 (July 23, 2024): e57306. http://dx.doi.org/10.2196/57306.

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Background Comprehensive session summaries enable effective continuity in mental health counseling, facilitating informed therapy planning. However, manual summarization presents a significant challenge, diverting experts’ attention from the core counseling process. Leveraging advances in automatic summarization to streamline the summarization process addresses this issue because this enables mental health professionals to access concise summaries of lengthy therapy sessions, thereby increasing their efficiency. However, existing approaches often overlook the nuanced intricacies inherent in co

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Omar, Nasiroh, and Nur Naelah ‘Ariefah Nordin. "Gender Representation of 20 years Malaysian Films based on Andy Kirk Dynamic Visualization Framework." Mathematical Sciences and Informatics Journal 2, no. 2 (2021): 15–25. http://dx.doi.org/10.24191/mij.v2i2.13909.

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The role of visualization in journalism evolved when dynamic visualization was introduced. Previously, data visualization in media were constrained with the static nature of the media itself. Nowadays, front-end technology advancement allows for dynamic visualization included in journalism or as a standalone itself. Dynamic visualization ables to provide a compelling story and also effective in summarizing large amounts of data into useful insights. Using Andy Kirk’s framework of creating effective visualization, this paper aims to provide insightful and dynamic visualization on the evolution

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Staiger, Douglas O., and Jonah E. Rockoff. "Searching for Effective Teachers with Imperfect Information." Journal of Economic Perspectives 24, no. 3 (2010): 97–118. http://dx.doi.org/10.1257/jep.24.3.97.

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Over the past four decades, empirical researchers—many of them economists—have accumulated an impressive amount of evidence on teachers. In this paper, we ask what the existing evidence implies for how school leaders might recruit, evaluate, and retain teachers. We begin by summarizing the evidence on five key points, referring to existing work and to evidence we have accumulated from our research with the nation's two largest school districts: Los Angeles and New York City. First, teachers display considerable heterogeneity in their effects on student achievement gains. Second, estimates of t

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Vatsalya, Samarth. "Remote Sensing Image Classification using Machine Learning Algorithms." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 2343–49. http://dx.doi.org/10.22214/ijraset.2023.54049.

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Abstract: The classification of images can be influenced by various factors. When multiple sources of data are available for earth exploration, extracting valuable information or achieving effective outcomes can be both fascinating and challenging. Remote Sensing Images (RSI) classification plays a crucial role in remote sensing applications and serves as the foundation for efficient classification. Various classifiers are employed to classify different types of targets in remote sensing images. Achieving improved target classification is of utmost importance in both military and civilian doma

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D. D Sarpate. "Q&A In Financial Queries Using Zero-Shot Learning with LLM for Novel Task Understanding." Journal of Information Systems Engineering and Management 10, no. 42s (2025): 629–37. https://doi.org/10.52783/jisem.v10i42s.7922.

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For understanding novel tasks, Zero-Shot Learning (ZSL) in combination with Large Language Models (LLMs) exhibits immense potential. By solely depending on task descriptions or guidelines provided in natural language, LLMs can deduce solutions without requiring explicit training data. For instance, an LLM could be assigned the task of summarizing a newly introduced scientific principle or responding to inquiries on an unfamiliar subject. The model's capability to understand tasks from linguistic indicators and apply pre-acquired knowledge is what makes ZSL particularly effective. Despite these

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Rinaldi, Antonio M. "Web Summarization and Browsing Through Semantic Tag Clouds." International Journal of Intelligent Information Technologies 15, no. 3 (2019): 1–23. http://dx.doi.org/10.4018/ijiit.2019070101.

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The need to manage electronic documents is an open issue in the digital era. It becomes a challenging problem on the internet where a large amount of data needs even more efficient and effective methods and techniques for mining and representing information. In this context, document summarization, browsing processes and visualization techniques have had a great impact on several dimensions of user information perception. In this context, the use of ontologies for knowledge representation has rapidly grown in the last years in several application domains together with social-based techniques s

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Harahap, Muhammad Yunan, Rustam Ependi, Abdi Syahrial Harahap, and Fadli Nurul Ikhsan. "Keterampilan Membuka Dan Menutup Pelajaran Yang Efektif Dalam Konteks Pendidikan Islam Di Madrasah Aliyah Swasta Amaliyah Sunggal." JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah 9, no. 4 (2024): 552–65. https://doi.org/10.24815/jimps.v9i4.32900.

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This research explores effective opening and closing skills in the context of Islamic Religious Education at Madrasah Aliyah Swasta Amaliyah Sunggal. The method used in this research is qualitative while data collection through observation, interview and document study. The purpose of this study was to explore the skills of opening and closing an effective lesson at the private madrasah aliyah Amaliyah Sunggal. The results showed that opening the lesson involved the use of prayer, brief motivation, and linking the material to real life, while effective closing included summarizing the material

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Susanto, Yanuar Bagus, Akhmad Suharto, and Ira Puspitadewi. "ANALISIS STRATEGI PEMASARAN UMKM BATIK SEMBORO DENGAN METODE STP (SEGMENTATION, TARGETING, POSITIONING) UNTUK MENINGKATKAN DAYA SAING." Jurnal Mahasiswa Entrepreneurship (JME) 2, no. 1 (2023): 143. http://dx.doi.org/10.36841/jme.v2i1.2664.

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This study aims to find out how effective the implementation of the Segmenting, Targeting, and Positioning (STP) strategy implemented by Batik Semboro is in increasing its competitiveness. In this study, researchers used descriptive analysis methods with a qualitative approach, which is a research method for describing, summarizing various social phenomena that exist in society, as well as drawing surface social reality as characteristics, characters, traits, models, signs or descriptions of phenomena. Data collection techniques used by researchers are observation, interviews, and documentatio

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inci, edanur. "Investigation of Infographic Design and Summarizing Processes from the Biology Texts of Primary School Students in Terms of Different Variables." Journal of Higher Education and Science 11, no. 3 (2021): 536–44. http://dx.doi.org/10.5961/jhes.2021.473.

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Technological developments have increased the importance of presenting and the processing of information as effective and memorable in the field of education. The aim of the study is to examine the effect of performing biology subjects in the elementary school science lessons with infographic design tasks in terms of the effects on students’ cognitive structures and knowledge levels in the learning - teaching process. As the research method was used the pretest-posttest control group design from the experimental research models. The sample of the research consists of 4th grade students of a pr

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Dubey, Anand Kumar. "AI LLM Integration." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1842–49. http://dx.doi.org/10.22214/ijraset.2023.57731.

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Abstract: This study investigates the integration and utilization of advanced language models in diverse applications, ranging from creative content generation to sentiment analysis, emotion analysis, text completion, and article summarization. The study leverages state-of-the-art models from Hugging Face and OpenAI, exploring their capacities in addressing distinct facets of natural language processing. The primary focus is on the capabilities and limitations of language models in generating creative content, discerning sentiment in text, identifying emotional nuances, completing text prompts

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Quattrin, Rosanna, Laura Calligaris, Carla Londero, Enrico Zalateu, and Silvio Brusaferro. "Shift-to-shift handoff: A comparison between two methods of conveying essential information in a University Hospital in North-eastern Italy." Journal of Hospital Administration 3, no. 5 (2014): 39. http://dx.doi.org/10.5430/jha.v3n5p39.

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Objective: The present study focuses on effective communication among nurses during a shift-to-shift handoff. Methods: The completeness of data conveyed during the shift-to-shift handoff was compared in two University Hospital Units, before and after the introduction of a pre-printed sheet summarizing the most important patients’ piece of information. The study took place in a University Hospital located in North-eastern Italy. In the first study phase 111 single patient’s handoffs were analyzed: 52 in Operative Unit 1 (OU1) and 59 in Operative Unit 1 (OU2). In the second phase of the study 39

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Wiencierz, Christian, and Ulrike Röttger. "The use of big data in corporate communication." Corporate Communications: An International Journal 22, no. 3 (2017): 258–72. http://dx.doi.org/10.1108/ccij-02-2016-0015.

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Purpose The purpose of this paper is to illustrate the current state of research on the significance of big data in and for corporate communication and to introduce a framework which provides specific connecting points for future research. This is achieved by summarizing and reviewing the insights provided by relevant articles in the most significant scholarly journals. The paper also investigates trends in the literature. Design/methodology/approach On the basis of a systematic literature review, 53 key articles from 2010 to 2015 were further analyzed. Findings The literature review illustrat

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McKoy, Deborah, Ruby Kosewicz-Strickland, and Pixie Popplewell. "Empowerment as Prevention: How Youth-Driven Initiatives Transform Frameworks for Change." Youth 5, no. 1 (2025): 17. https://doi.org/10.3390/youth5010017.

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Youth-led action research has significantly influenced local and statewide policies aimed at supporting students experiencing homelessness in California. This study employs a Youth Participatory Action Research (YPAR) methodology, summarizing five years of research conducted by high school student cohorts and UC Berkeley graduate students to examine effective strategies for preventing and addressing student homelessness. The research engaged over 240 high school students, nine graduate research fellows, 120 university student mentors, and eight civic and community organizations through data co

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Singh, Alka. "A review on prediction of diabetes type 2 by machine learning techniques." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 5638–51. http://dx.doi.org/10.17762/turcomat.v12i3.2238.

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Machine learning is considered to be one of the most promising tools when it comes to working with heterogeneous data. It provides a new dimension which enables one to extract relevant data and take decision for the effective functioning of the network, making use of network generated data. Every sphere of our life is now dependent on machine learning. It has flourished in every dimension. Making it versatile and ever demanding. Department of healthcare contains very abundant and sensitive information which is needed to be carefully handled. Diabetes mellitus is increasing exponentially

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