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Journal articles on the topic 'Extraction de graphes'

Author: Grafiati

Published: 28 September 2022

Last updated: 31 July 2025

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1

Ahmad, Jawad, Abdur Rehman, Hafiz Tayyab Rauf, Kashif Javed, Maram Abdullah Alkhayyal, and Abeer Ali Alnuaim. "Service Recommendations Using a Hybrid Approach in Knowledge Graph with Keyword Acceptance Criteria." Applied Sciences 12, no. 7 (2022): 3544. http://dx.doi.org/10.3390/app12073544.

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Businesses are overgrowing worldwide; people struggle for their businesses and startups in almost every field of life, whether industrial or academic. The businesses or services have multiple income streams with which they generate revenue. Most companies use different marketing and advertisement strategies to engage their customers and spread their services worldwide. Service recommendation systems are gaining popularity to recommend the best services and products to customers. In recent years, the development of service-oriented computing has had a significant impact on the growth of busines

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (March 7, 2019): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.3.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integra

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Hernández-García, Ángel, and Miguel Ángel Conde-González. "Bridging the Gap between LMS and Social Network Learning Analytics in Online Learning." Journal of Information Technology Research 9, no. 4 (2016): 1–15. http://dx.doi.org/10.4018/jitr.2016100101.

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Despite the great potential of social network analysis (SNA) methods and visualizations for learning analytics in computer-supported collaborative learning (CSCL), these approaches have not been fully explored due to two important barriers: the scarcity and limited functionality of built-in tools in Learning Management Systems (LMS), and the difficulty to import educational data from formal virtual learning environments into social network analysis programs. This study aims to cover that gap by introducing GraphFES, an application and web service for extraction of interaction data from Moodle

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REBENCIUC, Ioana, and Ovidiu TIȚA. "Influence of Pectolytic Enzymes on the Quality of Wine Maceration." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Animal Science and Biotechnologies 75, no. 1 (2018): 53. http://dx.doi.org/10.15835/buasvmcn-asb:000417.

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Obtaining high-quality wines with a registered designation of origin means making the most of the specific features of the variety and those imprinted with technology and the place of harvesting. The aroma is due to the chemical compounds of terpenic nature that accumulate in the grapes (variety flavors) and the secondary aromas that are formed during the alcoholic fermentation and the aging period of the wines (Amrani, and Glories, 1995). The wine-making of the varieties is followed by the appreciation of the primary grapes. This is achieved by preferential maceration of the must by means of

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Psallidas, Fotis, Ashvin Agrawal, Chandru Sugunan, et al. "OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance from Database Query Event Logs." Proceedings of the VLDB Endowment 16, no. 12 (2023): 3662–75. http://dx.doi.org/10.14778/3611540.3611555.

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Provenance encodes information that connects datasets, their generation workflows, and associated metadata (e.g., who or when executed a query). As such, it is instrumental for a wide range of critical governance applications (e.g., observability and auditing). Unfortunately, in the context of database systems, extracting coarse-grained provenance is a long-standing problem due to the complexity and sheer volume of database workflows. Provenance extraction from query event logs has been recently proposed as favorable because, in principle, can result in meaningful provenance graphs for provena

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (December 10, 2018): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.1.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we develop

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Cramond, Fala, Alison O'Mara-Eves, Lee Doran-Constant, Andrew SC Rice, Malcolm Macleod, and James Thomas. "The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews." Wellcome Open Research 3 (January 25, 2019): 157. http://dx.doi.org/10.12688/wellcomeopenres.14738.2.

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Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integra

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8

Yan, Rongen, Dongmei Li, Yan Wu, Depeng Dang, Ye Tao, and Shaofei Wang. "NAS-CRE: Neural Architecture Search for Context-Based Relation Extraction." Applied Sciences 14, no. 23 (2024): 10960. http://dx.doi.org/10.3390/app142310960.

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Relation extraction, a crucial task in natural language processing (NLP) for constructing knowledge graphs, entails extracting relational semantics between pairs of entities within a sentence. Given the intricacy of language, a single sentence often encompasses multiple entities that mutually influence one another. Recently, various iterations of recurrent neural networks (RNNs) have been introduced into relation extraction tasks, where the efficacy of neural network structures directly influences task performance. However, many neural networks necessitate manual determination of optimal param

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9

Vijayam, Bhuwaneswaran, Siew Ping Lau, Jing Wen Wong, et al. "Validation of Glycemic Index Values Represented as Bar Graphs in Scholarly Articles for Clinical Nutrition Application." Journal of Health and Quality of Life 1, no. 1 (2024): 1–15. http://dx.doi.org/10.37934/jhqol.1.1.115.

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Glycemic index (GI) has been a proven clinical nutrition tool. It has been utilized in chronic diseases such as PCOS, diabetes, obesity and metabolic syndrome. The GI value of a test food is the ratio of the glucose response over 2 hours against the reference food. The references food is usually either glucose or bread. GI values may often be directly available as values in texts, tables, or figures. The indirect values may be represented as values, images or both values and, concentration of glucose over time or GI values. Less ideally, some GI data are only presented in graphs. Data from the

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Bhuwaneswaran Vijayam, Lau Siew Ping, Wong Jing Wen, et al. "Validation of Glycemic Index Values Represented as Bar Graphs in Scholarly Articles for Clinical Nutrition Application." Journal of Health and Quality of Life 1, no. 1 (2024): 1–15. http://dx.doi.org/10.37934/hqol.1.1.115.

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Glycemic index (GI) has been a proven clinical nutrition tool. It has been utilized in chronic diseases such as PCOS, diabetes, obesity and metabolic syndrome. The GI value of a test food is the ratio of the glucose response over 2 hours against the reference food. The references food is usually either glucose or bread. GI values may often be directly available as values in texts, tables, or figures. The indirect values may be represented as values, images or both values and, concentration of glucose over time or GI values. Less ideally, some GI data are only presented in graphs. Data from the

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Vijayam, Bhuwaneswaran, Siew Ping Lau, Jing Wen Wong, et al. "Validation of Glycemic Index Values Represented as Bar Graphs in Scholarly Articles for Clinical Nutrition Application." Journal of Health and Quality of Life 1, no. 1 (2025): 1–15. https://doi.org/10.37934/hqol.1.1.115a.

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Glycemic index (GI) has been a proven clinical nutrition tool. It has been utilized in chronic diseases such as PCOS, diabetes, obesity and metabolic syndrome. The GI value of a test food is the ratio of the glucose response over 2 hours against the reference food. The references food is usually either glucose or bread. GI values may often be directly available as values in texts, tables, or figures. The indirect values may be represented as values, images or both values and, concentration of glucose over time or GI values. Less ideally, some GI data are only presented in graphs. Data from the

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Goharshady, Amir Kafshdar, Chun Kit Lam, and Lionel Parreaux. "Fast and Optimal Extraction for Sparse Equality Graphs." Proceedings of the ACM on Programming Languages 8, OOPSLA2 (2024): 2551–77. http://dx.doi.org/10.1145/3689801.

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Equality graphs (e-graphs) are used to compactly represent equivalence classes of terms in symbolic reasoning systems. Beyond their original roots in automated theorem proving, e-graphs have been used in a variety of applications. They have become particularly important as the key ingredient in the popular technique of equality saturation, which has notable applications in compiler optimization, program synthesis, program verification, and symbolic execution, among others. In a typical equality saturation workflow, an e-graph is used to store a large number of equalities that are generated by

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Ringwald, Célian, Fabien Gandon, Catherine Faron, Franck Michel, and Hanna Abi Akl. "Well-Written Knowledge Graphs: Most Effective RDF Syntaxes for Triple Linearization in End-to-End Extraction of Relations from Texts (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 23631–32. http://dx.doi.org/10.1609/aaai.v38i21.30502.

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Seq-to-seq generative models recently gained attention for solving the relation extraction task. By approaching this problem as an end-to-end task, they surpassed encoder-based-only models. Little research investigated the effects of the output syntaxes on the training process of these models. Moreover, a limited number of approaches were proposed for extracting ready-to-load knowledge graphs following the RDF standard. In this paper, we consider that a set of triples can be linearized in many different ways, and we evaluate the combined effect of the size of the language models and different

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Shi, Wei, Weiguo Zheng, Jeffrey Xu Yu, Hong Cheng, and Lei Zou. "Keyphrase Extraction Using Knowledge Graphs." Data Science and Engineering 2, no. 4 (2017): 275–88. http://dx.doi.org/10.1007/s41019-017-0055-z.

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Taran, Nicolae, Boris Morari, and Olga Soldatenco. "INFLUENCE OF DIFFERENT TECHNOLOGICAL PROCESSES ON THE CONTENT OF BIOLOGICALLY ACTIVE SUBSTANCES AT THE PRODUCTION OF DRY RED WINE FROM THE CABERNET SAUVIGNON VARIETY." Akademos 60, no. 1 (2021): 63–67. http://dx.doi.org/10.52673/18570461.21.1-60.08.

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This research was focused on the influence of different fermentation-maceration processes for the optimization of the extraction of anthocyanins, tannins and biologically active substances from grapes of the Cabernet Sauvignon variety and their impact on the quality during dry red wine production. It was determined that increasing the duration of the fermentation-maceration process and extracting 20 % of the juice from the must allow the production of dry red wines with high proanthocyanidin content.

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Ruseva, Olga, Eugenia Covaliov, Vladislav Resitca, Olga Deseatnicova, Tatiana Capcanari, and Natalia Suhodol. "Harnessing grape pomace: nutritional aspects, recovery and extraction techniques for health benefits." Journal of Engineering Science 31, no. 1 (2024): 112–25. https://doi.org/10.52326/jes.utm.2024.31(1).09.

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Nowadays, grapes represent the third most widely cultivated horticulture crop in the world. For the Republic of Moldova, grapes have been recognized as the most culturally important crop. About 70% of the total production of Moldovan grapes is processed in the wine industry, 30 % of which are by-products that tend to be not fully exploited, being frequently burned or landfilled. Due to its chemical composition, grape pomace is one type of agricultural waste that can be used to achieve sustainability in the food business by converting waste into useful resources. In this sense, the pomace chemi

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Liu, Kang, Wenqing Dai, Xunyuan Liu, Mengtao Kang, and Runshi Ji. "NHSH: Graph Hybrid Learning with Node Homophily and Spectral Heterophily for Node Classification." Symmetry 17, no. 1 (2025): 115. https://doi.org/10.3390/sym17010115.

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Graph Neural Network (GNN) is an effective model for processing graph-structured data. Most GNNs are designed to solve homophilic graphs, where all nodes belong to the same category. However, graph data in real-world applications are mostly heterophilic, and homophilic GNNs cannot handle them well. To address this, we propose a novel hybrid-learning framework based on Node Homophily and Spectral Heterophily (NHSH) for node classification in graph networks. NHSH is designed to achieve state-of-the-art or superior performance on both homophilic and heterophilic graphs. It includes three core mod

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Iglesias-Carres, Lisard, Anna Mas-Capdevila, Lucía Sancho-Pardo, et al. "Optimized Extraction by Response Surface Methodology Used for the Characterization and Quantification of Phenolic Compounds in Whole Red Grapes (Vitis vinifera)." Nutrients 10, no. 12 (2018): 1931. http://dx.doi.org/10.3390/nu10121931.

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Scientific research has focused on the characterization of bioactive polyphenols from grape seeds and skins, and the pulp has often been overlooked. However, since the beneficial properties of grapes are associated with the consumption of whole fruit, a full extraction and posterior characterization of the phenolic compounds in whole grapes is required to identify the involved bioactive compounds. Such methodologies are not currently available for the whole edible parts of red grapes. This study aimed to determine the best polyphenol extraction conditions of whole red grapes, and apply the met

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Yang Deng, Yang Deng, Bangchao Wang Yang Deng, Zhongyuan Hua Bangchao Wang, Yong Xiao Zhongyuan Hua, and Xingfu Li Yong Xiao. "A Knowledge Graph Construction Method for Software Project Based on CAJP." 網際網路技術學刊 24, no. 6 (2023): 1229–39. http://dx.doi.org/10.53106/160792642023112406006.

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<p>In recent years, there has been increasing interest in using knowledge graphs (KGs) to help stakeholders organize and better understand the connections between various artifacts during software development. However, extracting entities and relationships automatically and accurately in open-source projects is still a challenge. Therefore, an efficient method called Concise Annotated JavaParser (CAJP) has been proposed to support these extraction activities, which are vitally important for KG construction. The experimental result shows that CAJP improves the accuracy and type of entity

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Czyrski, Andrzej, and Hubert Jarzębski. "Response Surface Methodology as a Useful Tool for Evaluation of the Recovery of the Fluoroquinolones from Plasma—The Study on Applicability of Box-Behnken Design, Central Composite Design and Doehlert Design." Processes 8, no. 4 (2020): 473. http://dx.doi.org/10.3390/pr8040473.

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The aim of this study was to find the best design that is suitable for optimizing the recovery of the representatives of the 2nd, 3rd and 4th generation of fluoroquinolones. The following designs were applied: Central Composite Design, Box–Behnken Design and Doehlert Design. The recovery, which was a dependent variable, was estimated for liquid–liquid extraction. The time of shaking, pH, and the volume of the extracting agent (dichloromethane) were the independent variables. All results underwent the statistical analysis (ANOVA), which indicated Central Composite Design as the best model for e

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Feng, Yanna, Feng Zhang, Yongheng Zhang, Jiangang Dong, and PengJu Wang. "A hybrid extraction model for semantic knowledge discovery of water conservancy big data." PeerJ Computer Science 11 (July 7, 2025): e2960. https://doi.org/10.7717/peerj-cs.2960.

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To address the growing demand for efficient public opinion analysis in water conservancy and related domains, as well as the inefficiencies and limited scalability of existing automated web data extraction algorithms for multi-source datasets, this research integrates advanced technologies including big data analytics, natural language processing, and deep learning. A novel, transferable web information extraction model based on deep learning (WIEM-DL) is proposed, leveraging knowledge graphs, machine learning, and ontology-based methods. This model is designed to adapt to varying website stru

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Tsiropoulos, Nicholas G., Konstantinos Liapis, Dimitrios T. Likas, and George E. Miliadis. "Determination of Spiroxamine Residues in Grapes, Must, and Wine by Gas Chromatography/Ion Trap-Mass Spectrometry." Journal of AOAC INTERNATIONAL 88, no. 6 (2005): 1834–39. http://dx.doi.org/10.1093/jaoac/88.6.1834.

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Abstract Analytical methodology was developed and validated for the determination of spiroxamine residues in grapes, must, and wine by gas chromatography/ion trap-mass spectrometry (GC/IT-MS). Two extraction procedures were used: the first involved grapes, must, and wine extraction with alkaline cyclohexane–dichloromethane (9 + 1, v/v) solution, and the second grape extraction with acetone, dichloromethane, and petroleum ether. In both procedures, the extract was centrifuged, evaporated to dryness, and reconstituted in cyclohexane or 2,2,4-trimethylpentane–toluene (9 + 1, v/v), respectively. S

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Al Shammari Abdullah, Amirah. "Graph-based Model for Keyphrases Extraction from Arabic Text (GMKE)." International Journal of Science and Research (IJSR) 12, no. 6 (2023): 2755–61. http://dx.doi.org/10.21275/sr23601112115.

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GLAVAŠ, GORAN, and JAN ŠNAJDER. "Construction and evaluation of event graphs." Natural Language Engineering 21, no. 4 (2014): 607–52. http://dx.doi.org/10.1017/s1351324914000060.

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AbstractEvents play an important role in natural language processing and information retrieval due to numerous event-oriented texts and information needs. Many natural language processing and information retrieval applications could benefit from a structured event-oriented document representation. In this paper, we proposeevent graphsas a novel way of structuring event-based information from text. Nodes in event graphs represent the individual mentions of events, whereas edges represent the temporal and coreference relations between mentions. Contrary to previous natural language processing re

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Bahtaji, Michael Allan A. "Improving students graphing skills and conceptual understanding using explicit Graphical Physics Instructions." Cypriot Journal of Educational Sciences 15, no. 4 (2020): 843–53. http://dx.doi.org/10.18844/cjes.v15i4.5063.

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The study presented investigates the effects of supportive graphical interventions on the graphing skills and conceptual understanding of students in physics. In this study, the first group of participants was presented with ready-made graphs during the instruction, the second group was instructed on the proper construction and extraction of graphs, while the third group was instructed to construct graphs independently. The groups were compared with respect to their scores in the graphing skills and achievement tests before and after the instructions. The group that received supportive interve

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Wu, Shangjia, Zhiqiang Guo, Xiaofeng Huang, Jialiang Zhang, and Yingfang Ni. "SPECE: Subject Position Encoder in Complex Embedding for Relation Extraction." Electronics 13, no. 13 (2024): 2571. http://dx.doi.org/10.3390/electronics13132571.

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As a crucial component of many natural language processing tasks, extracting entities and relations transforms unstructured text information into structured data, providing essential support for constructing knowledge graphs (KGs). However, current entity relation extraction models often prioritize the extraction of richer semantic features or the optimization of relation extraction methods, overlooking the significance of positional information and subject characteristics in this task. To solve this problem, we introduce the subject position-based complex exponential embedding for entity rela

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Dang, Xiaochao, Han Deng, Xiaohui Dong, Zhongyan Zhu, Fenfang Li, and Li Wang. "MHlinker: Research on a Joint Extraction Method of Fault Entity Relationship for Mine Hoist." Electronics 12, no. 16 (2023): 3430. http://dx.doi.org/10.3390/electronics12163430.

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Triplet extraction is the key technology to automatically construct knowledge graphs. Extracting the triplet of mechanical equipment fault relationships is of great significance in constructing the fault diagnosis of a mine hoist. The pipeline triple extraction method will bring problems such as error accumulation and information redundancy. The existing joint learning methods cannot be applied to fault texts with more overlapping relationships, ignoring the particularity of professional knowledge in the field of complex mechanical equipment faults. Therefore, based on the Chinese pre-trained

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Yusuf, Muhammad, Sri Indriati, Muhammad Irsal, Mahyati Latief, Nuraeni Umar, and Nur Fitriani Usdyana Attahmid. "Extraction Optimization of Pigeon Pea Seed Protein and Yield Using Response Surface Methodology." INTEK: Jurnal Penelitian 9, no. 1 (2022): 66. http://dx.doi.org/10.31963/intek.v9i1.3530.

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Pigeon Pea (Casanus Cajan L.) is one of the local foods in South Sulawesi. Pigeon pea seeds contain protein that the body can absorb. This study aims to determine the optimum operating conditions for extracting pigeon pea on protein and yield using Ultrasonic-Assisted Extraction (UAE). Response Surface Methodology (RSM) with Box-Behnken Design (BBD) was used by considering three variables, time (30, 40, and 50 min), temperature (40, 50, and 60oC), and methanol concentration (50, 70, and 90%). The experiment results show that yield ranges from 8.85663% to 31.4766% and 46.1538 mg/l to 15584.6 mg

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Chen, Dr Mingyu L., and Muhammad Siddiqui. "CODE-SWITCHED RELATION EXTRACTION: A NOVEL DATASET AND TRAINING METHODOLOGY." International Journal of Modern Computer Science and IT Innovations 2, no. 2 (2025): 1–9. https://doi.org/10.55640/ijmcsit-v02i02-01.

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Relation Extraction (RE) is a fundamental task in Natural Language Processing (NLP) crucial for constructing knowledge graphs and enhancing information retrieval. While significant progress has been made in monolingual and cross-lingual RE, the unique challenges posed by code-switched (mix-lingual) text remain largely underexplored due to a scarcity of dedicated datasets and tailored methodologies. This paper introduces a novel, large-scale dataset specifically designed for code-switched relation extraction. Furthermore, we propose an effective training methodology tailored to capture the comp

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Zhou, Wei. "Research on information extraction technology applied for knowledge graphs." Applied and Computational Engineering 4, no. 1 (2023): 26–31. http://dx.doi.org/10.54254/2755-2721/4/20230340.

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Information extraction is an important part of natural language processing and is an important basis for building question and answer systems and knowledge graphs. A growing number of new technologies are being applied to information extraction with the development of deep learning techniques. As a first step, this paper introduces information extraction techniques and their main tasks, then describes the development history of information extraction techniques, and introduces the practice and application of different types of information extraction techniques in knowledge graph construction,

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Morris, J. R., W. A. Sistrunk, J. Junek, and C. A. Sims. "Effects of Fruit Maturity, Juice Storage, and Juice Extraction Temperature on Quality of ‘Concord’ Grape Juice." Journal of the American Society for Horticultural Science 111, no. 5 (1986): 742–46. http://dx.doi.org/10.21273/jashs.111.5.742.

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Abstract A factorial study was designed to examine the effects of fruit maturities, juice extraction temperatures, storage time, and storage temperature on the quality of ‘Concord’ grape (Vitis labrusca L.) juice. Mature grapes produced juice with superior sensory quality and better objective color initially than less-mature grapes, but juice from grapes at both maturities had similar sensory quality after 18 months. The high extraction temperature (99°C) resulted in juice with better color initially than extraction at 60°, but juice extracted at 85° or 99° resulted in greater browning and los

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XU Chenjie, 徐陈捷, 李丹 LI Dan та 孔繁锵 KONG Fanqiang. "基于动态图-谱特征提取的高光谱图像分类方法". ACTA PHOTONICA SINICA 54, № 4 (2025): 0410002. https://doi.org/10.3788/gzxb20255404.0410002.

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Boné, João, Mariana Dias, João C. Ferreira, and Ricardo Ribeiro. "DisKnow: A Social-Driven Disaster Support Knowledge Extraction System." Applied Sciences 10, no. 17 (2020): 6083. http://dx.doi.org/10.3390/app10176083.

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This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time vis

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Li, Bei, Changbiao Li, Jianwei Sun, Xu Zeng, Xiaofan Chen, and Jing Zheng. "ERNIE-UIE: Advancing information extraction in Chinese medical knowledge graph." PLOS One 20, no. 5 (2025): e0325082. https://doi.org/10.1371/journal.pone.0325082.

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Background The field of information extraction (IE) is currently exploring more versatile and efficient methods for minimization of reliance on extensive annotated datasets and integration of knowledge across tasks and domains. Objective We aim to evaluate and refine the application of the universal IE (UIE) technology in the field of Chinese medical expertise in terms of processing accuracy and efficiency. Methods Our model integrates ontology modeling, web scraping, UIE, fine-tuning strategies, and graph databases, thereby covering knowledge modeling, extraction, and storage techniques. The

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Liu, Bin, Jialin Tao, Wanyuan Chen, et al. "Integration of Relation Filtering and Multi-Task Learning in GlobalPointer for Entity and Relation Extraction." Applied Sciences 14, no. 15 (2024): 6832. http://dx.doi.org/10.3390/app14156832.

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The rise of knowledge graphs has been instrumental in advancing artificial intelligence (AI) research. Extracting entity and relation triples from unstructured text is crucial for the construction of knowledge graphs. However, Chinese text has a complex grammatical structure, which may lead to the problem of overlapping entities. Previous pipeline models have struggled to address such overlap problems effectively, while joint models require entity annotations for each predefined relation in the set, which results in redundant relations. In addition, the traditional models often lead to task im

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Yoshikawa, Tomohiro, Yuki Uchida, Takeshi Furuhashi, Eiji Hirao, and Hiroto Iguchi. "Extraction of Evaluation Keywords for Analyzing Product Evaluation in User-Reviews Using Hierarchical Keyword Graph." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 4 (2009): 457–62. http://dx.doi.org/10.20965/jaciii.2009.p0457.

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Recently, the number of sites on the Internet which give users the opportunity to write their ideas and opinions for the public to read have been increasing. In addition, the number of people who want to know the opinions of others about interesting products has also been increasing. However, it is very difficult for people to read complete reviews on the Internet. This study tries to develop a new system for the analysis of reviews, a system which shows evaluation information about products using graphs of evaluation keywords. This paper focuses on the extraction of evaluation keywords from r

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Khan, Naeemullah, Mustafa Tuzen, and Tasneem Gul Kazi. "Simple and Rapid Dual-Dispersive Liquid–Liquid Microextraction as an Innovative Extraction Method for Uranium in Real Water Samples Prior to the Determination of Uranium by a Spectrophotometric Technique." Journal of AOAC INTERNATIONAL 100, no. 6 (2017): 1848–53. http://dx.doi.org/10.5740/jaoacint.17-0054.

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Abstract An innovative, rapid, and simple dual-dispersive liquid–liquid microextraction (DDLL-ME) approach was used to extract uranium from real samples for the first time. The main objective of this study was to disperse extraction solvent by using an air-agitated syringe system to overcome matrix effects and avoid dispersion of hazardous dispersive organic solvents by using heat. The DDLL-ME method consisted of two dispersive liquid–liquid extraction steps with chloroform as the extracting solvent. Uranium formed complexes with 4-(2-thiazolylazo) resorcinol in the aqueous phase and was extra

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Pérez Mora, Walter Hernando, and Jaquelin Mojica Gómez. "Effect of extraction conditions on obtaining pectin from agroindustrial coffee by-products." Scientia et Technica 28, no. 03 (2023): 150–56. http://dx.doi.org/10.22517/23447214.25163.

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To present a proposal to reduce the waste generated in coffee agroindustrial production and explore potential applications of by-products, this study presents the effects of different physical factors (pH, temperature, and reflux time) on the extraction of pectin from coffee husks Coffea arabica, discarded in coffee farms of San Juan de Rioseco area after the desiccation process. The extraction is carried out by hydrolysis in an acidic medium using hydrochloric acid, precipitation by coagulation with 96% ethanol, filtration, and subsequent drying at 45 °C. Finally, the quality of the pectin ob

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Niu, L., and Y. Q. Song. "A FASTER R-CNN APPROACH FOR EXTRACTING INDOOR NAVIGATION GRAPH FROM BUILDING DESIGNS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 865–72. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-865-2019.

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<p><strong>Abstract.</strong> The indoor navigation graph is crucial for emergency evacuation and route guidance. However, most of existing solutions are limited to the tedious manual solutions and inefficient automatic solutions of the indoor building designs. In this paper, we strive to combine the cutting-edge faster R-CNN deep learning models with spatial connection rules to provide fine quality indoor navigation graphs. The extraction experiment result is convincing for general navigation purpose. But there exist several shortages for faster R-CNN models to overcome, suc

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Wang, Min, Hongbin Chen, Dingcai Shen, Baolei Li, and Shiyu Hu. "RSRNeT: a novel multi-modal network framework for named entity recognition and relation extraction." PeerJ Computer Science 10 (February 9, 2024): e1856. http://dx.doi.org/10.7717/peerj-cs.1856.

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Named entity recognition (NER) and relation extraction (RE) are two important technologies employed in knowledge extraction for constructing knowledge graphs. Uni-modal NER and RE approaches solely rely on text information for knowledge extraction, leading to various limitations, such as suboptimal performance and low efficiency in recognizing polysemous words. With the development of multi-modal learning, multi-modal named entity recognition (MNER) and multi-modal relation extraction (MRE) have been introduced to improve recognition performance. However, existing MNER and MRE methods often en

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ANGELINI, E., I. BAZZO, M. SAVINO, and M. BORGO. "Ochratoxin A: Comparison of Extraction Methods from Grapes and Quantitative Determination by Different Competitive Enzyme-Linked Immunosorbent Assay Kits." Journal of Food Protection 71, no. 12 (2008): 2488–96. http://dx.doi.org/10.4315/0362-028x-71.12.2488.

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The European Community has recently established a maximum limit for ochratoxin A (OTA) concentration in grapevine products, but many practical difficulties remain concerning the establishment of optimum cost-effective methods of quantification. The performance of four extraction procedures and three commercial competitive enzyme-linked immunosorbent assays (cELISAs) for grapes were compared. Results differed for the extractions and the cELISA kits. The advantage of using immunoaffinity columns (IACs) in the extraction was the excellent detection limit, which was between 0.06 and 0.0075 ng ml−1

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LOURENS, TINO, and ROLF P. WÜRTZ. "EXTRACTION AND MATCHING OF SYMBOLIC CONTOUR GRAPHS." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 07 (2003): 1279–302. http://dx.doi.org/10.1142/s0218001403002848.

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We describe an object recognition system based on symbolic contour graphs. The image to be analyzed is transformed into a graph with object corners as vertices and connecting contours as edges. Image corners are determined using a robust multiscale corner detector. Edges are constructed by line-following between corners based on evidence from the multiscale Gabor wavelet transform. Model matching is done by finding subgraph isomorphisms in the image graph. The complexity of the algorithm is reduced by labeling vertices and edges, whereby the choice of labels also makes the recognition system i

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Cho, Yong-Jin, Ji-Young Hong, Hyang Sook Chun, Sang Kook Lee, and Hye-Young Min. "Ultrasonication-assisted extraction of resveratrol from grapes." Journal of Food Engineering 77, no. 3 (2006): 725–30. http://dx.doi.org/10.1016/j.jfoodeng.2005.06.076.

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Hotta, Seiji, Kohei Inoue, and Kiichi Urahama. "Extraction of fuzzy clusters from weighted graphs." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 86, no. 1 (2002): 80–88. http://dx.doi.org/10.1002/ecjc.1133.

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Pulung Nurtantio Andono and Siti Hadiati Nugraini. "Texture Feature Extraction in Grape Image Classification Using K-Nearest Neighbor." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 5 (2022): 768–75. http://dx.doi.org/10.29207/resti.v6i5.4137.

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Indonesian Grapes are a vine. This fruit is often found in markets, shops, roadside. Along with the development of computer technology today, computers can solve problems by classifying objects and objects. How to apply GLCM and K-NN methods for classification of grapes. The purpose of this study is to apply the GLCM and K-NN methods in the classification of grapes. The dataset used from kaggle.com sources, the data tested are 3 types of grapes, the number of images is 2624. The fruit that will be used for data collection and classification process is limited to three types of grapes, namely g

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Ghimire, Dadhi Ram, Sanjeev Panday, and Aman Shakya. "Information Extraction from a Large Knowledge Graph in the Nepali Language." National College of Computer Studies Research Journal 3, no. 1 (2024): 33–49. https://doi.org/10.3126/nccsrj.v3i1.72336.

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Information is abundant in the web. The knowledge graph is used for organizing information in a structured format that can be retrieved using specialized queries. There are many Knowledge graphs but they differ in their ontologies and taxonomies as well as property types that bind the relation between the entities, which creates problems while extracting the knowledge from them. There is an issue in multilingual support. While most of them claim to be multilingual they are more suitable for querying in the English language. Most of the existing knowledge graphs in existence are based on Wikipe

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Zulkarneev, Rustem, Nafisa Yusupova, Olga Smetanina, Maya Gayanova, and Alexey Vulfin. "Method and Models of Extraction of Knowledge from Medical Documents." Informatics and Automation 21, no. 6 (2022): 1169–210. http://dx.doi.org/10.15622/ia.21.6.4.

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The paper analyzes the problem of extracting knowledge from clinical recommendations presented in the form of semi-structured corpora of text documents in natural language, taking into account their periodic updating. The considered methods of intellectual analysis of the accumulated arrays of medical data make it possible to automate a number of tasks aimed at improving the quality of medical care due to significant decision support in the treatment process. A brief review of well-known publications has been made, highlighting approaches to automating the construction of ontologies and knowle

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Yuan, Changsen, Heyan Huang, and Chong Feng. "Multi-Graph Cooperative Learning Towards Distant Supervised Relation Extraction." ACM Transactions on Intelligent Systems and Technology 12, no. 5 (2021): 1–21. http://dx.doi.org/10.1145/3466560.

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The Graph Convolutional Network (GCN) is a universal relation extraction method that can predict relations of entity pairs by capturing sentences’ syntactic features. However, existing GCN methods often use dependency parsing to generate graph matrices and learn syntactic features. The quality of the dependency parsing will directly affect the accuracy of the graph matrix and change the whole GCN’s performance. Because of the influence of noisy words and sentence length in the distant supervised dataset, using dependency parsing on sentences causes errors and leads to unreliable information. T

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Huang, Jingxiu, Ruofei Ding, Xiaomin Wu, et al. "WERECE: An Unsupervised Method for Educational Concept Extraction Based on Word Embedding Refinement." Applied Sciences 13, no. 22 (2023): 12307. http://dx.doi.org/10.3390/app132212307.

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The era of educational big data has sparked growing interest in extracting and organizing educational concepts from massive amounts of information. Outcomes are of the utmost importance for artificial intelligence–empowered teaching and learning. Unsupervised educational concept extraction methods based on pre-trained models continue to proliferate due to ongoing advances in semantic representation. However, it remains challenging to directly apply pre-trained large language models to extract educational concepts; pre-trained models are built on extensive corpora and do not necessarily cover a

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Feng, Jiayi, Runtong Zhang, Donghua Chen, and Lei Shi. "A Visualization Method of Knowledge Graphs for the Computation and Comprehension of Ultrasound Reports." Biomimetics 8, no. 8 (2023): 560. http://dx.doi.org/10.3390/biomimetics8080560.

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Knowledge graph visualization in ultrasound reports is essential for enhancing medical decision making and the efficiency and accuracy of computer-aided analysis tools. This study aims to propose an intelligent method for analyzing ultrasound reports through knowledge graph visualization. Firstly, we provide a novel method for extracting key term networks from the narrative text in ultrasound reports with high accuracy, enabling the identification and annotation of clinical concepts within the report. Secondly, a knowledge representation framework based on ultrasound reports is proposed, which

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