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Journal articles on the topic 'Automatic data structuring'

Author: Grafiati

Published: 23 November 2024

Last updated: 31 July 2025

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1

Duval, Erik, Henk Olivié, and Nick Scherbakov. "Contained Hypermedia." JUCS - Journal of Universal Computer Science 1, no. (10) (1995): 687–705. https://doi.org/10.3217/jucs-001-10-0687.

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We propose a new hypermedia data model, called CHM for Contained HyperMedia. Our model is based on set-oriented data structuring, with a strong emphasis on automatic maintenance of link integrity. In this paper, the CHM model is presented in detail: both data structuring, navigational facilities and authoring support are presented. We will also explain how we have integrated support for the CHM model in Home, our Hypermedia Object Management Environment, publicly accessible through the World-Wide Web.

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Yermukhanbetova, Sharbanu, and Gulnara Bektemyssova. "AUTOMATIC MERGING AND STRUCTURING OF DATA FROM DIFFERENT CATALOGS." JP Journal of Heat and Mass Transfer, Special (June 4, 2020): 7–11. http://dx.doi.org/10.17654/hmsi120007.

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Xiong, Wei, Chung-Mong Lee, and Rui-Hua Ma. "Automatic video data structuring through shot partitioning and key-frame computing." Machine Vision and Applications 10, no. 2 (1997): 51–65. http://dx.doi.org/10.1007/s001380050059.

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Pryhodinuk, V. V., Yu A. Tymchenko, M. V. Nadutenko, and A. Yu Gordieiev. "Automated data processing for evaluation the hydrophysical state of the Black Sea water areas." Oceanographic Journal (Problems, methods and facilities for researches of the World Ocean), no. 2(13) (April 22, 2020): 114–29. http://dx.doi.org/10.37629/2709-3972.2(13).2020.114-129.

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The article explores the issues of collecting, structuring and displaying oceanographic information from spatially distributed sources. The aim of the work was to develop services for an intelligent information system (IIS) designed to assess the hydrophysical state of the Black Sea waters by creating a library of ontological descriptions of the processing and displaying information in the IIS software environment. Article describes approaches to the creation of an automated data processing system for the assessment of the hydrophysical state of the Black Sea using the method of recursive redu

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Yu, Haiyang, Shuai Yang, Zhihai Wu, and Xiaolei Ma. "Vehicle trajectory reconstruction from automatic license plate reader data." International Journal of Distributed Sensor Networks 14, no. 2 (2018): 155014771875563. http://dx.doi.org/10.1177/1550147718755637.

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Using perception data to excavate vehicle travel information has been a popular area of study. In order to learn the vehicle travel characteristics in the city of Ruian, we developed a common methodology for structuring travelers’ complete information using the travel time threshold to recognize a single trip based on the automatic license plate reader data and built a trajectory reconstruction model integrated into the technique for order preference by similarity to an ideal solution and depth-first search to manage the vehicles’ incomplete records phenomenon. In order to increase the practic

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Dovgal, Sofiia, Egor Mukhaev, Marat Sabitov, and Lyubov' Adamcevich. "Development of a web service for processing data from electronic images of urban plans of land plots." Construction and Architecture 11, no. 1 (2023): 17. http://dx.doi.org/10.29039/2308-0191-2022-11-1-17-17.

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The article gives an idea of the content of urban planning plans for land plots (UPPLP), their purpose, as well as the relevance of developing a service for automatic recognition of data from an electronic image of a document. The existing services for automatic processing of documents are analyzed, and a technical solution developed by the authors is presented in the form of a web service for parsing and structuring electronic images of UPPLP. The description of the structure and operation of the web service, as well as the data conversion algorithm implemented in the solution is given.

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Tang, Shi, Takamasa Bito, and Kazuya Shide. "Automatic Classification of BIM Object Based on IFC Data Using the Uniclass Classification Standard." Buildings 15, no. 13 (2025): 2347. https://doi.org/10.3390/buildings15132347.

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Classification of BIM objects is critical for enhancing information interoperability and standardization within construction projects; however, research on automated BIM object classification based on standardized classification systems remains limited. Therefore, this study proposes an automated method to classify BIM objects using IFC data under the Uniclass system, aiming to enhance standardization, semantic clarity, and practical applicability. The proposed method first assigns Uniclass codes to 8715 BIM objects, then extracts 13 types of IFC-derived feature variables—including semantic, s

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Kopyrin, Andrey Sergeevich, and Irina Leonidovna Makarova. "Algorithm for preprocessing and unification of time series based on machine learning for data structuring." Программные системы и вычислительные методы, no. 3 (March 2020): 40–50. http://dx.doi.org/10.7256/2454-0714.2020.3.33958.

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The subject of the research is the process of collecting and preliminary preparation of data from heterogeneous sources. Economic information is heterogeneous and semi-structured or unstructured in nature. Due to the heterogeneity of the primary documents, as well as the human factor, the initial statistical data may contain a large amount of noise, as well as records, the automatic processing of which may be very difficult. This makes preprocessing dynamic input data an important precondition for discovering meaningful patterns and domain knowledge, and making the research topic relevant.Data

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Willot, L., D. Vodislav, L. De Luca, and V. Gouet-Brunet. "AUTOMATIC STRUCTURING OF PHOTOGRAPHIC COLLECTIONS FOR SPATIO-TEMPORAL MONITORING OF RESTORATION SITES: PROBLEM STATEMENT AND CHALLENGES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-2/W1-2022 (February 25, 2022): 521–28. http://dx.doi.org/10.5194/isprs-archives-xlvi-2-w1-2022-521-2022.

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Abstract. Over the last decade, a large number of digital documentation projects have demonstrated the potential of image-based modelling of heritage objects in the context of documentation, conservation, and restoration. The inclusion of these emerging methods in the daily monitoring of the activities of a heritage restoration site (context in which hundreds of photographs per day can be acquired by multiple actors, in accordance with several observation and analysis needs) raises new questions at the intersection of big data management, analysis, semantic enrichment, and more generally autom

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Galauskis, Maris, and Arturs Ardavs. "The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments." Applied Computer Systems 26, no. 2 (2021): 173–77. http://dx.doi.org/10.2478/acss-2021-0021.

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Abstract In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also ou

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Kang, Tian, Shaodian Zhang, Youlan Tang, et al. "EliIE: An open-source information extraction system for clinical trial eligibility criteria." Journal of the American Medical Informatics Association 24, no. 6 (2017): 1062–71. http://dx.doi.org/10.1093/jamia/ocx019.

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Abstract Objective To develop an open-source information extraction system called Eligibility Criteria Information Extraction (EliIE) for parsing and formalizing free-text clinical research eligibility criteria (EC) following Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) version 5.0. Materials and Methods EliIE parses EC in 4 steps: (1) clinical entity and attribute recognition, (2) negation detection, (3) relation extraction, and (4) concept normalization and output structuring. Informaticians and domain experts were recruited to design an annotation guideline and ge

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Koshman, Varvara, Anastasia Funkner, and Sergey Kovalchuk. "An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records." Journal of Personalized Medicine 12, no. 1 (2022): 25. http://dx.doi.org/10.3390/jpm12010025.

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Electronic medical records (EMRs) include many valuable data about patients, which is, however, unstructured. Therefore, there is a lack of both labeled medical text data in Russian and tools for automatic annotation. As a result, today, it is hardly feasible for researchers to utilize text data of EMRs in training machine learning models in the biomedical domain. We present an unsupervised approach to medical data annotation. Syntactic trees are produced from initial sentences using morphological and syntactical analyses. In retrieved trees, similar subtrees are grouped using Node2Vec and Wor

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Lee, Yong-Ki, Jineon Kim, Chae-Soon Choi, and Jae-Joon Song. "Semi-automatic calculation of joint trace length from digital images based on deep learning and data structuring techniques." International Journal of Rock Mechanics and Mining Sciences 149 (January 2022): 104981. http://dx.doi.org/10.1016/j.ijrmms.2021.104981.

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Kuzikov, S. I., and D. V. Kenigsberg. "Automatic Verification, Collection of Metainformation and Structuring of Primary Data of Space Geodetic Observations for Their Qualitative Analysis." Seismic Instruments 60, no. 1-3 (2024): 10–18. https://doi.org/10.3103/s0747923925700069.

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Mentari, Mustika, Yan Watequlis Syaifudin, Nobuo Funabiki, Nadia Layra Aziza, and Tita Wijayanti. "Canny and Morphological Approaches to Calculating Area and Perimeter of Two-Dimensional Geometry." Jurnal Jartel Jurnal Jaringan Telekomunikasi 12, no. 4 (2022): 287–96. http://dx.doi.org/10.33795/jartel.v12i4.574.

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Calculating area and perimeter in real-world conditions has its challenges. The actual conditions include applications in the medical field to measure the presence of tumors or the condition of human organs and applications in geography to measure specific areas on a map; applications in architecture often calculate the area and perimeter of buildings, interior design, exterior design, and other uses. Technology can make it easier with automatic calculations. Mathematical methods and computer vision techniques are required to create automated systems. The Canny method is usually used, which is

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Gulmirzaeva, G. A. "Using semantic indexing and thesauri in processing dermoscopic images." Современные инновации, системы и технологии - Modern Innovations, Systems and Technologies 5, no. 2 (2025): 3071–76. https://doi.org/10.47813/2782-2818-2025-5-2-3071-3076.

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This article presents an innovative algorithm for automatic semantic indexing of dermoscopic images using clinical metadata (age, gender, anatomical location). The proposed approach integrates advanced natural language processing (NLP) techniques with medical thesauri and ontologies to enhance the efficiency of medical data analysis and structuring. The BioBERT neural language model was employed to generate clinical descriptions for each image, transforming natural language expressions into a vector space. These vector representations were then compared with selected semantic concepts from med

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Benício, Diego Henrique Pegado, João Carlos Xavier Junior, Kairon Ramon Sabino de Paiva, and Juliana Dantas de Araújo Santos Camargo. "Applying Text Mining and Natural Language Processing to Electronic Medical Records for extracting and transforming texts into structured data." Research, Society and Development 11, no. 6 (2022): e37711629184. http://dx.doi.org/10.33448/rsd-v11i6.29184.

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The recording of patients' data in electronic patient records (EPRs) by healthcare providers is usually performed in free text fields, allowing different ways of describing that type of information (e.g., abbreviation, terminology, etc.). In scenarios like that, retrieving data from such source (text) by using SQL (Structured Query Language) queries becomes an unfeasible issue. Based on this fact, we present in this paper a tool for extracting comprehensible and standardized patients' data from unstructured data which applies Text Mining and Natural Language Processing techniques. Our main goa

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Plisenko, Olga. "Algorithms and methodology for inflection line identification within information and mathematical model of relief." InterCarto. InterGIS 28, no. 1 (2022): 683–95. http://dx.doi.org/10.35595/2414-9179-2022-1-28-683-695.

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The relevance of this research topic lies in the fact that a universal technology for automated recognition and identification of structural relief elements is currently not available. This task is one of the main analytical directions of geomorphological mapping, and its solution will reduce the time for its development, unify the results, and expand the field of application of the homomorphic and genetically homogeneous elementary surface model in interdisciplinary research. To solve this problem, an information and mathematical relief model is developed, the purpose of which is to present s

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Sidi, Fatimah, Iskandar Ishak, and Marzanah A. Jabar. "MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstructured Documents." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 1 (2018): 1. http://dx.doi.org/10.11591/ijece.v8i1.pp1-10.

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The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to

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Fatimah, Sidi, Ishak Iskandar, and A. Jabar Marzanah. "MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstructured Documents." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 1 (2018): 1–10. https://doi.org/10.11591/ijece.v8i1.pp1-10.

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The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to

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Doria, E., and F. Picchio. "TECHNIQUES FOR MOSAICS DOCUMENTATION THROUGH PHOTOGRAMMETRY DATA ACQUISITION. THE BYZANTINE MOSAICS OF THE NATIVITY CHURCH." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 965–72. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-965-2020.

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Abstract. This paper describes a sequence of actions developed to guarantee a reliable and suitable dataset for the creation of detailed ortho images of Nativity Church mosaics. During acquisition campaigns, different photogrammetric techniques were tested, and different survey instruments were compared to improve the quality of the data obtained. The different outputs allow the adjustment of the instrument parameters and the acquisition methods, to structure a methodological process aimed at obtaining an accurate level of detail to describe the individual mosaic tile.From the realization of a

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Vadurin, Kyrylo, Andrii Perekrest, Volodymyr Bakharev, Andriy Deriyenko, Artem Ivashchenko, and Sergii Shkarupa. "AN INFORMATION SYSTEM FOR COLLECTING AND STORING AIR QUALITY DATA FROM MUNICIPAL LEVEL VAISALA STATIONS." Інфокомунікаційні та комп’ютерні технології, no. 2(6) (2023): 38–49. http://dx.doi.org/10.36994/2788-5518-2023-02-06-04.

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Today, the problem of air pollution is a pressing one, especially in Ukraine. As a result of the war and the Kakhovka hydroelectric power station disaster, as well as the relocation of certain industrial enterprises and the displacement of the population, there have been significant changes in the state of the atmospheric air in municipalities compared to the state before these changes, which was recorded by environmental monitoring stations and could be predicted for a long time. In Kremenchuk, air quality studies are carried out by a municipal enterprise of the city council. The company's au

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Poguda, A. A., and H. Tape. "Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social Networks." Open Education 29, no. 2 (2025): 34–45. https://doi.org/10.21686/1818-4243-2025-2-55-70.

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Scientific relevance of the study. In the era of rapidly increasing volumes of data generated by social media users, analyzing textual data such as comments is becoming one of the key challenges of modern science. Comments are a valuable source of information, allowing us to identify public sentiment, analyze users’ opinions, and track social trends. However, due to the semistructured or completely unstructured nature of these data, their processing requires innovative approaches. Purpose of research. The aim of this research is to develop an intelligent system for processing semistructured da

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Salmam, Fatima Zahra, Mohamed Fakir, and Rahhal Errattahi. "Prediction in OLAP Data Cubes." Journal of Information & Knowledge Management 15, no. 02 (2016): 1650022. http://dx.doi.org/10.1142/s0219649216500222.

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Online analytical processing (OLAP) provides tools to explore data cubes in order to extract the interesting information, it refers to techniques used to query, visualise and synthesise the multidimensional data. Nevertheless OLAP is limited on visualisation, structuring and exploring manually the data cubes. On the other side, data mining allows algorithms that offer automatic knowledge extraction, such as classification, explanation and prediction algorithms. However, OLAP is not capable of explaining and predicting events from existing data; therefore, it is possible to make a more efficien

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Nunes, Carolina, Jasper Anckaert, Fanny De Vloed, et al. "HTSplotter: An end-to-end data processing, analysis and visualisation tool for chemical and genetic in vitro perturbation screening." PLOS ONE 19, no. 1 (2024): e0296322. http://dx.doi.org/10.1371/journal.pone.0296322.

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In biomedical research, high-throughput screening is often applied as it comes with automatization, higher-efficiency, and more and faster results. High-throughput screening experiments encompass drug, drug combination, genetic perturbagen or a combination of genetic and chemical perturbagen screens. These experiments are conducted in real-time assays over time or in an endpoint assay. The data analysis consists of data cleaning and structuring, as well as further data processing and visualisation, which, due to the amount of data, can easily become laborious, time-consuming and error-prone. T

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Ploux, Sabine. "Modélisation et Traitement Informatique de la Synonymie." Lingvisticæ Investigationes. International Journal of Linguistics and Language Resources 21, no. 1 (1997): 1–27. http://dx.doi.org/10.1075/li.21.1.02plo.

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This paper deals with automatic structuring of semantic values in a dictionary of synonyms. The data we used were first extracted from seven French published dictionnaries of synonyms and then merged to obtain the files we worked on. We explain here why a discrete mathematic representation of synonymic relation is not sufficient to produce a semantic structure (that represents the different meanings of a term but also their overlapping). Then we propose a continuous representation (using data analysis) that ables the machine to produce for each term its semantic values. The system also labels

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Barabanschikov, V. A., and A. V. Zhegallo. "Dynamics of Key Facial Points as an Indicator of the Credibility of Reported Information." Experimental Psychology (Russia) 14, no. 2 (2021): 101–12. http://dx.doi.org/10.17759/exppsy.2021140207.

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This research describes a method for studying the authenticity/unauthenticity of the information re- ported by people in video images. It is based on automatic tracking of coordinates of key points of a speaker’s face using OpenFace software. When processing the data, the multiple linear regression procedure is used. It was found that the dynamics of neighboring key points in the obtained models has a multidirectional char- acter, indicating the presence of a superposition of several dynamic structures, corresponding to the characteristic complex changes in the face position and facial express

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Acampa, Giovanna, and Alessio Pino. "A Simplified Facility Management Tool for Condition Assessment through Economic Evaluation and Data Centralization: Branch to Core." Sustainability 15, no. 8 (2023): 6418. http://dx.doi.org/10.3390/su15086418.

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The field of facility management, especially concerning condition assessment, is affected by two main issues: one is the incompleteness and heterogeneity of information transfer between the involved subjects; the other is the frequent lack of specific advanced skills needed for technically complex tools. The immediate consequences of this process inefficiency fall on economic and environmental aspects: the unavailability or incorrect structuring of data related to building conditions does not allow for making optimal choices concerning interventions on components. This paper attempts to provid

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Nadutenko, M. V. "ntelligent Lexico-Conceptographic Systems: Integrating Cognitive Technologies, Ontologies, and Dynamic Knowledge Management." Scientific Notes of Junior Academy of Sciences of Ukraine, no. 1(31) (2025): 84–95. https://doi.org/10.51707/2618-0529-2024-31_1-08.

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Modern intelligent systems require innovative approaches to managing large volumes of ever-changing knowledge. This article explores the conceptual foundations of building intelligent lexico-conceptographic systems that combine cognitive technologies, ontologies, and dynamic knowledge compression. Special emphasis is placed on the use of ontologies for knowledge formalization and structuring, enabling adaptability, relevance, and transparency in the processes of integrating new data. The proposed system is based on conceptographic analysis, which formalizes knowledge in the form of concept gra

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Benichou, Laurence, Marianne Salaün, Iva Boyadzhieva, Seyhan Demirov, Teodor Georgiev, and Lyubomir Penev. "Pre-publication Data Linking in Taxonomy and Biodiversity: The ARPHA and Metotaxa-Metostem publishing systems." Biodiversity Information Science and Standards 7 (August 9, 2023): e110919. https://doi.org/10.3897/biss.7.110919.

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The traditional way of publishing in PDF makes it difficult to retrospectively convert the legacy literature into data. This presentation will discuss pre-publication tagging as an alternative solution for publishing FAIR (Findable, Accessible, Interoperable, Resuable) biodiversity data.The Metotaxa-Metostem workflow Тhe MetoTaxa project aims to create a new digital production chain for the <em>European Journal of Taxonomy</em>, which enables the pre-publication semantic structuring of text, automatic tagging and semantic enrichment (annotation).The system is based on a single-source publishin

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Cascella, Marco, Daniela Schiavo, Arturo Cuomo, et al. "Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives." Pain Research and Management 2023 (June 28, 2023): 1–13. http://dx.doi.org/10.1155/2023/6018736.

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Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be add

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Mora-Cross, Maria, William Ulate, Chacón Brandon Retana, Portillo María Biarreta, Ramírez Josué David Castro, and Madriz Jose Chavarria. "Structuring Information from Plant Morphological Descriptions using Open Information Extraction." Biodiversity Information Science and Standards 7 (September 21, 2023): e113055. https://doi.org/10.3897/biss.7.113055.

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Taxonomic literature keeps records of the planet's biodiversity and gives access to the knowledge needed for research and sustainable management. The number of publications generated is quite large: the corpus of biodiversity literature includes tens of millions of figures and taxonomic treatments. Unfortunately, most of the taxonomic descriptions are from scientific publications in text format. With more than 61 million digitized pages in the Biodiversity Heritage Library (BHL), only 467,265 taxonomic treatments are available in the Biodiversity Literature Repository. To obtain highly structu

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La Russa, F. M., E. Grilli, F. Remondino, C. Santagati, and M. Intelisano. "ADVANCED 3D PARAMETRIC HISTORIC CITY BLOCK MODELING COMBINING 3D SURVEYING, AI AND VPL." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-M-2-2023 (June 24, 2023): 903–10. http://dx.doi.org/10.5194/isprs-archives-xlviii-m-2-2023-903-2023.

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Abstract. The presented research aims to define a parametric modelling methodology that allows, in short time and at a sustainable cost, the digital acquisition, modelling and semantic structuring of urban city blocks to facilitate 3D city modelling applied to historic centres. The methodology is based on field surveying and derives 3D data for the realisation of a parametric City Information Model (CIM). This is pursued through the adoption of parametric modelling as main method combined with AI procedures like supervised machine learning. In particular, the Visual Programming Language (VPL)

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Adanza Dopazo, Daniel, Lamine Mahdjoubi, and Bill Gething. "A Method to Enable Automatic Extraction of Cost and Quantity Data from Hierarchical Construction Information Documents to Enable Rapid Digital Comparison and Analysis." Buildings 13, no. 9 (2023): 2286. http://dx.doi.org/10.3390/buildings13092286.

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Context: Despite the effort put into developing standards for structuring construction costs and the strong interest in the field, most construction companies still perform the process of data gathering and processing manually. This provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly in large projects. Additionally, the lack of standardization makes cost estimation and comparison tasks very difficult. Objective: The aim of this work was to create a method to extract and organize construction cost and quant

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Ruiz-Diaz, C. M., J. A. Gómez-Camperos, and M. M. Hernández-Cely. "Flow pattern identification of liquid-liquid (oil and water) in vertical pipelines using machine learning techniques." Journal of Physics: Conference Series 2163, no. 1 (2022): 012001. http://dx.doi.org/10.1088/1742-6596/2163/1/012001.

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Abstract Given the importance of process control in the petrochemical industry, there is a need to determine the behavior of the fluids inside the pipes. In this work a methodology is developed for the identification of flow patterns in vertical pipes with diameters between 0.01 m and 0.10 m, from the implementation of artificial intelligence techniques, for a liquid combination of two phases composed of oil with viscosity in the range of 792 Kg/m3 to 1823 Kg/m3 and water at room temperature. The predictive models generated in the structuring of the methodology were trained with 70% of data ba

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Li, Sixuan, Liang Zhang, Shiwei Liu, Richard Hubbard, and Hui Li. "Surveillance of Noncommunicable Disease Epidemic Through the Integrated Noncommunicable Disease Collaborative Management System: Feasibility Pilot Study Conducted in the City of Ningbo, China." Journal of Medical Internet Research 22, no. 7 (2020): e17340. http://dx.doi.org/10.2196/17340.

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Background Noncommunicable diseases (NCDs) have become the main public health concern worldwide. With rapid economic development and changes in lifestyles, the burden of NCDs in China is increasing dramatically every year. Monitoring is a critical measure for NCDs control and prevention. However, because of the lack of regional representativeness, unsatisfactory data quality, and inefficient data sharing and utilization, the existing surveillance systems and surveys in China cannot track the status and transition of NCDs epidemic. Objective To efficaciously track NCDs epidemic in China, this p

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Shamaeva, Ekaterina F., and Anna K. Perevozchikova. "Analytical situational center of the region in the context of energy-ecological, socio-economic and infrastructural indicators." Geoinformatika, no. 3 (September 29, 2023): 81–92. http://dx.doi.org/10.47148/1609-364x-2023-3-81-92.

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Today, geo-information systems play a special role in regional and industry management, which serve as an effective tool for modeling regional systems. This work presents the results of the development of a situation center, the task of which is to store and update data on the state of regional systems. The situation center serves as a convenient tool for structuring and presenting data. The information base for the formation of an array of initial data is the Federal State Statistics Service, from where statistical data on multi-level regional systems were uploaded in the context of energy-en

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Moutinho, Thomas J., Benjamin C. Neubert, Matthew L. Jenior, and Jason A. Papin. "Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions." PLOS Computational Biology 18, no. 2 (2022): e1009341. http://dx.doi.org/10.1371/journal.pcbi.1009341.

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Genome-scale metabolic network reconstructions (GENREs) are valuable tools for understanding microbial metabolism. The process of automatically generating GENREs includes identifying metabolic reactions supported by sufficient genomic evidence to generate a draft metabolic network. The draft GENRE is then gapfilled with additional reactions in order to recapitulate specific growth phenotypes as indicated with associated experimental data. Previous methods have implemented absolute mapping thresholds for the reactions automatically included in draft GENREs; however, there is growing evidence th

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Tilkar, Swati. "Generating Meeting Transcription Using Natural Language Processing." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem51091.

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Natural Language Processing plays a pivotal role in automating the transcription of meetings. It enables machines to understand, interpret, and generate human language. In meeting transcription, NLP components such as Automatic Speech Recognition (ASR), speaker diarization, entity recognition, summarization, and sentiment analysis work together to produce accurate and readable transcripts. ASR converts spoken words into text, while NLP refines the raw output by correcting grammatical errors, identifying speakers, and structuring dialogue for readability and comprehension. Ethical consideration

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Rysová, Magdaléna. "Studying text coherence in Czech – a corpus-based analysis." Topics in Linguistics 18, no. 2 (2017): 36–47. http://dx.doi.org/10.1515/topling-2017-0009.

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Abstract The paper deals with the field of Czech corpus linguistics and represents one of various current studies analysing text coherence through language interactions. It presents a corpusbased analysis of grammatical coreference and sentence information structure (in terms of contextual boundness) in Czech. It focuses on examining the interaction of these two language phenomena and observes where they meet to participate in text structuring. Specifically, the paper analyses contextually bound and non-bound sentence items and examines whether (and how often) they are involved in relations of

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Czyzewski, Andrzej. "Optimizing medical personnel speech recognition models using speech synthesis and reinforcement learning." Journal of the Acoustical Society of America 154, no. 4_supplement (2023): A202—A203. http://dx.doi.org/10.1121/10.0023271.

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Text-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons. Speech can be synthesized by mimicking different accents, dialects, and speaking styles in a medical language. Reinforcement Learning (RL), in the context of ASR, can be used to optimize a model. A model can be trained to minimize errors in speech-to-text transcription, especially for technical medical terminology. In this case, the “reward” to the RL model can

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Rogushina, J. V. "Fuzzy data in semantic Wiki-resources: models, sources and processing methods." PROBLEMS IN PROGRAMMING, no. 2 (June 2023): 67–83. http://dx.doi.org/10.15407/pp2023.02.067.

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We analyze main types of dirty data processed by intelligente information systems, criteria of data classification and means of detection non-classical properties of data. Results of this analysis are represented by ontological model that contains taxonomy of classical and nonclassical data and knowledge-oriented methods of their transformation. Special attention is paid to semantically incorrect data that corresponds to vague knowledge. This ontological model intended to provide more effectively methods for transforming raw data into smart data suitable for automatic analysis, knowledge acqui

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Sbrollini, Agnese, Chiara Leoni, Micaela Morettini, et al. "Identification of Electrocardiographic Patterns Related to Mortality with COVID-19." Applied Sciences 14, no. 2 (2024): 817. http://dx.doi.org/10.3390/app14020817.

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COVID-19 is an infectious disease that has greatly affected worldwide healthcare systems, due to the high number of cases and deaths. As COVID-19 patients may develop cardiac comorbidities that can be potentially fatal, electrocardiographic monitoring can be crucial. This work aims to identify electrocardiographic and vectorcardiographic patterns that may be related to mortality in COVID-19, with the application of the Advanced Repeated Structuring and Learning Procedure (AdvRS&LP). The procedure was applied to data from the “automatic computation of cardiovascular arrhythmic risk from ele

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Rervyatskyy, I. Yu. "A relational database with pharmaceutical information: problems of creation and primary filling for provision of a qualitative statistical processing." Farmatsevtychnyi zhurnal, no. 4 (September 10, 2019): 23–31. http://dx.doi.org/10.32352/0367-3057.4.19.03.

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The disclosure of pharmaceutical information is not intended to provide the possibility of further automated processing of the data provided by independent experts, and, accordingly, the choice of the methods of presentation is aimed to optimize visual perception by users. The aim of the work was to analyze in the internet-sources the availability of information in the appropriate format for automatic filling of the relational database. The subjects of the study were: ATC: ICD-10 (International Classification of Diseases); content of EF 9.8; classification of dosage forms by the Ministry

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Konovalov, V. A. "MODEL OF ILLEGAL ECONOMIC ACTIVITY IN ANTI-MONEY LAUNDERING PROCEEDS FROM CRIME." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 228 (June 2023): 41–53. http://dx.doi.org/10.14489/vkit.2023.06.pp.041-053.

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In the interests of developing the theoretical provisions of the methodology for classifying the typologies of the risks of laundering proceeds from crime and financing of terrorism in big data from a variety of data sources of organizational systems, a study is being made of the signs of illegal economic activity. Theoretically substantiates and synthesizes a reference model of illegal economic activity of organizational systems. This model considers four stages of possible illegal economic activity of organizational systems. The stages have symbols: “institutions, organizations, structuring

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Appazov, Eduard, Dmytro Krugliy, Serhii Zinchenko, and Pavlo Nosov. "Choice of the Fractal Method For Visualization of Input Data While Designing Support Systems for Decision-Making by Navigator." Science and Innovation 17, no. 5 (2021): 63–72. http://dx.doi.org/10.15407/scine17.05.063.

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Introduction. The constant increase in the amount and intensity of traffic requires organization and precise management.Problem Statement. In the present-day conditions, when the number of vessels engaged on internal and external routes has been growing, without the vessel driver/navigator all alone are not physically able to assess the navigation situation and to make the right decision how to operate his vessel. The need to develop and to implement algorithms that help address the issue of navigation safety is an important task, especially when it comes to the management of groups of vessels

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KHEMAKHEM, AIDA, BILEL GARGOURI, ABDELMAJID BEN HAMADOU, and GIL FRANCOPOULO. "ISO standard modeling of a large Arabic dictionary." Natural Language Engineering 22, no. 6 (2015): 849–79. http://dx.doi.org/10.1017/s1351324915000224.

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AbstractIn this paper, we address the problem of the large coverage dictionaries of Arabic language usable both for direct human reading and automatic Natural Language Processing. For these purposes, we propose a normalized and implemented modeling, based on Lexical Markup Framework (LMF-ISO 24613) and Data Registry Category (DCR-ISO 12620), which allows a stable and well-defined interoperability of lexical resources through a unification of the linguistic concepts. Starting from the features of the Arabic language, and due to the fact that a large range of details and refinements need to be d

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Irfan, Irfan, Sofendi Sofendi, and Machdalena Vianty. "Technological knowledge application on academic writing English education study program students." English Review: Journal of English Education 9, no. 1 (2020): 157–66. http://dx.doi.org/10.25134/erjee.v9i1.3788.

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Technological knowledge plays a role in academic writing such as assisting in finding suitable references, checking plagiarism, and publishing the article. However, technological knowledge does not always provide benefits in academic writing. Technological knowledge may affect the writers’ mentality to take shortcut in finishing and checking their writing. The objectives of this study were: (1) to find out the technological knowledge level of English education study program students, (2) to find out how English education study program students applied their technological knowledge in academic

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Hansen, Matthias, André Pomp, Kemal Erki, and Tobias Meisen. "Data-Driven Recognition and Extraction of PDF Document Elements." Technologies 7, no. 3 (2019): 65. http://dx.doi.org/10.3390/technologies7030065.

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In the age of digitalization, the collection and analysis of large amounts of data is becoming increasingly important for enterprises to improve their businesses and processes, such as the introduction of new services or the realization of resource-efficient production. Enterprises concentrate strongly on the integration, analysis and processing of their data. Unfortunately, the majority of data analysis focuses on structured and semi-structured data, although unstructured data such as text documents or images account for the largest share of all available enterprise data. One reason for this

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Chatterjee, Ayan, Andreas Prinz, Martin Gerdes, and Santiago Martinez. "An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-Concept Study." Journal of Medical Internet Research 23, no. 4 (2021): e24656. http://dx.doi.org/10.2196/24656.

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Background Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. However, it may produce a data compatibility dilemma. Our proposed eHealth ontology can increase interoperability between dif

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