Relevant bibliographies by topics / Document optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Document optimization'

Author: Grafiati
Published: 30 May 2022
Last updated: 19 July 2025

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Journal articles on the topic "Document optimization"

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Et. al., Tamilselvan Jayaraman,. "Brainstorm optimization for multi-document summarization." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 10 (2021): 7607–19. http://dx.doi.org/10.17762/turcomat.v12i10.5670.

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Document summarization is one of the solutions to mine the appropriate information from a huge number of documents. In this study, brainstorm optimization (BSO) based multi-document summarizer (MDSBSO) is proposed to solve the problem of multi-document summarization. The proposed MDSBSO is compared with two other multi-document summarization algorithms including particle swarm optimization (PSO) and bacterial foraging optimization (BFO). To evaluate the performance of proposed multi-document summarizer, two well-known benchmark document understanding conference (DUC) datasets are used. Perform
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K. Adi Narayana Reddy. "Multi-Document Summarization using Discrete Bat Optimization." Journal of Electrical Systems 20, no. 7s (2024): 831–42. http://dx.doi.org/10.52783/jes.3457.

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With the World Wide Web, we now have a wide range of data that was previously unavailable. Therefore, it has become a complex problem to find useful information in large datasets. In recent years, text summarization has emerged as a viable option for mining relevant data from massive collections of texts. We may classify summarizing as either "single document" or "multi document" depending on how many source documents we are working with. Finding an accurate summary from a collection of documents is more difficult for researchers than doing it from a single document. For this reason, this rese
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Slavin, O. A. "Optimizing the performance of a server-based classification for a large business document flow." «System analysis and applied information science», no. 4 (February 24, 2023): 60–64. http://dx.doi.org/10.21122/2309-4923-2022-4-60-64.

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The document categorization problem in the case of a large business document flow is considered. Textual and visual embeddings were employed for classification. Textual embeddings were extracted via OCR Tesseract. The Viola and Jones method was applied to generate visual embeddings. This paper describes the performance optimization technology for the implemented classification algorithm. Servers with Intel CPUs were used for the algorithm execution. For single-threaded implementation, high-level and low-level optimizations were performed. High-level optimization was based on the parametrizatio
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Cheng, Wen Zhi, Yi Yang, Liao Zhang, and Lian Li. "Optimization for Web-Based Online Document Management." Advanced Materials Research 756-759 (September 2013): 1135–40. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1135.

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In this paper, we construct a web-based document life-cycle management model. The model manages documents which consist of the institute library from their creation to the archive state. For an online office system, we aim at solving three issues: network delay, version storage problems and deletion strategy. To solve network delay, we propose both local and online document synchronized editing model. In addition, we combine the longest recursive chain with recursive chain time to optimize the system response time. In order to optimize documents to be deleted, we propose a two-step optimized m
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Jisheng Liang, I. T. Phillips, and R. M. Haralick. "An optimization methodology for document structure extraction on Latin character documents." IEEE Transactions on Pattern Analysis and Machine Intelligence 23, no. 7 (2001): 719–34. http://dx.doi.org/10.1109/34.935846.

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Orlov, I. V. "Role of document management system for business processes optimization." Problems of Theory and Methodology of Accounting, Control and Analysis, no. 2(58) (September 16, 2024): 45–49. http://dx.doi.org/10.26642/pbo-2024-2(58)-45-49.

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The automation of work processes and seamless integration with various business services highlight the essential role of digital document management systems (DMS) in enhancing organizational flexibility, productivity, and adaptability. DMS serve as centralized repositories that streamline, automate, and interconnect business processes, thereby facilitating effective document management. The integration of DMS with Enterprise Resource Planning (ERP) systems provides a comprehensive solution for optimizing business workflows, addressing the needs for both operational efficiency and strategic man
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T. Elavarasi. "Spectral Clustering-Based Particle Swarm Optimization Algorithm for Document Clustering." Journal of Information Systems Engineering and Management 10, no. 4s (2025): 134–46. https://doi.org/10.52783/jisem.v10i4s.487.

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The process of automatically grouping documents into clusters such that the documents in one cluster are very comparable to the documents in the remaining clusters have been known as document clustering. Due to its broad application in a number of fields, including search engines, web mining, and information retrieval, it has been the subject of much research. It involves clustering documents that are identical to one another and calculating how identical they are. It facilitates simple navigation by offering effective document representation as well as visualization. Hence, this research pape
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Liu, R. H., Q. Zhang, and G. Yin. "document." Applied Mathematics and Optimization 44, no. 2 (2001): 105–29. http://dx.doi.org/10.1007/s00245-001-0016-8.

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Abualigah, Laith, Amir H. Gandomi, Mohamed Abd Elaziz, et al. "Nature-Inspired Optimization Algorithms for Text Document Clustering—A Comprehensive Analysis." Algorithms 13, no. 12 (2020): 345. http://dx.doi.org/10.3390/a13120345.

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Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. In which, each cluster contains similar documents and the clusters contain dissimilar text documents. Nature-inspired optimization algorithms have been successfully used to solve various optimization problems, including text document clustering problems. In this paper, a comprehensive review is presented to show the most related nature-inspired algorithms that have been used in solving the text clustering problem. Moreover, comprehensive experime
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Kayest, Mamta, and Sanjay Kumar Jain. "An incremental learning approach for the text categorization using hybrid optimization." International Journal of Intelligent Computing and Cybernetics 12, no. 3 (2019): 333–51. http://dx.doi.org/10.1108/ijicc-12-2018-0170.

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Purpose Document retrieval has become a hot research topic over the past few years, and has been paid more attention in browsing and synthesizing information from different documents. The purpose of this paper is to develop an effective document retrieval method, which focuses on reducing the time needed for the navigator to evoke the whole document based on contents, themes and concepts of documents. Design/methodology/approach This paper introduces an incremental learning approach for text categorization using Monarch Butterfly optimization–FireFly optimization based Neural Network (MB–FF ba
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Dissertations / Theses on the topic "Document optimization"

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Lam, Franky Shung Lai Chemical Sciences &amp Engineering Faculty of Engineering UNSW. "Optimization techniques for XML databases." Awarded by:University of New South Wales. Chemical Sciences & Engineering, 2007. http://handle.unsw.edu.au/1959.4/40702.

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In this thesis, we address several fundamental concerns of maintaining and querying huge ordered label trees. We focus on practical implementation issues of storing, updating and query optimization of XML database management system. Specifically, we address the XML order maintenance problem, efficient evaluation of structural join, intrinsic skew handling of join, succinct storage of XML data and update synchronization of mobile XML data.
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Sghir, Inès. "A Multi-Agent based Optimization Method for Combinatorial Optimization Problems." Thesis, Angers, 2016. http://www.theses.fr/2016ANGE0009/document.

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Nous élaborons une approche multi-agents pour la résolution des problèmes d’optimisation combinatoire nommée MAOM-COP. Elle combine des métaheuristiques, les systèmes multi-agents et l’apprentissage par renforcement. Les heuristiques manquent d’une vue d’ensemble sur l’évolution de la recherche. Notre objectif consiste à utiliser les systèmes multi-agents pour créer des méthodes de recherche coopératives. Ces méthodes explorent plusieurs métaheuristiques. MAOM-COP est composée de plusieurs agents qui sont l’agent décideur, les agents intensificateurs et les agents diversificateurs (agents croi
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Cauwet, Marie-Liesse. "Uncertainties in Optimization." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS308/document.

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Ces recherches sont motivées par la nécessité de développer de nouvelles méthodes d'optimisation des systèmes électriques. Dans ce domaine, les méthodes usuelles de contrôle et d'investissement sont à présent limitées de par les problèmes comportant une grande part d'aléa, qui interviennent lors de l'introduction massive d'énergies renouvelables. Après la présentation des différentes facettes de l'optimisation d'un système électrique, nous discuterons le problème d'optimisation continue bruitée de type boîte noire puis des cas bruités comprenant des caractéristiques supplémentaires.Concernant
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Kiran, Bangalore Ravi. "Energetic-lattice based optimization." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1091/document.

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La segmentation hiérarchique est une méthode pour produire des partitions qui représentent une même image de manière de moins en moins fine. En même temps, elle sert d'entrée à la recherche d'une partition optimale, qui combine des extraits des diverses partitions en divers endroits. Le traitement hiérarchique des images est un domaine émergent en vision par ordinateur, et en particulier dans la communauté qui étudie les images hyperspectrales et les SIG, du fait de son capacité à structurer des données hyper-dimensionnelles. Le chapitre 1 porte sur les deux concepts fondamentaux de tresse et
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Kauniskangas, H. (Hannu). "Document image retrieval with improvements in database quality." Doctoral thesis, University of Oulu, 1999. http://urn.fi/urn:isbn:9514253132.

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Abstract Modern technology has made it possible to produce, process, transmit and store digital images efficiently. Consequently, the amount of visual information is increasing at an accelerating rate in many diverse application areas. To fully exploit this new content-based image retrieval techniques are required. Document image retrieval systems can be utilized in many organizations which are using document image databases extensively. This thesis presents document image retrieval techniques and new approaches to improve database content. The goal of the thesis is to develop a functional re
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Zhou, Yi. "Optimization Algorithms for Clique Problems." Thesis, Angers, 2017. http://www.theses.fr/2017ANGE0013/document.

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Cette thèse présente des algorithmes de résolution de quatre problèmes de clique : clique de poids maximum (MVWCP), s-plex maximum (MsPlex), clique maximum équilibrée dans un graphe biparti (MBBP) et clique partition (CPP). Les trois premiers problèmes sont des généralisations ou relaxations du problème de la clique maximum, tandis que le dernier est un problème de couverture. Ces problèmes, ayant de nombreuses applications pratiques, sont NP-difficiles, rendant leur résolution ardue dans le cas général. Nous présentons ici des algorithmes de recherche locale, principalement basés sur la reche
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Lin, Lei. "Optimization methods for inventive design." Thesis, Strasbourg, 2016. http://www.theses.fr/2016STRAD012/document.

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La thèse traite des problèmes d'invention où les solutions des méthodes d'optimisation ne satisfont pas aux objectifs des problèmes à résoudre. Les problèmes ainsi définis exploitent, pour leur résolution, un modèle de problème étendant le modèle de la TRIZ classique sous une forme canonique appelée "système de contradictions généralisées". Cette recherche instrumente un processus de résolution basé sur la boucle simulation-optimisation-invention permettant d'utiliser à la fois des méthodes d'optimisation et d'invention. Plus précisément, elle modélise l'extraction des contractions généralisée
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Waas, Florian Michael. "Principles of probabilistic query optimization." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2000. http://dare.uva.nl/document/83735.

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Haine, Christopher. "Kernel optimization by layout restructuring." Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0639/document.

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Bien penser la structuration de données est primordial pour obtenir de hautes performances, alors que les processeurs actuels perdent un temps considérable à attendre la complétion de transactions mémoires. En particulier les localités spatiales et temporelles de données doivent être optimisées.Cependant, les transformations de structures de données ne sont pas proprement explorées par les compilateurs, en raison de la difficulté que pose l'évaluation de performance des transformations potentielles. De plus,l'optimisation des structures de données est chronophage, sujette à erreur etles transf
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Decock, Jérémie. "Hybridization of dynamic optimization methodologies." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112359/document.

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Dans ce manuscrit de thèse, mes travaux portent sur la combinaison de méthodes pour la prise de décision séquentielle (plusieurs étapes de décision corrélées) dans des environnements complexes et incertains. Les méthodes mises au point sont essentiellement appliquées à des problèmes de gestion et de production d'électricité tels que l'optimisation de la gestion des stocks d'énergie dans un parc de production pour anticiper au mieux la fluctuation de la consommation des clients.Le manuscrit comporte 7 chapitres regroupés en 4 parties : Partie I, « Introduction générale », Partie II, « État de l
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Books on the topic "Document optimization"

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Mental ray for Maya, 3dsMax, and XSI. Sybex, 2007.

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Marzouka, George R., Lynda Otalvaro-Orozco, and Robert C. Hendel. Guidelines and Appropriate Use Criteria. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199392094.003.0033.

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Multiple documents have been published regarding the use of radionuclide imaging which attempt to outline the applications of SPECT and PET cardiac imaging and to offer guidance in not only how these techniques are performed but also when these tests should be used. These guidance documents, which include position papers, consensus documents, white papers, clinical practice guidelines (CPG), and appropriate use criteria (AUC) serve a number of purposes and are applicable to various health care providers. The focus of this chapter is on CPG and AUC, as these provide the basis for care optimizat
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Rummell, Christina M. Support Groups and Behavioral Science. Edited by Tomasz Rogula, Philip Schauer, and Tammy Fouse. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190608347.003.0003.

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While a psychological evaluation is often a required part of a weight-loss surgery workup, providers are becoming aware of the need for behavioral health services during each phase of the surgery process. Research has documented a higher prevalence of psychiatric comorbidities in severely obese patient populations, with those who receive behavioral health interventions before surgery having better outcomes than those who do not. Common recommendations and interventions for pre- and postoperative behavioral health optimization are reviewed and discussed.Statistics indicate a greater lifetime pr
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Book chapters on the topic "Document optimization"

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Anan, Sabiha, Nazneen Islam, Mohammed Nadir Bin Ali, et al. "Automatic Document Summarization of Unilingual Documents: A Review." In Intelligent Computing and Optimization. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-50327-6_36.

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Nishida, Hirobumi. "Networked Document Imaging with Normalization and Optimization." In Document Analysis Systems VII. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11669487_5.

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Satpute, Meghana N., Luobing Dong, Weili Wu, and Ding-Zhu Du. "Multi-Document Extractive Summarization as a Non-linear Combinatorial Optimization Problem." In Nonlinear Combinatorial Optimization. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16194-1_15.

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Jlassi, Sinda, Imen Jdey, and Hela Ltifi. "Bayesian Hyperparameter Optimization of Deep Neural Network Algorithms Based on Ant Colony Optimization." In Document Analysis and Recognition – ICDAR 2021. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86334-0_38.

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Killani, Ramanji, K. Srinivasa Rao, Suresh Chandra Satapathy, Gunanidhi Pradhan, and K. R. Chandran. "Effective Document Clustering with Particle Swarm Optimization." In Swarm, Evolutionary, and Memetic Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17563-3_73.

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Kumar, Vishal, Manoj Kumar, Simran Sirohi, Ravi Kumar, and Santosh Kumar. "Particle Swarm Optimization for Web Document Retrieval Based on Term-Document Matrix." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8865-3_43.

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Badawy, H. A., E. Emary, Mohamed Yassien, and Mahmoud Fathi. "Discrete Grey Wolf Optimization for Shredded Document Reconstruction." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99010-1_26.

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Su, Yatao. "Optimization and Improvement of Lucene Document Sorting Algorithm." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3250-4_157.

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Wang, Ziqiang, Xin Li, Dexian Zhang, and Feng Wu. "A PSO-Based Web Document Query Optimization Algorithm." In The Semantic Web – ASWC 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11836025_59.

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Charles, Jesse St, Thomas E. Potok, Robert Patton, and Xiaohui Cui. "Flocking-based Document Clustering on the Graphics Processing Unit." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78987-1_3.

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Conference papers on the topic "Document optimization"

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Taşyürek, Efe Yılmaz, Abdullah Himmet Özcan, Sevinç İlhan Omurca, Erol Gerçeker, and Hüseyin Kara. "Screen-cam Resistant Watermarking for Turkish Document Images." In 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA). IEEE, 2025. https://doi.org/10.1109/ichora65333.2025.11017279.

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Xiao, Yan, Yaochu Jin, Haoyu Zhang, Xu Huo, Qiqi Liu, and Zeqi Zheng. "A Personalized Federated Framework for Document-Level Biomedical Relation Extraction." In 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2024. http://dx.doi.org/10.1109/docs63458.2024.10704513.

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Aubakirov, Shakarim, and Iskander Akhmetov. "Dynamic Optimization of Minimum Document Frequency for Extractive Text Summarization Using GreedSum Algorithm." In 2024 20th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS). IEEE, 2024. http://dx.doi.org/10.1109/opcs63516.2024.10720390.

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Magee, John, Stephen Sheridan, and Christina Thorpe. "Optimization of Biomedical Imaging Filters for use in Recaptured Identity Document Classification." In 2023 Cyber Research Conference - Ireland (Cyber-RCI). IEEE, 2023. http://dx.doi.org/10.1109/cyber-rci59474.2023.10671521.

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Sharma, Yagya Dutt, and Parth Sharma. "Dynamic Thresholding in Document Indexing: An Adaptive Scoring Approach for Retrieval Optimization." In 2024 International Conference on Electrical and Computer Engineering Researches (ICECER). IEEE, 2024. https://doi.org/10.1109/icecer62944.2024.10920403.

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Reddy, B. Srikanth, A. Balavivekanandhan, Pallavi Lakhera, Ravindra Changala, R. Sabareesh, and A. Balakumar. "Optimization of BERT Algorithms for Deep Contextual Analysis and Automation in Legal Document Processing." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10723962.

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Senthilkumar, Radha, A. Kannan, D. Vimala, and M. Bhuvaneswari. "Query optimization for inter document relationships in XML structured document." In International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). IEEE, 2007. http://dx.doi.org/10.1109/iccima.2007.363.

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Bafna, Prafulla, Dhanya Pramod, and Anagha Vaidya. "Document clustering: TF-IDF approach." In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7754750.

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Gui, Min, Junfeng Tian, Rui Wang, and Zhenglu Yang. "Attention Optimization for Abstractive Document Summarization." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1117.

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Kido, Yusuke, Hikaru Yokono, Goran Topić, and Akiko Aizawa. "Document Layout Optimization with Automated Paraphrasing." In DocEng '15: ACM Symposium on Document Engineering 2015. ACM, 2015. http://dx.doi.org/10.1145/2682571.2797095.

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Reports on the topic "Document optimization"

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Miner, Nadine E., Alan Stewart Nanco, Kristin L. Adair, et al. Contingency contractor optimization. Phase 2, architecture document. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1055589.

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Jones, Katherine A., Kristin L. Adair, Alisa Bandlow, et al. Contingency contractor optimization. Phase 2, requirements document. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1055604.

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Bandlow, Alisa, Justin David Durfee, Christopher Rawls Frazier, Katherine A. Jones, and Jared Lee Gearhart. Contingency Contractor Optimization Phase 3 Sustainment Requirements Document Contingency Contractor Optimization Tool - Prototype. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1254275.

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Frazier, Christopher Rawls, Justin David Durfee, Alisa Bandlow, Jared Lee Gearhart, and Katherine A. Jones. Contingency Contractor Optimization Phase 3 Sustainment Database Design Document - Contingency Contractor Optimization Tool - Prototype. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1257618.

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Durfee, Justin David, Christopher Rawls Frazier, Alisa Bandlow, and Katherine A. Jones. Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1257619.

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Lapointe, Linda J., and Robert V. Bryant. Operational Concept Document for the Manufacturing Optimization (MO) system. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada250262.

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Lapointe, Linda J., Thomas J. Laliberty, and Robert V. Bryant. System Description Document for the Manufacturing Optimization (MO) System. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada267104.

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Wang, L., and S. N. Atluri. Automated Structural Optimization System (ASTROS) Damage Tolerance Module. Volume 3. Interface Design Document. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada375883.

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Bonomolo, Marina, and Michael Strobel. Building and process optimization potential. IEA SHC Task 65, 2023. http://dx.doi.org/10.18777/ieashc-task65-2023-0003.

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This document is the final report on activity A4 “Building and process optimization” of the IEA SHC Task 65 “Solar Cooling for the Sunbelt regions”. It presents an overview on the relevance of building and process optimization..Several ongoing and completed projects are introduced and results are depicted. In particular, information about completed and running research projects are presented in order to quantify the amount of energy used for cooling systems. Furthermore, main projects related to the IEA EBC (Buildings and Communities Programme) about cooling systems are reported.
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Michalski, A,, D. Andersson, R. Rossi, and C. Soriano. D7.1 DELIVERY OF GEOMETRY AND COMPUTATIONAL MODEL. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.020.

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This document describes the industrial application, on which the developments of the project are implemented, and the CFD set-up. The developments are implemented over six analysis cases with increasing complexity starting from a 2D geometry with mean wind inflow to a 3D geometry with turbulent inflow and real-time shape optimization. The application represents the CAARC tall building model, which has served as a benchmark model for many studies since the 1970’s when it was first developed. Base moments (bending and torsional moments) of the building are extracted for validation by comparison
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