Inhaltsverzeichnis
Auswahl der wissenschaftlichen Literatur zum Thema „Task oriented dialogue system“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Machen Sie sich mit den Listen der aktuellen Artikel, Bücher, Dissertationen, Berichten und anderer wissenschaftlichen Quellen zum Thema "Task oriented dialogue system" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Zeitschriftenartikel zum Thema "Task oriented dialogue system"
Xiang, Lu, Junnan Zhu, Yang Zhao, Yu Zhou und Chengqing Zong. „Robust Cross-lingual Task-oriented Dialogue“. ACM Transactions on Asian and Low-Resource Language Information Processing 20, Nr. 6 (30.11.2021): 1–24. http://dx.doi.org/10.1145/3457571.
Der volle Inhalt der QuelleMatsumoto, Kazuyuki, Manabu Sasayama und Taiga Kirihara. „Topic Break Detection in Interview Dialogues Using Sentence Embedding of Utterance and Speech Intention Based on Multitask Neural Networks“. Sensors 22, Nr. 2 (17.01.2022): 694. http://dx.doi.org/10.3390/s22020694.
Der volle Inhalt der QuelleZhu, Qi, Kaili Huang, Zheng Zhang, Xiaoyan Zhu und Minlie Huang. „CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset“. Transactions of the Association for Computational Linguistics 8 (Juli 2020): 281–95. http://dx.doi.org/10.1162/tacl_a_00314.
Der volle Inhalt der QuelleWu, Zhong, Qiping She und Chuan Zhou. „Intelligent Customer Service System Optimization Based on Artificial Intelligence“. Journal of Organizational and End User Computing 36, Nr. 1 (07.02.2024): 1–27. http://dx.doi.org/10.4018/joeuc.336923.
Der volle Inhalt der QuelleZhang, Zheng, Minlie Huang, Zhongzhou Zhao, Feng Ji, Haiqing Chen und Xiaoyan Zhu. „Memory-Augmented Dialogue Management for Task-Oriented Dialogue Systems“. ACM Transactions on Information Systems 37, Nr. 3 (20.07.2019): 1–30. http://dx.doi.org/10.1145/3317612.
Der volle Inhalt der QuelleIizuka, Shinya, Shota Mochizuki, Atsumoto Ohashi, Sanae Yamashita, Ao Guo und Ryuichiro Higashinaka. „Clarifying the Dialogue-Level Performance of GPT-3.5 and GPT-4 in Task-Oriented and Non-Task-Oriented Dialogue Systems“. Proceedings of the AAAI Symposium Series 2, Nr. 1 (22.01.2024): 182–86. http://dx.doi.org/10.1609/aaaiss.v2i1.27668.
Der volle Inhalt der QuelleZENG, Ya, Li WAN, Qiuhong LUO und Mao CHEN. „A Hierarchical Memory Model for Task-Oriented Dialogue System“. IEICE Transactions on Information and Systems E105.D, Nr. 8 (01.08.2022): 1481–89. http://dx.doi.org/10.1587/transinf.2022edp7001.
Der volle Inhalt der QuelleMORIN, PHILIPPE, JEAN-PAUL HATON, JEAN-MARIE PIERREL, GUENTHER RUSKE und WALTER WEIGEL. „A MULTILINGUAL APPROACH TO TASK-ORIENTED MAN-MACHINE DIALOGUE BY VOICE“. International Journal of Pattern Recognition and Artificial Intelligence 02, Nr. 03 (September 1988): 573–88. http://dx.doi.org/10.1142/s0218001488000339.
Der volle Inhalt der QuelleYoung, Tom, Frank Xing, Vlad Pandelea, Jinjie Ni und Erik Cambria. „Fusing Task-Oriented and Open-Domain Dialogues in Conversational Agents“. Proceedings of the AAAI Conference on Artificial Intelligence 36, Nr. 10 (28.06.2022): 11622–29. http://dx.doi.org/10.1609/aaai.v36i10.21416.
Der volle Inhalt der QuelleDong, Xuelian, und Jiale Chen. „PluDG: enhancing task-oriented dialogue system with knowledge graph plug-in module“. PeerJ Computer Science 9 (24.11.2023): e1707. http://dx.doi.org/10.7717/peerj-cs.1707.
Der volle Inhalt der QuelleDissertationen zum Thema "Task oriented dialogue system"
ISOMURA, Naoki, Fujio TORIUMI und Kenichiro ISHII. „EVALUATION METHOD OF NON-TASK-ORIENTED DIALOGUE SYSTEM BY HMM“. INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2006. http://hdl.handle.net/2237/10479.
Der volle Inhalt der QuelleYang, Fan. „Directing the flow of conversation in task-oriented dialogue“. Full text open access at:, 2008. http://content.ohsu.edu/u?/etd,625.
Der volle Inhalt der QuelleBalaraman, Vevake. „Leveraging Domain Information for Data Driven Task-Oriented Dialogue Systems“. Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/339652.
Der volle Inhalt der QuelleLinné, Christoffer, und Pontus Olausson. „Crowdsourcing av data för Hybrid Code Networks“. Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281968.
Der volle Inhalt der QuelleUppgiftsorienterade dialogsystem är ett populärt sätt för företag att generera extra värde både internt och för kunder. Moderna modeller för dessa dialogsystem som använder neurala nätverk för att möjliggöra träning direkt på skriftliga dialoger är väldigt datahungriga, vilket försvårar implementationen av dessa. Crowdsourcing är en attraktiv lösning för att generera denna typ av träningsdata, men metoden kommer även med flera svårigheter. Vi introducerar en ny metod för generering av träningsdata som bygger på parallell crowdsourcing av dialoger, samt crowdsourcad kvalitetsgranskning. Vi använder denna metod för att samla in ett litet dataset som utspelar sig inom domänen busschaufför-resenär. Vi menar att denna metod erbjuder ett effektivt sätt att samla in nya, högkvalitativa dataset. Hybrid Code Networks är en modell för dialogsystem som kombinerar ett neuralt nätverk med domänspecifik kunskap, och som på så sätt kräver en betydligt mindre mängd träningsdata än andra liknande dialogsystem för att uppnå jämförbar prestanda. Genom att kombinera Hybrid Code Networks med vår nya metod för generering av träningsdata menar vi att man kan sänka tröskeln för att implementera uppgiftsorienterade dialogsystem på domäner med otillräcklig träningsdata. Vi implementerar Hybrid Code Networks och tränar implementationen på det insamlade datasetet, och uppnår goda resultat.
Veron, Mathilde. „Systèmes de dialogue apprenant tout au long de leur vie : de l'élaboration à l'évaluation“. Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG089.
Der volle Inhalt der QuelleTask-oriented dialogue systems, more commonly known as chatbots, are intended to perform tasks and provide the information required by a user in a conversation in a specific domain (e.g., train booking). These systems have been widely adopted by many companies. However, they suffer in practice from some limitations: (1) they are dependent on the training data needed to obtain a performing system, (2) they lack flexibility and perform poorly as soon as the case encountered in practice moves away from the data seen during development, and (3) it is difficult to adapt them over time to new elements that appear given the inevitable evolution of the world, of the requirements of the designers and users. Thus, we apply Lifelong Learning (LL) to task-oriented dialogue systems. We define LL as the ability of a system to be applied to and learn multiple tasks over time, in production, autonomously, continuously, and interactively. Three steps must be performed in autonomy by the system: (1) Detect the presence of a new element, (2) extract and identify the new element, and (3) adapt the system components associated with this element. As part of this thesis and given the complexity of LL, we focus our work on three subproblems associated with LL dialogue systems. As a first step, we propose a first methodology for the continuous and time-dependent evaluation of on-the-job learning dialogue systems. This type of learning is close to LL but puts aside the multitask aspect. We also describe a task-oriented dialogue system capable of improving its slot detection on-the-job via the autonomous annotation of data collected during its interactions. We evaluate this system through two adaptation methods using our methodology and show interest in a continuous evaluation over time. As a second step, we focus on the innovative study of interlingual transfer when applying continual learning to a language sequence. Indeed, transfer and continual learning are two main aspects of LL. We perform this study on the slot-filling task using multilingual BERT. We observe substantial forward transfer capabilities despite the presence of forgetting and demonstrate the capabilities of a model trained in a continual manner. As a third step, we study inter-domain transfer in the context of zero-shot learning. We carry out this study on a task that requires considering the whole dialogue and not only the current turn, which corresponds to the dialogue state tracking task. We first study the generalization and transfer capabilities of an existing model on new slot values. Then, we propose some model variants and a method able to improve the zero-shot performance of the model on new types of slots belonging to a new domain
Bouguelia, Sara. „Modèles de dialogue et reconnaissance d'intentions composites dans les conversations Utilisateur-Chatbot orientées tâches“. Electronic Thesis or Diss., Lyon 1, 2023. http://www.theses.fr/2023LYO10106.
Der volle Inhalt der QuelleDialogue Systems (or simply chatbots) are in very high demand these days. They enable the understanding of user needs (or user intents), expressed in natural language, and on fulfilling such intents by invoking the appropriate back-end APIs (Application Programming Interfaces). Chatbots are famed for their easy-to-use interface and gentle learning curve (it only requires one of humans' most innate ability, the use of natural language). The continuous improvement in Artificial Intelligence (AI), Natural Language Processing (NLP), and the countless number of devices allow performing real-world tasks (e.g., making a reservation) by using natural language-based interactions between users and a large number of software enabled services.Nonetheless, chatbot development is still in its preliminary stage, and there are several theoretical and technical challenges that need to be addressed. One of the challenges stems from the wide range of utterance variations in open-end human-chatbot interactions. Additionally, there is a vast space of software services that may be unknown at development time. Natural human conversations can be rich, potentially ambiguous, and express complex and context-dependent intents. Traditional business process and service composition modeling and orchestration techniques are limited to support such conversations because they usually assume a priori expectation of what information and applications will be accessed and how users will explore these sources and services. Limiting conversations to a process model means that we can only support a small fraction of possible conversations. While existing advances in NLP and Machine Learning (ML) techniques automate various tasks such as intent recognition, the synthesis of API calls to support a broad range of potentially complex user intents is still largely a manual, ad-hoc and costly process.This thesis project aims at advancing the fundamental understanding of cognitive services engineering. In this thesis we contribute novel abstractions and techniques focusing on the synthesis of API calls to support a broad range of potentially complex user intents. We propose reusable and extensible techniques to recognize and realize complex intents during humans-chatbots-services interactions. These abstractions and techniques seek to unlock the seamless and scalable integration of natural language-based conversations with software-enabled services
Schaub, Léon-Paul. „Dimensions mémorielles de l'interaction écrite humain-machine ˸ une approche cognitive par les modèles mnémoniques pour la détection et la correction des incohérences du système dans les dialogues orientés-tâche“. Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG023.
Der volle Inhalt der QuelleIn this work, we are interested in the place of task-oriented dialogue systems in both automatic language processing and human-machine interaction. In particular, we focus on the difference in information processing and memory use, from one turn to the next, by humans and machines, during a written chat conversation. After having studied the mechanisms of memory retention and recall in humans during a dialogue, in particular during the accomplishment of a task, we hypothesize that one of the elements that may explain why the performance of machines remains below that of humans, is the ability to possess not only an image of the user, but also an image of oneself, explicitly summoned during the inferences linked to the continuation of the dialogue. This translates into the following three axes for the system. First, by the anticipation, at a given turn of speech, of the next turn of the user. Secondly, by the detection of an inconsistency in one's own utterance, facilitated, as we demonstrate, by the anticipation of the user's next turn as an additional cue. Finally, by predicting the number of remaining turns in the dialogue in order to have a better vision of the dialogue progression, taking into account the potential presence of an incoherence in one's own utterance, this is what we call the dual model of the system, which represents both the user and the image that the system sends to the user. To implement these features, we exploit end-to-end memory networks, a recurrent neural network model that has the specificity not only to handle long dialogue histories (such as an RNN or an LSTM) but also to create reflection jumps, allowing to filter the information contained in both the user's utterance and the dialogue history. In addition, these three reflection jumps serve as a "natural" attention mechanism for the memory network, similar to a transformer decoder. For our study, we enhance a type of memory network called WMM2Seq (sequence-based working memory network) by adding our three features. This model is inspired by cognitive models of memory, presenting the concepts of episodic memory, semantic memory and working memory. It performs well on dialogue response generation tasks on the DSTC2 (human-machine in the restaurant domain) and MultiWOZ (multi-domain created with Wizard of Oz) corpora; these are the corpora we use for our experiments. The three axes mentioned above bring two main contributions to the existing. Firstly, it adds complexity to the intelligence of the dialogue system by providing it with a safeguard (detected inconsistencies). Second, it optimizes both the processing of information in the dialogue (more accurate or richer answers) and the duration of the dialogue. We evaluate the performance of our system with firstly the F1 score for the entities detected in each speech turn, secondly the BLEU score for the fluency of the system utterance and thirdly the joint accuracy for the success of the dialogue. The results obtained show that it would be interesting to direct research towards more cognitive models of memory management in order to reduce the performance gap in a human-machine dialogue
Kowtko, J. C. „The function of intonation in task-oriented dialogue“. Thesis, University of Edinburgh, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508706.
Der volle Inhalt der QuelleCarletta, Jean. „Risk-taking and recovery in task-oriented dialogue“. Thesis, University of Edinburgh, 1992. http://hdl.handle.net/1842/20370.
Der volle Inhalt der QuelleSotillo, Catherine Frances. „Phonological reduction and intelligibility in task-oriented dialogue“. Thesis, University of Edinburgh, 1997. http://hdl.handle.net/1842/21544.
Der volle Inhalt der QuelleBücher zum Thema "Task oriented dialogue system"
Taboada, María Teresa. Building coherence and cohesion: Task-oriented dialogue in English and Spanish. Philadelphia: John Benjamins Pub. Co., 2004.
Den vollen Inhalt der Quelle findenTaboada, María Teresa. Building coherence and cohesion: Task-oriented dialogue in English and Spanish. Amsterdam: J. Benjamins, 2004.
Den vollen Inhalt der Quelle findenTaboada, María Teresa. Building coherence and cohesion: Task-oriented dialogue in English and Spanish. Amsterdam: John Benjamins, 2003.
Den vollen Inhalt der Quelle findenBernhaupt, Regina. Human-Centred Software Engineering: Third International Conference, HCSE 2010, Reykjavik, Iceland, October 14-15, 2010. Proceedings. Berlin, Heidelberg: IFIP International Federation of Information Processing, 2010.
Den vollen Inhalt der Quelle findenDadyan, Eduard. Modern programming technologies. The C#language. Volume 2. For advanced users. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1478383.
Der volle Inhalt der QuelleLeech, Geoffrey. Pragmatics and Dialogue. Herausgegeben von Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0007.
Der volle Inhalt der QuelleWatson, Craig. Task-Oriented Performance: The Top Management System. Ballinger Pub Co, 1988.
Den vollen Inhalt der Quelle findenKim, Joong Nam. An agent-based cockpit task management system: A task-oriented pilot-vehicle interface. 1994.
Den vollen Inhalt der Quelle findenKim, Joong Nam. An agent-based cockpit task management system: A task-oriented pilot-vehicle interface. 1994.
Den vollen Inhalt der Quelle findenLarson, Victoria M. Task-Oriented, Naturally Elicited Speech (TONE) database for the Force Requirements Expert System, Hawaii (FRESH). 1988.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Task oriented dialogue system"
Peng, Yan, Penghe Chen, Yu Lu, Qinggang Meng, Qi Xu und Shengquan Yu. „A Task-Oriented Dialogue System for Moral Education“. In Lecture Notes in Computer Science, 392–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23207-8_72.
Der volle Inhalt der QuelleMazumder, Sahisnu, und Bing Liu. „Continual Learning for Task-Oriented Dialogue Systems“. In Synthesis Lectures on Human Language Technologies, 127–51. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-48189-5_6.
Der volle Inhalt der QuelleVogel, Liane, und Lucie Flek. „Investigating Paraphrasing-Based Data Augmentation for Task-Oriented Dialogue Systems“. In Text, Speech, and Dialogue, 476–88. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16270-1_39.
Der volle Inhalt der QuelleBerg, Markus M., Antje Düsterhöft und Bernhard Thalheim. „Towards Interrogative Types in Task-Oriented Dialogue Systems“. In Natural Language Processing and Information Systems, 302–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31178-9_38.
Der volle Inhalt der QuelleFang, Ting, Tingting Qiao und Duanqing Xu. „HaGAN: Hierarchical Attentive Adversarial Learning for Task-Oriented Dialogue System“. In Neural Information Processing, 98–109. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36708-4_9.
Der volle Inhalt der QuelleSteindl, Sebastian, Ulrich Schäfer und Bernd Ludwig. „Generating Synthetic Dialogues from Prompts to Improve Task-Oriented Dialogue Systems“. In KI 2023: Advances in Artificial Intelligence, 207–14. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-42608-7_17.
Der volle Inhalt der QuelleVeron, Mathilde, Sahar Ghannay, Anne-Laure Ligozat und Sophie Rosset. „Lifelong Learning and Task-Oriented Dialogue System: What Does It Mean?“ In Lecture Notes in Electrical Engineering, 347–56. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9323-9_32.
Der volle Inhalt der QuelleCarbonell, N., und J. M. Pierrel. „Task-Oriented Dialogue Processing in Human-Computer Voice Communication“. In Recent Advances in Speech Understanding and Dialog Systems, 491–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83476-9_46.
Der volle Inhalt der QuelleMarques, Tânia. „Towards a Taxonomy of Task-Oriented Domains of Dialogue“. In PRIMA 2015: Principles and Practice of Multi-Agent Systems, 510–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25524-8_33.
Der volle Inhalt der QuelleChauhan, Anamika, Aditya Malhotra, Anushka Singh, Jwalin Arora und Shubham Shukla. „Encoding Context in Task-Oriented Dialogue Systems Using Intent, Dialogue Acts, and Slots“. In Innovations in Computer Science and Engineering, 287–95. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2043-3_34.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Task oriented dialogue system"
Blache, Philippe. „Dialogue management in task-oriented dialogue systems“. In ICMI '17: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3139491.3139507.
Der volle Inhalt der QuelleWei, Zhongyu, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong und Xiangying Dai. „Task-oriented Dialogue System for Automatic Diagnosis“. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-2033.
Der volle Inhalt der QuelleLi, Qian, und Xinmeng Li. „Memory-Augmented Dialogue State Tracker in Task-Oriented Dialogue System“. In 2020 International Conference on Computer Information and Big Data Applications (CIBDA). IEEE, 2020. http://dx.doi.org/10.1109/cibda50819.2020.00100.
Der volle Inhalt der QuelleHu, Xiangkun, Junqi Dai, Hang Yan, Yi Zhang, Qipeng Guo, Xipeng Qiu und Zheng Zhang. „Dialogue Meaning Representation for Task-Oriented Dialogue Systems“. In Findings of the Association for Computational Linguistics: EMNLP 2022. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.findings-emnlp.17.
Der volle Inhalt der QuelleXing, Xulei, und Zelong Wang. „Probabilistic Dialogue Model Combined With VAE For Task-oriented Dialogue System“. In 2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT). IEEE, 2021. http://dx.doi.org/10.1109/cecit53797.2021.00154.
Der volle Inhalt der QuelleMu, Yanhua, und YiXin Yin. „Task-Oriented Spoken Dialogue System for Humanoid Robot“. In 2010 International Conference on Multimedia Technology (ICMT). IEEE, 2010. http://dx.doi.org/10.1109/icmult.2010.5631205.
Der volle Inhalt der QuelleWang, Weizhi, Zhirui Zhang, Junliang Guo, Yinpei Dai, Boxing Chen und Weihua Luo. „Task-Oriented Dialogue System as Natural Language Generation“. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3477495.3531920.
Der volle Inhalt der QuelleSong, Meina, Zhongfu Chen, Peiqing Niu und E. Haihong. „Task-oriented Dialogue System Based on Reinforcement Learning“. In 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS). IEEE, 2019. http://dx.doi.org/10.1109/icsess47205.2019.9040789.
Der volle Inhalt der QuelleSun, Shaochen, Youlang Ji, Hongying Zhao und Yang Yu. „Knowledge Graph Driven Dialogue Management for Task-oriented Dialogue“. In 2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS). IEEE, 2020. http://dx.doi.org/10.1109/icicas51530.2020.00012.
Der volle Inhalt der QuelleZhao, Xinyan, Bin He, Yasheng Wang, Yitong Li, Fei Mi, Yajiao Liu, Xin Jiang, Qun Liu und Huanhuan Chen. „UniDS: A Unified Dialogue System for Chit-Chat and Task-oriented Dialogues“. In Proceedings of the Second DialDoc Workshop on Document-grounded Dialogue and Conversational Question Answering. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.dialdoc-1.2.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Task oriented dialogue system"
Traum, David R., und Elizabeth A. Hinkelman. Conversation Acts in Task-Oriented Spoken Dialogue. Fort Belvoir, VA: Defense Technical Information Center, Juni 1992. http://dx.doi.org/10.21236/ada256368.
Der volle Inhalt der QuelleБакум, З. П., und В. О. Лапіна. Educational Dialogue in the Process of Foreign Language Training of Future Miners. Криворізький державний педагогічний університет, 2014. http://dx.doi.org/10.31812/0564/395.
Der volle Inhalt der QuelleHeredia, Blanca. The Political Economy of Reform of the Administrative Systems of Public Sector Personnel in Latin America: An Analytical Framework. Inter-American Development Bank, November 2002. http://dx.doi.org/10.18235/0012273.
Der volle Inhalt der QuellePinchuk, O. P., und A. A. Prokopenko. Model of a computer-orient-ed methodological system for the development of digital competence of officers of the military administration of the Armed Forces of Ukraine in the system of qualification improvement. Національна академія Державної прикордонної служби України імені Б. Хмельницького, 2023. http://dx.doi.org/10.33407/lib.naes.736836.
Der volle Inhalt der QuelleFreeman, Paul, Leslie A. Martin, Joanne Linnerooth-Bayer, Reinhard Mechler, Georg Pflug und Koko Warner. Disaster Risk Management: National Systems for the Comprehensive Management of Disaster Risk and Financial Strategies for Natural Disaster Reconstruction. Inter-American Development Bank, November 2003. http://dx.doi.org/10.18235/0010539.
Der volle Inhalt der QuelleShyshkina, Mariya P. The use of the cloud services to support the math teachers training. [б. в.], Juli 2020. http://dx.doi.org/10.31812/123456789/3897.
Der volle Inhalt der QuelleBaader, Franz, und Barbara Morawska. Matching with respect to general concept inclusions in the Description Logic EL. Technische Universität Dresden, 2014. http://dx.doi.org/10.25368/2022.205.
Der volle Inhalt der Quelle