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UNINA990008581860403321 |
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Autore |
Maue, Gerhard |
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Titolo |
Zur Pharmakognosie der Ranunculaceen und Berberidaceen : Anatomie des Laubblattes / Gerhard Maue |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910495724803321 |
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Autore |
Maurel Amélie |
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Titolo |
Les chercheurs saisis par la norme : Contribution à l'étude des droits et devoirs des chercheurs / Amélie Maurel |
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Pubbl/distr/stampa |
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Toulouse, : Presses de l’Université Toulouse 1 Capitole, 2018 |
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Descrizione fisica |
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1 online resource (722 p.) |
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Altri autori (Persone) |
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Soggetti |
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Law |
innovation |
liberté |
valorisation |
arbitrage |
divulgation |
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L'objet de cette thèse est de déterminer quels sont les droits et devoirs des chercheurs. Plus précisément, il s'agit d'examiner comment la norme se saisit des chercheurs dans leur diversité tant dans le processus de recherche - c'est-à-dire pendant la phase du choix des sujets de recherche et celle de la conduite des investigations - qu'après l'obtention d'un résultat scientifique. Il en résulte que, durant le processus de recherche, les chercheurs doivent bénéficier d'une liberté hors du commun afin que puissent librement s'exprimer leurs qualités inventives. Néanmoins, en tant qu'activité humaine oeuvrant pour le bien commun et puissant moteur des économies modernes, la recherche doit être orientée et encadrée par les pouvoirs publics. Une fois le résultat scientifique obtenu, un arbitrage entre différents impératifs opposés - ceux de l'économie et ceux de la recherche - doit être réalisé. Le droit doit, à la fois, inciter à la recherche et à l'innovation, permettre une large et rapide diffusion des résultats ainsi que leur valorisation économique pour que la recherche puisse continuer à progresser. Les droits et devoirs des chercheurs ont, à ce stade, vocation à répondre à ces objectifs. |
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3. |
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UNINA9910502637103321 |
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Titolo |
Natural Language Processing and Chinese Computing : 10th CCF International Conference, NLPCC 2021, Qingdao, China, October 13–17, 2021, Proceedings, Part II / / edited by Lu Wang, Yansong Feng, Yu Hong, Ruifang He |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
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[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (647 pages) |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 13029 |
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Artificial intelligence |
Natural language processing (Computer science) |
Data mining |
Information storage and retrieval systems |
Artificial Intelligence |
Natural Language Processing (NLP) |
Data Mining and Knowledge Discovery |
Information Storage and Retrieval |
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Nota di contenuto |
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Posters - Fundamentals of NLP -- Syntax and Coherence - The Effect on Automatic Argument Quality Assessment -- ExperienceGen 1.0: A Text Generation Challenge Which Requires Deduction and Induction Ability -- Machine Translation and Multilinguality -- SynXLM-R: Syntax-enhanced XLM-R in Translation Quality Estimation -- Machine Learning for NLP -- Memetic Federated Learning for Biomedical Natural Language Processing -- Information Extraction and Knowledge Graph -- Event Argument Extraction via a Distance-Sensitive Graph Convolutional Network -- Exploit Vague Relation: An Augmented Temporal Relation Corpus and Evaluation -- Searching Effective Transformer for Seq2Seq Keyphrase Generation -- Prerequisite Learning with Pre-trained Language and Graph Embedding Models -- Summarization and Generation -- Variational Autoencoder with Interactive Attention for Affective Text Generation -- CUSTOM: Aspect-Oriented Product Summarization for E-Commerce -- Question Answering.-FABERT: A Feature Aggregation BERT-Based Model for Document Reranking -- Generating Relevant, Correct and Fluent Answers in Natural Answer Generation -- GeoCQA: A Large-scale Geography-Domain Chinese Question Answering Dataset from Examination -- Dialogue Systems -- Generating Informative Dialogue Responses with Keywords-Guided Networks -- Zero-Shot Deployment for Cross-Lingual Dialogue System -- MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation -- EmoDialoGPT: Enhancing DialoGPT with Emotion -- Social Media and Sentiment Analysis -- BERT-based Meta-learning Approach with Looking Back for Sentiment Analysis of Literary Book Reviews -- ISWR: an Implicit Sentiment Words Recognition Model Based on Sentiment Propagation -- An Aspect-Centralized Graph Convolutional Network for Aspect-based Sentiment Classification -- NLP Applications and Text Mining -- Capturing Global Informativeness in Open Domain Keyphrase Extraction -- Background Semantic Information Improves VerbalMetaphor Identification -- Multimodality and Explainability -- Towards unifying the explainability evaluation methods for NLP -- Explainable AI Workshop -- Detecting Covariate Drift with Explanations -- A Data-Centric Approach Towards Deducing Bias in Artificial Intelligence Systems for Textual Contexts -- Student Workshop -- Enhancing Model Robustness via Lexical Distilling -- Multi-stage Multi-modal Pre-training for Video Representation -- Nested Causality Extraction on Traffic Accident Texts as Question Answering -- Evaluation Workshop -- MSDF: A General Open-Domain Multi-Skill Dialog Framework -- RoKGDS: A Robust Knowledge Grounded Dialog System -- Enhanced Few-shot Learning with Multiple-Pattern-Exploiting Training -- BIT-Event at NLPCC-2021 Task 3: Subevent Identification via Adversarial Training -- Few-shot Learning for Chinese NLP tasks -- When Few-shot Learning Meets Large-scale Knowledge-enhanced Pre-training: Alibaba at FewCLUE -- TKB²ert: Two-stage Knowledge Infused Behavioral Fine-tuned BERT -- A Unified Information Extraction System Based on Role Recognition and Combination -- A Simple but Effective System for Multi-format Information Extraction -- A Hierarchical Sequence Labeling Model for Argument Pair Extraction -- Distant finetuning with discourse relations |
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for stance classification -- The Solution of Xiaomi AI Lab to the 2021 Language and Intelligence Challenge: Multi-Format Information Extraction Task -- A Unified Platform for Information Extraction with Two-stage Process -- Overview of the NLPCC 2021 Shared Task: AutoIE2 -- Task 1 - Argumentative Text Understanding for AI Debater (AIDebater) -- Two Stage Learning for Argument Pairs Extraction -- Overview of Argumentative Text Understanding for AI Debater Challenge -- ACE: A Context-Enhanced model for Interactive Argument Pair Identification -- Context-Aware and Data-Augmented Transformer for Interactive Argument Pair Identification -- ARGUABLY @ AI Debater-NLPCC 2021 Task 3: Argument Pair Extraction from Peer Review and Rebuttals -- Sentence Rewriting for Fine-Tuned Model Based on Dictionary: Taking the Track 1 of NLPCC 2021 Argumentative Text Understanding for AI Debater as an Example -- Knowledge Enhanced transformers System for Claim Stance Classification. |
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This two-volume set of LNAI 13028 and LNAI 13029 constitutes the refereed proceedings of the 10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021, held in Qingdao, China, in October 2021. The 66 full papers, 23 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 446 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability. |
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