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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 1 – 20 of 103 1 Explainable sentiment analysis application for social media crisis management in retail Jacob, Antonio; Lobato, Fabio; Bezbradica, Marija... In: Cirqueira, Douglas orcid:0000-0002-1283-0453 , Almeida, Fernando, Cakir, Gültekin orcid:0000-0001-9715-7167 , Jacob, Antonio orcid:0000-0002-9415-7265 , Lobato, Fabio orcid:0000-0002-6282-0368 , Bezbradica, Marija orcid:0000-0001-9366-5113 and Helfert, Markus orcid:0000-0001-6546-6408 (2020) Explainable sentiment analysis application for social media crisis management in retail. In: 4th International Conference on Computer-Human Interaction Research and Applications - Volume 1: WUDESHI-DR, 5-6 Nov 2020, Budapest, Hungry (Online). ISBN 978-989-758-480-0 (2020) BASE Show details 2 Using Twitter Streams for Opinion Mining: a case study on Airport Noise Meddeb, Iheb; Lavandier, Catherine; Kotzinos, Dimitris In: ISSN: 1865-0929 ; Communications in Computer and Information Science ; https://hal.archives-ouvertes.fr/hal-03018998 ; Communications in Computer and Information Science, Springer Verlag, 2020, ⟨10.1007/978-3-030-44900-1_10⟩ (2020) BASE Show details 3 An Algerian Corpus and an Annotation Platform for Opinion and Emotion Analysis Moudjari, Leila; Akli-Astouati, Karima; Benamara, Farah In: Proceedings of the 12th Language Resources and Evaluation Conference ; 12th Language Resources and Evaluation Conference, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-03102495 ; 12th Language Resources and Evaluation Conference, LREC 2020, May 2020, Marseille, France. pp.1202-1210 ; https://www.aclweb.org/anthology/2020.lrec-1.151/ (2020) BASE Show details 4 Affective behavior modeling on social networks ; Modélisation des sentiments sur les réseaux sociaux Ragheb, Waleed. - : HAL CCSD, 2020 In: https://tel.archives-ouvertes.fr/tel-03339755 ; Social and Information Networks [cs.SI]. Université Montpellier, 2020. English. ⟨NNT : 2020MONTS073⟩ (2020) BASE Show details 5 An Enhanced Corpus for Arabic Newspapers Comments Rahab, Hichem; Zitouni, Abdelhafid; Djoudi, Mahieddine In: ISSN: 1683-3198 ; International Arab Journal of Information Technology ; https://hal.archives-ouvertes.fr/hal-03124728 ; International Arab Journal of Information Technology, Colleges of Computing and Information Society (CCIS), 2020, 17 (5), pp.789-798. ⟨10.34028/iajit/17/5/12⟩ (2020) BASE Show details 6 Clickbait detection using multimodel fusion and transfer learning ; Détection de clickbait utilisant fusion multimodale et apprentissage par transfert Praboda Chathurangani Rajapaksha, Rajapaksha Waththe Vidanelage. - : HAL CCSD, 2020 In: https://tel.archives-ouvertes.fr/tel-03139880 ; Social and Information Networks [cs.SI]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAS025⟩ (2020) BASE Show details 7 Neural approach for Arabic sentiment analysis ; Une approche neuronale pour l’analyse d’opinions en arabe Barhoumi, Amira. - : HAL CCSD, 2020 In: https://tel.archives-ouvertes.fr/tel-03084468 ; Informatique et langage [cs.CL]. Université du Maine; Université de Sfax (Tunisie), 2020. Français. ⟨NNT : 2020LEMA1022⟩ (2020) BASE Show details 8 ПРИМЕНЕНИЕ ТЕХНОЛОГИИ WORD2VEC В ЗАДАЧЕ ВЫДЕЛЕНИЯ ИНВЕРТОРОВ ТОНАЛЬНОСТИ ... : APPLYING WORD2VEC TECHNOLOGY TO SHIFTER EXTRACTION TASK ... Полозов, И.К.; Волкова, И.А.. - : Международный научно-исследовательский журнал, 2020 BASE Show details 9 BanglaEmotion: A Benchmark Dataset for Bangla Textual Emotion Analysis ... Rahman, Md Ataur. - : Mendeley, 2020 BASE Show details 10 BanglaEmotion: A Benchmark Dataset for Bangla Textual Emotion Analysis ... Rahman, Md Ataur. - : Mendeley, 2020 BASE Show details 11 Hotel Review Sentiment Analysis using Natural Language Processing ... Λυκεσάς, Αλέξανδρος Γεωργίου. - : Aristotle University of Thessaloniki, 2020 BASE Show details 12 Czech image captioning, machine translation, sentiment analysis and summarization (Neural Monkey models) Libovický, Jindřich; Rosa, Rudolf; Helcl, Jindřich; Popel, Martin. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2020 Abstract: This submission contains trained end-to-end models for the Neural Monkey toolkit for Czech and English, solving four NLP tasks: machine translation, image captioning, sentiment analysis, and summarization. The models are trained on standard datasets and achieve state-of-the-art or near state-of-the-art performance in the tasks. The models are described in the accompanying paper. The same models can also be invoked via the online demo: https://ufal.mff.cuni.cz/grants/lsd In addition to the models presented in the referenced paper (developed and published in 2018), we include models for automatic news summarization for Czech and English developed in 2019. The Czech models were trained using the SumeCzech dataset (https://www.aclweb.org/anthology/L18-1551.pdf), the English models were trained using the CNN-Daily Mail corpus (https://arxiv.org/pdf/1704.04368.pdf) using the standard recurrent sequence-to-sequence architecture. There are several separate ZIP archives here, each containing one model solving one of the tasks for one language. To use a model, you first need to install Neural Monkey: https://github.com/ufal/neuralmonkey To ensure correct functioning of the model, please use the exact version of Neural Monkey specified by the commit hash stored in the 'git_commit' file in the model directory. Each model directory contains a 'run.ini' Neural Monkey configuration file, to be used to run the model. See the Neural Monkey documentation to learn how to do that (you may need to update some paths to correspond to your filesystem organization). The 'experiment.ini' file, which was used to train the model, is also included. Then there are files containing the model itself, files containing the input and output vocabularies, etc. For the sentiment analyzers, you should tokenize your input data using the Moses tokenizer: https://pypi.org/project/mosestokenizer/ For the machine translation, you do not need to tokenize the data, as this is done by the model. For image captioning, you need to: - download a trained ResNet: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz - clone the git repository with TensorFlow models: https://github.com/tensorflow/models - preprocess the input images with the Neural Monkey 'scripts/imagenet_features.py' script (https://github.com/ufal/neuralmonkey/blob/master/scripts/imagenet_features.py) -- you need to specify the path to ResNet and to the TensorFlow models to this script The summarization models require input that is tokenized with Moses Tokenizer (https://github.com/alvations/sacremoses) and lower-cased. Feel free to contact the authors of this submission in case you run into problems! Keyword: image captioning; machine translation; Neural Monkey; neural networks; sentiment analysis; summarization; transformer URL: http://hdl.handle.net/11234/1-3145 BASE Hide details 13 A sentiment analysis dataset for code-mixed Malayalam-English Sherly, Elizabeth; Jose, Navya; McCrae, John P.. - : European Language Resources Association (ELRA), 2020 BASE Show details 14 How Combining Terrorism, Muslim, and Refugee Topics Drives Emotional Tone in Online News: A Six-Country Cross-Cultural Sentiment Analysis Chan, Chung-Hong; Wessler, Hartmut; Rinke, Eike Mark... In: International Journal of Communication; Vol 14 (2020); 26 ; 1932-8036 (2020) BASE Show details 15 A Sentiment Analysis Dataset for Code-Mixed Malayalam-English ... Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul. - : Zenodo, 2020 BASE Show details 16 Evaluation of literature by professional and layperson critics. A digital and literary sociological analysis of evaluative talk of literature through the prism of literary prizes (2007-2017) ... De Greve, Lore; Martens, Gunther; Hoste, Veronique. - : Zenodo, 2020 BASE Show details 17 A Sentiment Analysis Dataset for Code-Mixed Malayalam-English ... Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul. - : Zenodo, 2020 BASE Show details 18 Evaluation of literature by professional and layperson critics. A digital and literary sociological analysis of evaluative talk of literature through the prism of literary prizes (2007-2017) ... De Greve, Lore; Martens, Gunther; Hoste, Veronique. - : Zenodo, 2020 BASE Show details 19 Distant Spectators: Distant Reading for periodicals of the Enlightenment ... Geiger, Bernhard; Hobisch, Elisabeth; Koncar, Philipp. - : Zenodo, 2020 BASE Show details 20 Distant Spectators: Distant Reading for periodicals of the Enlightenment ... Geiger, Bernhard; Hobisch, Elisabeth; Koncar, Philipp. - : Zenodo, 2020 BASE Show details Page: 1 2 3 4 5 6

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