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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 Hits 1 – 18 of 18 1 A bilingual approach to specialised adjectives through word embeddings in the karstology domain ... Simeunović, Larisa Grčić; Martinc, Matej; Vintar, Špela. - : arXiv, 2022 BASE Show details 2 A bilingual approach to specialised adjectives through word embeddings in the karstology domain ... Grčić Simeunović, Larisa; Martinc, Matej; Vintar, Špela. - : Zenodo, 2022 BASE Show details 3 A bilingual approach to specialised adjectives through word embeddings in the karstology domain ... Grčić Simeunović, Larisa; Martinc, Matej; Vintar, Špela. - : Zenodo, 2022 BASE Show details 4 EMBEDDIA tools output example corpus of Estonian, Croatian and Latvian news articles 1.0 Freienthal, Linda; Pelicon, Andraž; Martinc, Matej; Škrlj, Blaž; Krustok, Ivar; Pranjić, Marko; Cabrera-Diego, Luis Adrián; Purver, Matthew; Pollak, Senja; Kuulmets, Hele-Andra; Shekhar, Ravi; Koloski, Boshko. - : Ekspress Meedia Group, 2022. : Styria Media Group, 2022 Abstract: This dataset contains articles from EMBEDDIA Media partners with various information added by the tools developed within the EMBEDDIA project: - 12,390 Estonian articles from 2019 with tags given by Ekspress Meedia. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1408 - 5,000 Croatian articles from autumn of 2010 with tags given by 24sata. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1410 - 15,264 Latvian articles from 2019 with tags given by Ekspress Meedia. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1409 All the articles in the dataset have been analysed with texta-mlp Python package (https://pypi.org/project/texta-mlp/) via the EMBEDDIA Media assistant's Texta Toolkit (https://docs.texta.ee/). The tools used to analyse the articles were the following: - Latin1 and Latin2 Name Entity Recognition Tool modules (Cabrera-Diego et al., 2021, both described in https://aclanthology.org/2021.bsnlp-1.12/) . The Latin 1 results can be found folders annotated_articles_ner_latin1/ and annotated_articles_all_tools/, while the Latin 2 results are in annotated_articles_nerlatin2/ or annotated_articles_all_tools/. - RAKUN keyword extractor. RAKUN (Škrlj et al. 2019) is an unsupervised system for keyword extraction, so it can be used for any language. It detects keywords by turning text into a graph and the most important nodes in the graph mostly turn out to be the keywords. It is described in https://link.springer.com/chapter/10.1007/978-3-030-31372-2_26. The keyword annotation results can be found in the folder annotated_articles_rakun/ or annotated_articles_all_tools/. - TNT-KID keyword extractor. TNT-KID (Martinc et al. 2021, ) is a supervised system for automatic keyword extraction. It was trained on a corpus of articles with human-assigned keywords. For Croatian, the annotators were 24sata editors, for Estonian the Ekspress Meedia staff and for Latvian the Latvian Delfi staff. The system is further documented at https://doi.org/10.1017/S1351324921000127. For Croatian only TNT-KID was applied, while for Estonian and Latvian, the TNT-KID with TF-IDF, and extension by Koloski et al. (https://aclanthology.org/2021.hackashop-1.4.pdf) was used. The results of applying this tool are found in the folder annotated articles tnt_kid/ or annotated articles all tools/. - Sentiment analysis. Our news sentiment analyser (Pelicon et al. 2020) labels a news article as being of positive, negative, or neutral sentiment, using a fine-tuned multilingual BERT model, which was trained on Slovene sentiment annotated news articles. The system is further documented in https://doi.org/10.3390/app10175993. The results of this tools are found in the folder annotated articles sentiment/ or annotated articles all tools/. All the data is encoded in "JSON Lines" format. Each folder has its own README file which explains the structure of the files. Keyword: keyword extraction; named entity recognition; sentiment classification URL: http://hdl.handle.net/11356/1485 BASE Hide details 5 Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised? ... Koloski, Boshko; Pollak, Senja; Škrlj, Blaž. - : arXiv, 2022 BASE Show details 6 Word-embedding based bilingual terminology alignment ... Repar, Andraž; Martinc, Matej; Ulčar, Matej. - : Zenodo, 2021 BASE Show details 7 Word-embedding based bilingual terminology alignment ... Repar, Andraž; Martinc, Matej; Ulčar, Matej. - : Zenodo, 2021 BASE Show details 8 Keyword extraction datasets for Croatian, Estonian, Latvian and Russian 1.0 Koloski, Boshko; Pollak, Senja; Škrlj, Blaž. - : Ekspress Meedia Group, 2021. : Styria Media Group, 2021 BASE Show details 9 24sata news article archive 1.0 Purver, Matthew; Shekhar, Ravi; Pranjić, Marko. - : Styria Media Group, 2021 BASE Show details 10 Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings not Always Better Than Static for Semantic Change Detection ... Martinc, Matej; Montariol, Syrielle; Zosa, Elaine. - : Zenodo, 2021 BASE Show details 11 Discovery Team at SemEval-2020 Task 1: Context-sensitive Embeddings not Always Better Than Static for Semantic Change Detection ... Martinc, Matej; Montariol, Syrielle; Zosa, Elaine. - : Zenodo, 2021 BASE Show details 12 Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech Martinc, Matej; Haider, Fasih; Pollak, Senja... In: Front Aging Neurosci (2021) BASE Show details 13 Mining semantic relations from comparable corpora through intersections of word embeddings. ... Vintar, Špela; Grčič Simeunovič, Larisa; Martinc, Matej. - : Zenodo, 2020 BASE Show details 14 Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift ... Martinc, Matej; Kralj Novak, Petra; Pollak, Senja. - : Zenodo, 2020 BASE Show details 15 Mining semantic relations from comparable corpora through intersections of word embeddings. ... Vintar, Špela; Grčič Simeunovič, Larisa; Martinc, Matej. - : Zenodo, 2020 BASE Show details 16 Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift ... Martinc, Matej; Kralj Novak, Petra; Pollak, Senja. - : Zenodo, 2020 BASE Show details 17 Reproduction, replication, analysis and adaptation of a term alignment approach [<Journal>] Repar, Andraž [Verfasser]; Martinc, Matej [Verfasser]; Pollak, Senja [Verfasser] DNB Subject Category Language Show details 18 Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift ... Martinc, Matej; Novak, Petra Kralj; Pollak, Senja. - : arXiv, 2019 BASE Show details

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