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Titlebook: Artificial Intelligence and Natural Language; 9th Conference, AINL Andrey Filchenkov,Janne Kauttonen,Lidia Pivovarova Conference proceeding

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期刊全稱(chēng)Artificial Intelligence and Natural Language
期刊簡(jiǎn)稱(chēng)9th Conference, AINL
影響因子2023Andrey Filchenkov,Janne Kauttonen,Lidia Pivovarova
視頻videohttp://file.papertrans.cn/163/162259/162259.mp4
學(xué)科分類(lèi)Communications in Computer and Information Science
圖書(shū)封面Titlebook: Artificial Intelligence and Natural Language; 9th Conference, AINL Andrey Filchenkov,Janne Kauttonen,Lidia Pivovarova Conference proceeding
影響因子?This book constitutes the refereed proceedings of the 9th?Conference on Artificial Intelligence and Natural Language, AINL 2020, held in Helsinki, Finland, in October 2020.?.The 11 revised full papers and 3 short papers were carefully reviewed and selected from 36 submissions. Additionally, the volume presents 1 shared task paper. The volume presents recent research in areas of?of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics.?.
Pindex Conference proceedings 2020
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書(shū)目名稱(chēng)Artificial Intelligence and Natural Language影響因子(影響力)




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Artificial Intelligence and Natural Language978-3-030-59082-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Proze?phasen von lernenden FuE-KooperationenThe task for participants was to train a general-purpose MT system which performs reasonably well on very diverse text domains and styles without additional fine-tuning. 11 teams participated in the competition, some of the submitted models showed reasonably good performance topping at ..
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Encyclopedia of Heroism Studiesand political issues. The lexicon was generated from a database of posts and comments of the top 2,000 LiveJournal bloggers posted during one year (.1.5 million posts and 20 million comments). Following a topic modeling approach, we extracted 85,898 documents that were used to retrieve domain-specif
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Encyclopedia of Heroism Studiesposts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic
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Implikationen der Untersuchung,s, question answering, named entity recognition. Headline generation is a special kind of text summarization task. Models need to have strong natural language understanding that goes beyond the meaning of individual words and sentences and an ability to distinguish essential information to succeed i
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