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Titlebook: Artificial Intelligence and Natural Language; 6th Conference, AINL Andrey Filchenkov,Lidia Pivovarova,Jan ?i?ka Conference proceedings 2018

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期刊全稱Artificial Intelligence and Natural Language
期刊簡稱6th Conference, AINL
影響因子2023Andrey Filchenkov,Lidia Pivovarova,Jan ?i?ka
視頻videohttp://file.papertrans.cn/163/162256/162256.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Artificial Intelligence and Natural Language; 6th Conference, AINL Andrey Filchenkov,Lidia Pivovarova,Jan ?i?ka Conference proceedings 2018
影響因子.This book constitutes the refereed proceedings of the 6.th. Conference on Artificial Intelligence and Natural Language, AINL 2017, held in St. Petersburg, Russia, in September 2017.. .The 13 revised full papers, 4 revised short papers papers were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on social interaction analysis, speech processing, information extraction, Web-scale data processing, computation morphology and word embedding, machine learning. The volume also contains 6 papers participating in the Russian paraphrase detection shared task..
Pindex Conference proceedings 2018
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Corpus of Syntactic Co-Occurrences: A Delayed Promisen the Russian language. The paper includes an overview of the corpora collected for CoSyCo creation and the amount of collected combinations. In the paper, we also provide a short evaluation of the gathered information.
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Tanmay,Lakshmi,Vijay Kumar Soni,Adarsh Kumaranging from psychology to marketing, but there are very few works of this kind on Russian-speaking samples. We use Latent Dirichlet Allocation on the Facebook status updates to extract interpretable features that we then use to identify Facebook users with certain negative psychological traits (the
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Lecture Notes in Electrical Engineeringeyword-based answer retrieval heuristic. We test two neural network approaches to the near-duplicate question detection task as a first step towards a better answer retrieval method. A convolutional neural network architecture gives promising results on this difficult task.
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