Results 31 to 40 of about 145 (133)
Cross-lingual Lexical Sememe Prediction [PDF]
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018 Sememes are defined as the minimum semantic units of human languages. As important knowledge sources, sememe-based linguistic knowledge bases have been widely used in many NLP tasks. However, most languages still do not have sememe-based linguistic knowledge bases.
Fanchao Qi +5 more
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Security and Communication Networks, Volume 2021, Issue 1, 2021., 2021 In order to obtain the scene information of the ordinary football game more comprehensively, an algorithm of collecting the scene information of the ordinary football game based on web documents is proposed. The commonly used T‐graph web crawler model is used to collect the sample nodes of a specific topic in the football game scene information and ...
Bin Li, Ting Zhang, Chi-Hua Chen
wiley +1 more source
Improved Word Representation Learning with Sememes [PDF]
Proceedings of the 55th Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers), 2017 Sememes are minimum semantic units of word meanings, and the meaning of each word sense is typically composed by several sememes. Since sememes are not explicit for each word, people manually annotate word sememes and form linguistic common-sense knowledge bases.
Yilin Niu +3 more
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Digital Mining Algorithm of English Translation Course Information Based on Digital Twin Technology
Wireless Communications and Mobile Computing, Volume 2021, Issue 1, 2021., 2021 Cross‐language communication puts forward higher requirements for information mining in English translation course. Aiming at the problem that the frequent patterns in the current digital mining algorithms produce a large number of patterns and rules, with a long execution time, this paper proposes a digital mining algorithm for English translation ...
Juan Yang, Vinoth Babu Kumaravelu
wiley +1 more source
Hyponymic and graduonymic relations of forestry terms in German and Uzbek languages [PDF]
E3S Web of Conferences, 2023 The article deals with the hyponymic analysis of forestry terms in German and Uzbek languages, and this is one of the main points of the scientific work.
Tilovova Gavhar
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Unsupervised Neural Aspect Extraction with Sememes [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Aspect extraction relies on identifying aspects by discovering coherence among words, which is challenging when word meanings are diversified and processing on short texts. To enhance the performance on aspect extraction, leveraging lexical semantic resources is a possible solution to such challenge.
Ling Luo +6 more
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Automatic Construction of Sememe Knowledge Bases via Dictionaries [PDF]
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 A sememe is defined as the minimum semantic unit in linguistics. Sememe knowledge bases (SKBs), which comprise words annotated with sememes, enable sememes to be applied to natural language processing. So far a large body of research has showcased the unique advantages and effectiveness of SKBs in various tasks.
Fanchao Qi +5 more
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Towards Building a Multilingual Sememe Knowledge Base: Predicting Sememes for BabelNet Synsets
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 A sememe is defined as the minimum semantic unit of human languages. Sememe knowledge bases (KBs), which contain words annotated with sememes, have been successfully applied to many NLP tasks. However, existing sememe KBs are built on only a few languages, which hinders their widespread utilization.
Fanchao Qi +4 more
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Modeling Semantic Compositionality with Sememe Knowledge [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 Semantic compositionality (SC) refers to the phenomenon that the meaning of a complex linguistic unit can be composed of the meanings of its constituents. Most related works focus on using complicated compositionality functions to model SC while few works consider external knowledge in models.
Fanchao Qi +6 more
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Complex & Intelligent Systems, 2023 Document-level relation extraction is a challenging task in information extraction, as it involves identifying semantic relations between entities that are dispersed throughout a document.
Qihui Zhao, Tianhan Gao, Nan Guo
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