Results 21 to 30 of about 1,185,215 (298)
Socialized Word Embeddings [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Word embeddings have attracted a lot of attention. On social media, each user’s language use can be significantly affected by the user’s friends. In this paper, we propose a socialized word embedding algorithm which can consider both user’s personal characteristics of language use and the user’s social relationship on social media.
Ziqian Zeng +3 more
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Cultural Cartography with Word Embeddings [PDF]
Poetics, 2020 Using the frequency of keywords is a classic approach in the formal analysis of text, but has the drawback of glossing over the relationality of word meanings. Word embedding models overcome this problem by constructing a standardized and continuous “meaning-space” where words are assigned a location based on relations of similarity to other words ...
Stoltz, Dustin, Taylor, Marshall
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TWE‐WSD: An effective topical word embedding based word sense disambiguation
CAAI Transactions on Intelligence Technology, 2021 Word embedding has been widely used in word sense disambiguation (WSD) and many other tasks in recent years for it can well represent the semantics of words.
Lianyin Jia +5 more
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Context-word region embedding method.
, 2022 Context-word region embedding method.
Saranya Maneeroj (12506894) +2 more
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Joint Fine-Grained Components Continuously Enhance Chinese Word Embeddings
IEEE Access, 2019 The most common method of word embedding is to learn word vector representations from context information of large-scale text. However, Chinese words usually consist of characters, subcharacters, and strokes, and each part contains rich semantic ...
Chengyang Zhuang +3 more
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How Do Pronouns Affect Word Embedding
Tsinghua Science and Technology, 2017 Word embedding has drawn a lot of attention due to its usefulness in many NLP tasks. So far a handful of neural-network based word embedding algorithms have been proposed without considering the effects of pronouns in the training corpus.
Tonglee Chung +4 more
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Sentence model based subword embeddings for a dialog system
ETRI Journal, 2022 This study focuses on improving a word embedding model to enhance the performance of downstream tasks, such as those of dialog systems. To improve traditional word embedding models, such as skip-gram, it is critical to refine the word features and expand
Euisok Chung +2 more
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Survey of Word Embedding Models Research [PDF]
Jisuanji kexue yu tansuoAs a foundational technology in natural language processing, word embedding models map discrete linguistic symbols into continuous vector representations that computers can process.
WEN Yongqi, YANG Ruopeng, TAO Yu, ZHONG Yihao, HUANG Bo
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Name Entity Recognition for Military Based on Domain Adaptive Embedding [PDF]
Jisuanji kexue, 2022 In order to solve the poor quality problem of domain embedding space caused by inadequate military corpus which makes low accuracy of applying deep neural network model to military named entity recognition,this paper introduces a domain adaptive method ...
LIU Kai, ZHANG Hong-jun, CHEN Fei-qiong
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CoRR, 2019 This work lists and describes the main recent strategies for building fixed-length, dense and distributed representations for words, based on the distributional hypothesis. These representations are now commonly called word embeddings and, in addition to encoding surprisingly good syntactic and semantic information, have been proven useful as extra ...
Felipe Almeida, Geraldo Xexéo
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