An Integrated Word Embedding-Based Dual-Task Learning Method for Sentiment Analysis
Sign Up to like & getrecommendations! Published in 2019 at "Arabian Journal for Science and Engineering"
DOI: 10.1007/s13369-019-04241-7
Abstract: Sentiment analysis aimed to automate the task of discriminating the sentiment tendency of a textual review, which expresses a simple sentiment as positive, negative, or neutral. In general, the basic sentiment analysis solution used for… read more here.
Keywords: word embedding; sentiment analysis; task; sentiment ... See more keywords
Detecting negation and scope in Chinese clinical notes using character and word embedding
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DOI: 10.1016/j.cmpb.2016.11.009
Abstract: BACKGROUND AND OBJECTIVES Researchers have developed effective methods to index free-text clinical notes into structured database, in which negation detection is a critical but challenging step. In Chinese clinical records, negation detection is particularly challenging… read more here.
Keywords: clinical notes; detection; word; negation ... See more keywords
Clustering analysis of process alarms using word embedding
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Process Control"
DOI: 10.1016/j.jprocont.2019.08.011
Abstract: Abstract Industrial alarm systems have evolved significantly over the recent years both in terms of the number of observed alarms and the complexity of their presentation and management, seriously challenging the decision making abilities of… read more here.
Keywords: alarm; analysis; process; word embedding ... See more keywords
Re-LSTM: A long short-term memory network text similarity algorithm based on weighted word embedding
Sign Up to like & getrecommendations! Published in 2022 at "Connection Science"
DOI: 10.1080/09540091.2022.2140122
Abstract: Natural language processing text similarity calculation is a crucial and difficult problem that enables matching between various messages. This approach is the foundation of many applications. The word representation features and contextual relationships extracted by… read more here.
Keywords: lstm; weighted word; word embedding; word ... See more keywords
Perspective changes in human listeners are aligned with the contextual transformation of the word embedding space.
Sign Up to like & getrecommendations! Published in 2023 at "Cerebral cortex"
DOI: 10.1093/cercor/bhad082
Abstract: Word embedding representations have been shown to be effective in predicting human neural responses to lingual stimuli. While these representations are sensitive to the textual context, they lack the extratextual sources of context such as… read more here.
Keywords: human listeners; perspective changes; space; word embedding ... See more keywords
A Word-Embedding-Based Steganalysis Method for Linguistic Steganography via Synonym Substitution
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DOI: 10.1109/access.2018.2878273
Abstract: The development of steganography technology threatens the security of privacy information in smart campus. To prevent privacy disclosure, a linguistic steganalysis method based on word embedding is proposed to detect the privacy information hidden in… read more here.
Keywords: steganalysis; word; steganography; steganalysis method ... See more keywords
Skip-Gram-KR: Korean Word Embedding for Semantic Clustering
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2905252
Abstract: Deep learning algorithms are used in various applications for pattern recognition, natural language processing, speech recognition, and so on. Recently, neural network-based natural language processing techniques use fixed length word embedding. Word embedding is a… read more here.
Keywords: skip gram; word; korean word; gram korean ... See more keywords
Few-Shot Transfer Learning for Text Classification With Lightweight Word Embedding Based Models
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DOI: 10.1109/access.2019.2911850
Abstract: Many deep learning architectures have been employed to model the semantic compositionality for text sequences, requiring a huge amount of supervised data for parameters training, making it unfeasible in situations where numerous annotated samples are… read more here.
Keywords: shot transfer; based models; embedding based; transfer learning ... See more keywords
Impact of Stemming and Word Embedding on Deep Learning-Based Arabic Text Categorization
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DOI: 10.1109/access.2020.3009217
Abstract: Document classification is a classical problem in information retrieval, and plays an important role in a variety of applications. Automatic document classification can be defined as content-based assignment of one or more predefined categories to… read more here.
Keywords: learning based; word; word embedding; classification ... See more keywords
Job forecasting based on the patent information: A word embedding-based approach
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DOI: 10.1109/access.2022.3141910
Abstract: The rapid change in technology makes it challenging to forecast the future of jobs. Previous studies have analyzed economics and employment data or employed expert-based methods to forecast the future of jobs, but these approaches… read more here.
Keywords: information; job; patent; word embedding ... See more keywords
Comparison of Neural Language Modeling Pipelines for Outcome Prediction From Unstructured Medical Text Notes
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DOI: 10.1109/access.2022.3148279
Abstract: Machine learning techniques and algorithm-based approaches are becoming more and more vital to support clinical decision-making. In the medical area, natural language processing (NLP) techniques have shown the ability to extract useful information from electronic… read more here.
Keywords: outcome prediction; word embedding; language; text ... See more keywords