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North American Chapter of the Association for Computational Linguistics, 2019
Word embeddings are widely used in NLP for a vast range of tasks. It was shown that word embeddings derived from text corpora reflect gender biases in society.
Hila Gonen, Yoav Goldberg
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Word embeddings are widely used in NLP for a vast range of tasks. It was shown that word embeddings derived from text corpora reflect gender biases in society.
Hila Gonen, Yoav Goldberg
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The International Journal of Electrical Engineering & Education, 2020
Sentiment analysis becomes one of the most active research hotspots in the field of natural language processing tasks in recent years. However, the inability to fully and effectively use emotional information is a problem in present deep learning models.
Yong Li +6 more
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Sentiment analysis becomes one of the most active research hotspots in the field of natural language processing tasks in recent years. However, the inability to fully and effectively use emotional information is a problem in present deep learning models.
Yong Li +6 more
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Introduction to Word Embeddings
2021NLP tasks such as document classification, sentiment analysis, clustering, and document summarization require processing and understanding of textual data. Implementation of these tasks depends on how data are being processed and understood by AI systems.
Amit Agrawal, Navin Sabharwal
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2021
The current research on the topic of machine learning and especially the domain of natural language processing has gained much popularity in the modern era. One such framework for attaining NLP tasks is word embedding, which represents data as vectors, i.e., real numbers rather than words of natural language because neural networks do not understand ...
Satvika +2 more
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The current research on the topic of machine learning and especially the domain of natural language processing has gained much popularity in the modern era. One such framework for attaining NLP tasks is word embedding, which represents data as vectors, i.e., real numbers rather than words of natural language because neural networks do not understand ...
Satvika +2 more
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Linguistic Information in Word Embeddings
2018We study the presence of linguistically motivated information in the word embeddings generated with statistical methods. The nominal aspects of uter/neuter, common/proper, and count/mass in Swedish are selected to represent respectively grammatical, semantic, and mixed types of nominal categories within languages.
Basirat, Ali, Tang, Marc
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Word Embeddings for Comment Coherence
2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2019During the evolution of software, it could happen that the information in the comments and in the associated source code are not aligned, so hampering the execution of software evolution and maintenance tasks. This kind of misalignment is known as lack of coherence and it can happen for several reasons, e.g., programmers modify the intent of source ...
Alfonso Cimasa +3 more
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A heterogeneous stacking ensemble based sentiment analysis framework using multiple word embeddings
International Conference on Climate Informatics, 2021Word embedding techniques have been proposed in the literature to analyze and determine the sentiments expressed in various textual documents such as social media posts, online product reviews, and so forth. However, it is difficult to capture the entire
Basant Subba, Simpy Kumari
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Sentiment Analysis with Word Embedding
2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST), 2018The basic task of sentiment analysis is to determine the sentiment polarity (positivity, neutrality or negativity) of a piece text. The traditional bag-of-words models deficiencies affect the accuracy of sentiment classifications. The purpose of this study is to improve the accuracy of the sentiment classification by employing the concept of word ...
L. Felix Aryeh +3 more
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2022
Musical Word Embedding for Music Tagging and Retrieval IEEE Transactions on Audio, Speech and Language Processing (submitted) - SeungHeon Doh, Jongpil Lee, Dasaem Jeong, Juhan NamDEMO: https://seungheondoh.github.io/musical_word_embedding_demo/ Word embedding has become an essential means for text-based information retrieval.
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Musical Word Embedding for Music Tagging and Retrieval IEEE Transactions on Audio, Speech and Language Processing (submitted) - SeungHeon Doh, Jongpil Lee, Dasaem Jeong, Juhan NamDEMO: https://seungheondoh.github.io/musical_word_embedding_demo/ Word embedding has become an essential means for text-based information retrieval.
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Reducing sentiment polarity for demographic attributes in word embeddings using adversarial learning
FAT*, 2020The use of word embedding models in sentiment analysis has gained a lot of traction in the Natural Language Processing (NLP) community. However, many inherently neutral word vectors describing demographic identity have unintended implicit correlations ...
Chris Sweeney, M. Najafian
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