A systematic literature review on word embeddings
This article presents a systematic literature review on word embeddings within the field of
natural language processing and text processing. A search and classification of 140 articles …
natural language processing and text processing. A search and classification of 140 articles …
Incorporating syntactic and semantic information in word embeddings using graph convolutional networks
Word embeddings have been widely adopted across several NLP applications. Most
existing word embedding methods utilize sequential context of a word to learn its …
existing word embedding methods utilize sequential context of a word to learn its …
A systematic literature review of virtual reality locomotion taxonomies
The change of the user's viewpoint in an immersive virtual environment, called locomotion,
is one of the key components in a virtual reality interface. Effects of locomotion, such as …
is one of the key components in a virtual reality interface. Effects of locomotion, such as …
Methods to integrate natural language processing into qualitative research
MD Abram, KT Mancini… - International Journal of …, 2020 - journals.sagepub.com
Background: Qualitative methods analyze contextualized, unstructured data. These methods
are time and cost intensive, often resulting in small sample sizes and yielding findings that …
are time and cost intensive, often resulting in small sample sizes and yielding findings that …
Improvement and optimization of vulnerability detection methods for ethernet smart contracts
Z Yang, W Zhu, M Yu - IEEE Access, 2023 - ieeexplore.ieee.org
Smart contracts based on blockchain are widely used in finance, management, Internet of
Things, healthcare, and other fields. However, with the rapid development of smart contracts …
Things, healthcare, and other fields. However, with the rapid development of smart contracts …
Conceptualized and contextualized gaussian embedding
Word embedding can represent a word as a point vector or a Gaussian distribution in high-
dimensional spaces. Gaussian distribution is innately more expressive than point vector …
dimensional spaces. Gaussian distribution is innately more expressive than point vector …
Analysis of sentiment on movie reviews using word embedding self-attentive LSTM
In the contemporary world, people share their thoughts rapidly in social media. Mining and
extracting knowledge from this information for performing sentiment analysis is a complex …
extracting knowledge from this information for performing sentiment analysis is a complex …
Semglove: Semantic co-occurrences for glove from bert
GloVe learns word embeddings by leveraging statistical information from word co-
occurrence matrices. However, word pairs in the matrices are extracted from a predefined …
occurrence matrices. However, word pairs in the matrices are extracted from a predefined …
A custom word embedding model for clustering of maintenance records
Maintenance records of industrial equipment contain rich descriptive information in free-text
format, such as involved parts, failure mechanisms, operating conditions, etc. Our objective …
format, such as involved parts, failure mechanisms, operating conditions, etc. Our objective …
[HTML][HTML] Semantic similarity on multimodal data: A comprehensive survey with applications
Recently, the revival of the semantic similarity concept has been featured by the rapidly
growing artificial intelligence research fueled by advanced deep learning architectures …
growing artificial intelligence research fueled by advanced deep learning architectures …