Evolution of semantic similarity—a survey
Estimating the semantic similarity between text data is one of the challenging and open
research problems in the field of Natural Language Processing (NLP). The versatility of …
research problems in the field of Natural Language Processing (NLP). The versatility of …
A survey on aspect-based sentiment classification
G Brauwers, F Frasincar - ACM Computing Surveys, 2022 - dl.acm.org
With the constantly growing number of reviews and other sentiment-bearing texts on the
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …
WiC: the word-in-context dataset for evaluating context-sensitive meaning representations
By design, word embeddings are unable to model the dynamic nature of words' semantics,
ie, the property of words to correspond to potentially different meanings. To address this …
ie, the property of words to correspond to potentially different meanings. To address this …
Vector-space models of semantic representation from a cognitive perspective: A discussion of common misconceptions
Models that represent meaning as high-dimensional numerical vectors—such as latent
semantic analysis (LSA), hyperspace analogue to language (HAL), bound encoding of the …
semantic analysis (LSA), hyperspace analogue to language (HAL), bound encoding of the …
Distributional semantics and linguistic theory
G Boleda - Annual Review of Linguistics, 2020 - annualreviews.org
Distributional semantics provides multidimensional, graded, empirically induced word
representations that successfully capture many aspects of meaning in natural languages, as …
representations that successfully capture many aspects of meaning in natural languages, as …
Does BERT make any sense? Interpretable word sense disambiguation with contextualized embeddings
Contextualized word embeddings (CWE) such as provided by ELMo (Peters et al., 2018),
Flair NLP (Akbik et al., 2018), or BERT (Devlin et al., 2019) are a major recent innovation in …
Flair NLP (Akbik et al., 2018), or BERT (Devlin et al., 2019) are a major recent innovation in …
Text mining approaches for dealing with the rapidly expanding literature on COVID-19
More than 50 000 papers have been published about COVID-19 since the beginning of
2020 and several hundred new papers continue to be published every day. This incredible …
2020 and several hundred new papers continue to be published every day. This incredible …
Using sequences of life-events to predict human lives
Here we represent human lives in a way that shares structural similarity to language, and we
exploit this similarity to adapt natural language processing techniques to examine the …
exploit this similarity to adapt natural language processing techniques to examine the …
Identifying fake news on social networks based on natural language processing: trends and challenges
The epidemic spread of fake news is a side effect of the expansion of social networks to
circulate news, in contrast to traditional mass media such as newspapers, magazines, radio …
circulate news, in contrast to traditional mass media such as newspapers, magazines, radio …
A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …