Results 21 to 30 of about 2,104,744 (292)
Chinese text classification by combining Chinese-BERTology-wwm and GCN [PDF]
PeerJ Computer Science, 2023 Text classification is an important and classic application in natural language processing (NLP). Recent studies have shown that graph neural networks (GNNs) are effective in tasks with rich structural relationships and serve as effective transductive ...
Xue Xu +3 more
doaj +2 more sources
ESTeR: Combining Word Co-occurrences and Word Associations for Unsupervised Emotion Detection [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020 Accurate detection of emotions in user- generated text was shown to have several applications for e-commerce, public well-being, and disaster management. Currently, the state-of-the-art performance for emotion detection in text is obtained using complex, deep learning models trained on domain-specific, labeled data. In this paper, we propose ESTeR , an
Sujatha Das Gollapalli +2 more
openaire +1 more source
Conditional co-occurrence probability acts like frequency in predicting fixation durations
Journal of Eye Movement Research, 2008 The predictability of an upcoming word has been found to be a useful predictor in eye movement research, but is expensive to collect and subjective in nature.
James K. Y. Ong, Reinhold Kliegl
doaj +1 more source
A Pitman-Yor Process Self-Aggregated Topic Model for Short Texts of Social Media
IEEE Access, 2021 In recent years, with the rapid growth of social media, short texts have been very prevalent on the internet. Due to the limited length of each short text, word co-occurrence information in this type of documents is sparse.
Yue Niu, Hongjie Zhang, Jing Li
doaj +1 more source
Revista Educação Especial, 2011 Purpose: The aim of this study was to analyze the contribution of the words used in language assessment instruments and/or the vocabulary used in Brazil for the development of alternative communication boards.
Andréa Carla Paura, Débora Deliberato
doaj +1 more source
JThe occurrence patterns of important words found in six texts (one historical pamphlet and five renowned academic books) are analyzed using both univariate and multivariate Hawkes processes.
Hiroshi Ogura +3 more
doaj +1 more source
Bibliometric Analysis of Strategic Agility Using Word Co-occurrence Analysis [PDF]
مدیریت بازرگانیObjective Strategic agility, as one of the key concepts in strategic management, has attracted the attention of many researchers and managers. However, the concept remains controversial and is considered non-intuitive and intangible by some scholars ...
Ata Harandi, Alireza Mohebbi
doaj +1 more source
Text Authorship Identified Using the Dynamics of Word Co-Occurrence Networks. [PDF]
PLoS ONE, 2017 Automatic identification of authorship in disputed documents has benefited from complex network theory as this approach does not require human expertise or detailed semantic knowledge. Networks modeling entire books can be used to discriminate texts from
Camilo Akimushkin +2 more
doaj +1 more source
Frequency of occurrence of word sequences [PDF]
The Journal of the Acoustical Society of America, 1981 A problem encountered in speech synthesis using concatenation methods is the unnaturalness and lowered intelligibility which arise from reducing the duration of stored units (diphones, demisyllables, words, etc.). in word-concatenation systems, this problem is most severe in the case of a sequence of function words, where an extreme amount of ...
N. Umeda, D. Kahn
openaire +1 more source
Word Embedding With Zipf’s Context
IEEE Access, 2019 Word embeddings generated by neural language models have achieved great success in many NLP tasks. However, neural language models may be difficult to train and time consuming.
Lizheng Gao +3 more
doaj +1 more source