Results 51 to 60 of about 1,836 (199)
A Study of the Chinese spam Classification with Doc2vec and CNN
IOP Conference Series: Materials Science and Engineering, 2019 Abstract Convolution neural network is a kind of neural network, which has been proved to be very effective in image recognition and classification. In recent years, convolution neural networks have gradually shifted to the field of natural language processing and become one of the research hotspots.
Hechen Gong, Fucheng You, Shaomei Wang
openaire +1 more source
Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT This study aims at shedding light on the vast landscape of natural language processing (NLP) tasks used when analyzing sustainability reports or sustainability within integrated annual reports. A systematic literature review is carried out, identifying 160 studies of relevance.
Hannes Cordes
wiley +1 more source
Doc2vec order of performance in single hidden layer for ANN, LSTM and ELM.
, 2019 Doc2vec order of performance in single hidden layer for ANN, LSTM and ELM.
Sabih Ahmad Khan (7853771) +1 more
core +1 more source
An Empirical Study on the Evaluation of Graph‐Based Strategies for Intelligent Modeling Assistants
Software: Practice and Experience, EarlyView.ABSTRACT Context In the context of model‐driven engineering, the proliferation of intelligent modeling assistants (IMAs) has pushed the boundaries of automation, providing modelers with relevant recommendations based on incomplete modeling artifacts as primary input.
Ilirian Ibrahimi +3 more
wiley +1 more source
A Link Prediction Strategy for Personalized Tweet Recommendation through Doc2Vec Approach [PDF]
, 2017 Nowadays with growth of using Internet as a principle way of communication, likes different social medias channels (Twitter, Facebook, etc.) and also access to huge amount of information like News, there appear a main research subject to help users to ...
Mojtaba Zahedi Amiri +3 more
core +1 more source
Study on the Technology Trend Screening Framework Using Unsupervised Learning
Applied Sciences, 2022 Outliers that deviate from a normal distribution are typically removed during the analysis process. However, the patterns of outliers are recognized as important information in the outlier detection method.
Junseok Lee, Sangsung Park, Juhyun Lee
doaj +1 more source
Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Graph contrastive learning (GCL) relies on acquiring high‐quality positive and negative samples to learn the structural semantics of the input graph. Previous approaches typically sampled negative samples from the same training batch or an irrelevant external graph.
Haoran Yang +7 more
wiley +1 more source
IEEE AccessEmail phishing remains a prevalent and sophisticated cyber threat, targeting individuals and organizations by disguising malicious intent in seemingly legitimate communications.
Aqsa Khalid +5 more
doaj +1 more source
Creativity and Innovation Management, Volume 34, Issue 4, Page 991-1012, December 2025.ABSTRACT Traditional techniques for evaluating creative outcomes are typically based on evaluations made by human experts. These methods suffer from challenges such as subjectivity, biases, limited availability, ‘crowding’, and high transaction costs. We propose that large language models (LLMs) can be used to overcome these shortcomings.
Theresa Kranzle, Katelyn Sharratt
wiley +1 more source
Doc2vec order of performance in multiple hidden layers for DNN and LSTM.
, 2019 Doc2vec order of performance in multiple hidden layers for DNN and LSTM.
Sabih Ahmad Khan +3 more
core +1 more source