Retrieval-augmented generation for natural language processing: A survey
Large language models (LLMs) have demonstrated great success in various fields,
benefiting from their huge amount of parameters that store knowledge. However, LLMs still …
benefiting from their huge amount of parameters that store knowledge. However, LLMs still …
[HTML][HTML] The clean energy claims of BP, Chevron, ExxonMobil and Shell: A mismatch between discourse, actions and investments
M Li, G Trencher, J Asuka - PloS one, 2022 - journals.plos.org
The energy products of oil and gas majors have contributed significantly to global
greenhouse gas emissions (GHG) and planetary warming over the past century …
greenhouse gas emissions (GHG) and planetary warming over the past century …
COVID-19 sensing: negative sentiment analysis on social media in China via BERT model
Coronavirus disease 2019 (COVID-19) poses massive challenges for the world. Public
sentiment analysis during the outbreak provides insightful information in making appropriate …
sentiment analysis during the outbreak provides insightful information in making appropriate …
Owl2vec*: Embedding of owl ontologies
Semantic embedding of knowledge graphs has been widely studied and used for prediction
and statistical analysis tasks across various domains such as Natural Language Processing …
and statistical analysis tasks across various domains such as Natural Language Processing …
Special issue on feature engineering editorial
In order to improve the performance of any machine learning model, it is important to focus
more on the data itself instead of continuously developing new algorithms. This is exactly the …
more on the data itself instead of continuously developing new algorithms. This is exactly the …
Deep feature synthesis: Towards automating data science endeavors
JM Kanter, K Veeramachaneni - 2015 IEEE international …, 2015 - ieeexplore.ieee.org
In this paper, we develop the Data Science Machine, which is able to derive predictive
models from raw data automatically. To achieve this automation, we first propose and …
models from raw data automatically. To achieve this automation, we first propose and …
Remote sensing of riparian ecosystems
Riparian zones are dynamic ecosystems that form at the interface between the aquatic and
terrestrial components of a landscape. They are shaped by complex interactions between …
terrestrial components of a landscape. They are shaped by complex interactions between …
[HTML][HTML] Sentiment classification of Roman-Urdu opinions using Naïve Bayesian, Decision Tree and KNN classification techniques
Sentiment mining is a field of text mining to determine the attitude of people about a
particular product, topic, politician in newsgroup posts, review sites, comments on facebook …
particular product, topic, politician in newsgroup posts, review sites, comments on facebook …
Workplace flexibility, work hours, and work-life conflict: finding an extra day or two.
This study explores the influence of workplace flexibility on work-life conflict for a global
sample of workers from four groups of countries. Data are from the 2007 International …
sample of workers from four groups of countries. Data are from the 2007 International …
[图书][B] Introduction to machine learning with applications in information security
M Stamp - 2022 - taylorfrancis.com
Introduction to Machine Learning with Applications in Information Security, Second Edition
provides a classroom-tested introduction to a wide variety of machine learning and deep …
provides a classroom-tested introduction to a wide variety of machine learning and deep …