Results 71 to 80 of about 63,655 (233)

Research on Corporate Social Responsibility in Public Relations: A Hybrid Review Through Topic Modeling Analysis and Way Forward

Business Ethics, the Environment &Responsibility, EarlyView.
ABSTRACT Despite the growing significance of corporate social responsibility (CSR) in corporate public relations (PR) strategies, there has been a paucity of comprehensive reviews of the extant CSR literature within the PR discipline. The aim of this study is to investigate the relationship between the concept of CSR and the discipline of PR through a ...
Fatih Çelik, Mehmet Ali Koseoglu, Blend Ibrahim   +2 more
wiley   +1 more source

Interpreting atomization of agricultural spray image patterns using latent Dirichlet allocation techniques

Artificial Intelligence in Agriculture, 2020
Breakup patterns of agricultural formulations are explored using unsupervised learning techniques to elucidate the mechanics of atomization for oil-in-water formulations.
Hongfei Li, Steven Cryer, John Raymond, Lipi Acharya   +3 more
doaj  

Modeling Word Relatedness in Latent Dirichlet Allocation [PDF]

arXiv, 2014
Standard LDA model suffers the problem that the topic assignment of each word is independent and word correlation hence is neglected. To address this problem, in this paper, we propose a model called Word Related Latent Dirichlet Allocation (WR-LDA) by incorporating word correlation into LDA topic models.
arxiv  

Scoping review on natural language processing applications in counselling and psychotherapy

British Journal of Psychology, EarlyView.
Abstract Recent years have witnessed some rapid and tremendous progress in natural language processing (NLP) techniques that are used to analyse text data. This study endeavours to offer an up‐to‐date review of NLP applications by examining their use in counselling and psychotherapy from 1990 to 2021.
Maria Laricheva, Yan Liu, Edward Shi, Amery Wu   +3 more
wiley   +1 more source

Learning from LDA using Deep Neural Networks [PDF]

arXiv, 2015
Latent Dirichlet Allocation (LDA) is a three-level hierarchical Bayesian model for topic inference. In spite of its great success, inferring the latent topic distribution with LDA is time-consuming. Motivated by the transfer learning approach proposed by~\newcite{hinton2015distilling}, we present a novel method that uses LDA to supervise the training ...
arxiv  

EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation [PDF]

arXiv, 2020
As one of the most powerful topic models, Latent Dirichlet Allocation (LDA) has been used in a vast range of tasks, including document understanding, information retrieval and peer-reviewer assignment. Despite its tremendous popularity, the security of LDA has rarely been studied.
arxiv  

Leveraging Artificial Intelligence to Inform Care Coordination by Identifying and Intervening in Patients' Unmet Social Needs: A Scoping Review

Journal of Advanced Nursing, EarlyView.
ABSTRACT Aim We reviewed how artificial intelligence has been applied to inform care coordination by identifying and/or intervening in patients' unmet social needs. Design Scoping review. Data Sources PubMed, CINAHL, PsycInfo, and Scopus databases were searched for articles published by November 2023. Methods Articles were excluded if they were reviews
Victoria H. Davis, Andrew D. Pinto, Minal R. Patel   +2 more
wiley   +1 more source

The Nexus of Corporate Disclosure and Investors’ Information Needs: An Analysis Using Topic Modeling

Journal of Business Finance &Accounting, EarlyView.
ABSTRACT This paper identifies thematic topics that individual and institutional investors discuss about firms and investigates whether, and for which type of investors, companies incorporate in their disclosures the investors’ information needs. We use latent Dirichlet allocation to identify firm‐related topics discussed by investors and compare these
Daphne Lui, Andreea Moraru‐Arfire, Cong Tao   +2 more
wiley   +1 more source

Scene Semantic Recognition Based on Probability Topic Model

Information, 2018
In recent years, scene semantic recognition has become the most exciting and fastest growing research topic. Lots of scene semantic analysis methods thus have been proposed for better scene content interpretation.
Jiangfan Feng, Amin Fu
doaj   +1 more source

A 'Gibbs-Newton' Technique for Enhanced Inference of Multivariate Polya Parameters and Topic Models [PDF]

arXiv, 2015
Hyper-parameters play a major role in the learning and inference process of latent Dirichlet allocation (LDA). In order to begin the LDA latent variables learning process, these hyper-parameters values need to be pre-determined. We propose an extension for LDA that we call 'Latent Dirichlet allocation Gibbs Newton' (LDA-GN), which places non ...
arxiv