A systematic review of the use of topic models for short text social media analysis [0.03%]
主题模型在短文本社交媒体分析中应用的系统性综述
Caitlin Doogan Poet Laureate,Wray Buntine,Henry Linger
Caitlin Doogan Poet Laureate
Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform w...
Ciyuan Peng,Feng Xia,Mehdi Naseriparsa et al.
Ciyuan Peng et al.
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledg...
The role of artificial intelligence in developing a banking risk index: an application of Adaptive Neural Network-Based Fuzzy Inference System (ANFIS) [0.03%]
人工智能在开发银行风险指数中的作用：自适应神经网络模糊推理系统（ANFIS）的应用
Ibrahim Elsiddig Ahmed,Riyadh Mehdi,Elfadil A Mohamed
Ibrahim Elsiddig Ahmed
Banking risk measurement and management remain one of many challenges for managers and policymakers. This study contributes to the banking literature and practice in two ways by (a) proposing a risk ranking index based on the Mahalanobis Di...
The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era [0.03%]
基于q-水平模糊LOPTCOW-VIKOR模型评估无人机在农业4.0时代精准农业实施中的作用
Fatih Ecer,İlkin Yaran Ögel,Raghunathan Krishankumar et al.
Fatih Ecer et al.
Smart agriculture is gaining a lot of attention recently, owing to technological advancement and promotion of sustainable habits. Unmanned aerial vehicles (UAVs) play a crucial role in smart agriculture by aiding in different phases of agri...
Impact of word embedding models on text analytics in deep learning environment: a review [0.03%]
词嵌入模型对深度学习环境下文本分析影响的综述研究
Deepak Suresh Asudani,Naresh Kumar Nagwani,Pradeep Singh
Deepak Suresh Asudani
The selection of word embedding and deep learning models for better outcomes is vital. Word embeddings are an n-dimensional distributed representation of a text that attempts to capture the meanings of the words. Deep learning models utiliz...
Manuel Méndez,Mercedes G Merayo,Manuel Núñez
Manuel Méndez
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is important to develop forecasting mechanisms that can be used by the authorities, so that they can anticipate measures when high concentrations of cert...
An extensive survey on the use of supervised machine learning techniques in the past two decades for prediction of drug side effects [0.03%]
过去二十年监督机器学习技术预测药物副作用的研究进展综述
Pranab Das,Dilwar Hussain Mazumder
Pranab Das
Approved drugs for sale must be effective and safe, implying that the drug's advantages outweigh its known harmful side effects. Side effects (SE) of drugs are one of the common reasons for drug failure that may halt the whole drug discover...
Yuanhang Zheng,Zeshui Xu,Anran Xiao
Yuanhang Zheng
From the perspective of historical review, the methodology of economics develops from qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of the superiority in learning inherent law and representativ...
Deep learning: survey of environmental and camera impacts on internet of things images [0.03%]
深度学习：环境及摄像头对物联网影像影响的研究综述
Roopdeep Kaur,Gour Karmakar,Feng Xia et al.
Roopdeep Kaur et al.
Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and t...
José Marcio Duarte,Lilian Berton
José Marcio Duarte
A huge amount of data is generated daily leading to big data challenges. One of them is related to text mining, especially text classification. To perform this task we usually need a large set of labeled data that can be expensive, time-con...