Citation prediction using diverse features
Web2 days ago · Quantification of how different environmental cues affect protein allocation can provide important insights for understanding cell physiology. While absolute quantification of proteins can be obtained by resource-intensive mass-spectrometry-based technologies, prediction of protein abundances offers another way to obtain insights into protein … http://www.cond.org/citepredict.pdf
Citation prediction using diverse features
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WebOct 13, 2024 · To further improve prediction accuracy by increasing feature diversity, different features were selected in different degradation stages using the method described in Sec. 3.3. The hypothesis is that feature selection for ensembles is not necessarily the same as feature selection for a single base learner. WebSection 2 we first define a series of features which correlate with citation counts. We then formulate citation count prediction as a learning problem and introduce several …
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WebNov 9, 2024 · In this study, we aim to develop novel algorithms to provide accurate and timely predictions of fundraising performance, to better inform fundraisers. In particular, we propose a new approach to combine time-series features and time-invariant features in the deep learning model, to process diverse sources of input data. WebAug 1, 2024 · We use a multilayer BP neural network to predict the citations of academic papers. First, we select 49,834 papers in the library, information and documentation field published from 2000 to 2013 and indexed in the Chinese Social Science Citation Index database (hereafter CSSCI) (Su, Deng, & Shen, 2014). Second, we extract six article …
WebMay 1, 2024 · Conclusion. In this paper, we proposed a novel method for citation count prediction, which is based on artificial neural networks. We employed modern deep learning techniques (such as RNNs and sequence-to-sequence model) in order to learn a prediction method based on the sequence pattern of the citations from early years of …
WebFeb 21, 2024 · The precise estimate of remaining useful life (RUL) is vital for the prognostic analysis and predictive maintenance that can significantly reduce failure rate and maintenance costs. The degradation-related features extracted from the sensor streaming data with neural networks can dramatically improve the accuracy of the RUL prediction. … fix vape cartridge that won\\u0027t hitWebAug 10, 2024 · In addition, by analyzing factors that drive citation growth, we propose a multi-feature model for impact prediction. Experimental results demonstrate that the … fix vape cartridge that won\u0027t hitWebApr 10, 2024 · Results Here, we trained a transformer neural network model on molecular dynamics data for >50,000 peptides that is able to accurately predict the (relative) membrane-binding free energy for any given amino acid sequence.Using this information, our physics-informed model is able to classify a peptide’s membrane-associative activity … fix vaping garchingWebMay 1, 2024 · Conclusion. In this paper, we proposed a novel method for citation count prediction, which is based on artificial neural networks. We employed modern deep … cannizzaro\u0027s reaction is not given byWebNew Citation Alert added! ... The proposed technique resulted in a high classification AUC of 91.2% and 95.7% for 6-month- and 1-year-ahead AD prediction, respectively, using multimodal markers. ... “ A novel conversion prediction method of MCI to AD based on longitudinal dynamic morphological features using ADNI structural MRIs,” Journal ... fix valorant graphics driver crashedWebLink Prediction is the problem of predicting the existence of a relationship between nodes in a graph. In this guide, we will predict co-authorships using the link prediction machine learning model that was introduced in version 1.5.0 of the Graph Data Science Library. For background reading about link prediction, see the Link Prediction ... fix vanity top cornerhttp://rdkit.org/docs/Overview.html cann koncerty