Results 131 to 140 of about 41,060,851 (256)
A text mining approach for automatic taxonomy generation and text categorisation
, 2007 The research presented in this paper investigates the use of a text mining approach for automatic taxonomy generation and text categorisation for the content management system of Alergoclínica, a private clinic of Dermatology and Allergies in São Paulo ...
Dotsika, F., Shearer, J., Pais, N.
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Holographic Mapping of Orbital Angular Momentum using a Terahertz Diffractive Optical Neural Network
Advanced Intelligent Discovery, EarlyView.A compact six‐layer diffractive optical neural network enables direct recognition and spatial mapping of terahertz (THz) orbital angular momentum (OAM) beams. Fabricated by 3D printing, the system distinguishes nine OAM modes and their superpositions with high fidelity, good efficiency, and low crosstalk, offering a scalable solution for THz ...
Wei Jia +3 more
wiley +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Text Mining in Python through the HTRC Feature Reader
The Programming Historian, 2016 We introduce a toolkit for working with the 13.6 million volume Extracted Features Dataset from the HathiTrust Research Center. You will learn how to peer at the words and trends of any book in the collection, while developing broadly useful Python data ...
Peter Organisciak, Boris Capitanu
doaj
A Text Mining-Based Anomaly aZDetection Model in Network Security [PDF]
, 2014 Anomaly detection systems are extensively used security tools to detect cyber-threats and attack activities in computer systems and networks. In this paper, we present Text Mining-Based Anomaly Detection (TMAD) model.
Mohsen Kakavand
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Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Development of a text mining approach to disease network discovery [PDF]
, 2019 Scientific literature is one of the major sources of knowledge for systems biology, in the form of papers, patents and other types of written reports. Text mining methods aim at automatically extracting relevant information from the literature.
Lamurias, Andre
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Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
This paper explores the challenges of processing the increasing volume of natural language text, which often surpasses traditional methods' real-time processing abilities.
Postiglione, Alberto
core +1 more source
Annotation of conceptual co-reference and text Mining the Qur'an [PDF]
, 2012 This research contributes to the area of corpus annotation and text mining by developing novel domain specific language resources. Most practical text mining applications restrict their domain.
Muhammad, Abdul Baquee
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