Results 91 to 100 of about 511,753 (356)
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
Applied Stochastic Models in Business and Industry, EarlyView.ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco +4 more
wiley +1 more source
Features requirement elicitation process for designing a chatbot application
IET Networks, EarlyView., 2022 This article seeks to assist the chatbot community by outlining the characteristics that a chatbot needs to possess and explaining how to create a chatbot for a bank. In order to determine which capabilities are most crucial to ending users, a study of a small sample of chatbot users was conducted.
Nurul Muizzah Johari +4 more
wiley +1 more source
Generative Deep Learning for Advanced Battery Materials
Batteries &Supercaps, EarlyView.This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal +3 more
wiley +1 more source
Biological Reviews, EarlyView.ABSTRACT Basal and standard metabolic rate (BMR and SMR) are cornerstones of physiological ecology and are assumed to be relatively fixed intrinsic properties of organisms that represent the minimum energy required to sustain life. However, this assumption is conceptually flawed. Many core maintenance processes underlying SMR are temporally partitioned
Helena Norman +4 more
wiley +1 more source
Time series segmentation with shifting means hidden markov models [PDF]
Nonlinear Processes in Geophysics, 2006 We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means ...
Ath. Kehagias, V. Fortin
doaj
Bayesian regularization of hidden Markov models with an application to bioinformatics [PDF]
, 2000 This paper discusses a Bayesian approach to regularizing hidden Markov models and demonstrates an application of this scheme to ...
Husmeier, D.
core
Hidden Markov Models for Time Series – An Introduction Using R
, 2011 The book by Walter Zucchini and Iain MacDonald is an introduction to the theory and computation of HMM (Part I) and their applications to a wide variety of time series data (Part II). Chapters 1–7 of Part I introduce the main ideas using a single running
Juana Sanchez, W. Zucchini, I. MacDonald
semanticscholar +1 more source
Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series
AAAI Conference on Artificial Intelligence, 2015 Faced with the problem of characterizing systematic changes in multivariate time series in an unsupervised manner, we derive and test two methods of regularizing hidden Markov models for this task.
George D. Montañez +2 more
semanticscholar +1 more source
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Introducing Busy Customer Portfolio Using Hidden Markov Model [PDF]
Iranian Journal of Management Studies, 2011 Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures.
Sepideh Emam, Abdollah Aaghaie
doaj