Results 151 to 160 of about 17,519 (197)

Revolutionizing market surveillance: customer relationship management with machine learning. [PDF]

PeerJ Comput Sci
Shi X, Zhang Y, Yu M, Zhang L.
europepmc   +1 more source

Synthesizing Explainability Across Multiple ML Models for Structured Data. [PDF]

Algorithms
Veledar E, Zhou L, Veledar O, Gardener H, Gutierrez CM, Romano JG, Rundek T.   +6 more
europepmc   +1 more source

Regulation to function: A computational approach to specialized metabolism. [PDF]

PLoS Biol
Nodwell JR.
europepmc   +1 more source

A flow pattern recognition method for gas-liquid two-phase flow based on dilated convolutional channel attention mechanism. [PDF]

PLoS One
Liu J, Wu Y.
europepmc   +1 more source

The role of AI-enhanced fast delivery services in strengthening customer retention and loyalty in competitive markets. [PDF]

Front Artif Intell
Kasoju A, Vishwakarma T, Kasoju A.
europepmc   +1 more source

Churn Prediction in Digital Marketing

, 2019
openaire   +2 more sources

Cell Complexity Impact on Railway 5G Performance: Measurements Along Tallinn-Tartu Corridor. [PDF]

Sensors (Basel)
Pilvik R, Jairus T, Sadam A, Kõrbe Kaare K.   +3 more
europepmc   +1 more source

A robust pressure drop prediction model in vertical multiphase flow: a machine learning approach. [PDF]

Sci Rep
Alakbari FS, Ayoub MA, Awad MA, Ganat T, Mohyaldinn ME, Mahmood SM.   +5 more
europepmc   +1 more source

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Employee churn prediction

Expert Systems with Applications, 2011
Customer churn is a notorious problem for most industries, as loss of a customer affects revenues and brand image and acquiring new customers is difficult. Reliable predictive models for customer churn could be useful in devising customer retention plans.
V. Vijaya Saradhi, Girish Keshav Palshikar   +1 more
openaire   +3 more sources

Customer churn prediction in telecommunications

Expert Systems with Applications, 2012
This paper presents a new set of features for land-line customer churn prediction, including 2 six-month Henley segmentation, precise 4-month call details, line information, bill and payment information, account information, demographic profiles, service orders, complain information, etc.
Bingquan Huang, Mohand Tahar Kechadi, Brian Buckley   +2 more
openaire   +3 more sources