Results 71 to 80 of about 13,159 (226)

Instruction‐Tuned Large Language Models for Review Helpfulness Prediction: An Efficient Fine‐Tuning Framework for E‐Commerce Review Understanding

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT With the exponential growth of online reviews on e‐commerce platforms, efficiently identifying helpful reviews has become increasingly critical for supporting consumer decision‐making and mitigating information overload. The task of Review Helpfulness Prediction (RHP) aims to address this challenge by automatically filtering high‐quality and ...
Xinzhe Li, Qinglong Li, Jaekyeong Kim
wiley   +1 more source

An ELECTRE-Based Multiple Criteria Decision Making Method for Supplier Selection Using Dempster-Shafer Theory

IEEE Access, 2019
The selection of the optimal supply is an open and crucial issue in supply chain management (SCM), which can be considered as a multi-criteria decision-making (MCDM) problem where the expression and processing of uncertain information could be involved ...
Liguo Fei, Jun Xia, Yuqiang Feng, Luning Liu   +3 more
semanticscholar   +1 more source

Interval-Valued Uncertainty Based on Entropy and Dempster–Shafer Theory

Journal of Statistical Theory and Applications (JSTA), 2018
This paper presents a new structure as a simple method at two uncertainties (i.e., aleatory and epistemic) that result from variabilities inherent in nature and a lack of knowledge.
F. Khalaj, E. Pasha, R. Tavakkoli-Moghaddam, M. Khalaj   +3 more
doaj   +1 more source

Predictive processing's flirt with transcendental idealism

Noûs, Volume 60, Issue 1, Page 87-109, March 2026.
Abstract The popular predictive processing (PP) framework posits prediction error minimization (PEM) as the sole mechanism in the brain that can account for all mental phenomena, including consciousness. I first highlight three ambitions associated with major presentations of PP: (1) Completeness (PP aims for a comprehensive account of mental phenomena)
Tobias Schlicht
wiley   +1 more source

Paradox Elimination in Dempster–Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion

Sensors, 2019
Multi-sensor data fusion technology in an important tool in building decision-making applications. Modified Dempster−Shafer (DS) evidence theory can handle conflicting sensor inputs and can be applied without any prior information.
Md Nazmuzzaman Khan, Sohel Anwar
doaj   +1 more source

Features of the application of the dumpster-shafer theory when adopting management decisions in construction operations [PDF]

E3S Web of Conferences, 2019
The article discusses the features of the application of the Dempster-Shafer theory in the management and planning of construction operations. An example of expert evaluation is given, the most possible reasons for the delay of construction and ...
Pogodin Denis, Kuzmin Konstantin, Shesterikov Yuri   +2 more
doaj   +1 more source

Applications of the Dempster-Shafer theory of evidence for simulation [PDF]

Proceedings of the 18th conference on Winter simulation - WSC '86, 1986
The Dempster-Shafer theory of belief functions shows promise as a means of incorporating incompleteness of evidence into simulation models. The key feature of the Dempster-Shafer theory is that precision in inputs is required only to a degree justified by available evidence.
Kathryn B. Laskey, Marvin S. Cohen
openaire   +1 more source

Omni Geometry Representation Learning Versus Large Language Models for Geospatial Entity Resolution

Transactions in GIS, Volume 30, Issue 1, February 2026.
ABSTRACT The development, integration, and maintenance of geospatial databases rely heavily on efficient and accurate matching procedures of Geospatial Entity Resolution (ER). While resolution of points‐of‐interest (POIs) has been widely addressed, resolution of entities with diverse geometries has been largely overlooked.
Kalana Wijegunarathna, Kristin Stock, Christopher B. Jones   +2 more
wiley   +1 more source

Rolling Bearing Fault Prediction Method Based on QPSO-BP Neural Network and Dempster–Shafer Evidence Theory

Energies, 2020
To effectively predict the rolling bearing fault under different working conditions, a rolling bearing fault prediction method based on quantum particle swarm optimization (QPSO) backpropagation (BP) neural network and Dempster−Shafer evidence ...
Lanjun Wan, Hongyang Li, Yiwei Chen, Changyun Li   +3 more
doaj   +1 more source

A Mini Review on Evolution of High‐Entropy Alloy Design: From Experimental Approaches to Machine Learning Integration

Rare Metals, Volume 45, Issue 1, January 2026.
ABSTRACT High‐entropy alloys (HEAs) have emerged as a transformative class of materials distinguished by their complex chemical compositions, unique microstructures, and remarkable mechanical and functional properties. Traditionally, the discovery and optimization of HEAs have relied on conventional methods, including trial‐and‐error experimentation ...
Chrispin Ouko Zamzu, Zhe Jia, Baolong Shen   +2 more
wiley   +1 more source