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Related papers: Evidence combination for a large number of sources

200 papers

In recent years, many methods have been developed for detecting causal relationships in observational data. Some of them have the potential to tackle large data sets. However, these methods fail to discover a combined cause, i.e. a…

Artificial Intelligence · Computer Science 2015-10-16 Saisai Ma , Jiuyong Li , Lin Liu , Thuc Duy Le

It is explored that available credible evidence fusion schemes suffer from the potential inconsistency because credibility calculation and Dempster's combination rule-based fusion are sequentially performed in an open-loop style. This paper…

Artificial Intelligence · Computer Science 2025-04-08 Chaoxiong Ma , Yan Liang , Huixia Zhang , Hao Sun

Data fusion is the combination of the results of independent searches on a document collection into one single output result set. It has been shown in the past that this can greatly improve retrieval effectiveness over that of the…

Information Retrieval · Computer Science 2014-10-01 David Lillis , Fergus Toolan , Rem Collier , John Dunnion

In this paper, we propose a general method for testing composite hypotheses. Our idea is to use confidence limits to define stopping and decision rules. The requirements of operating characteristic function can be satisfied by adjusting the…

Statistics Theory · Mathematics 2012-02-10 Xinjia Chen

Conjoint analysis is a popular experimental design used to measure multidimensional preferences. Researchers examine how varying a factor of interest, while controlling for other relevant factors, influences decision-making. Currently,…

Methodology · Statistics 2024-11-20 Dae Woong Ham , Kosuke Imai , Lucas Janson

Complex reasoning problems are most clearly and easily specified using logical rules, but require recursive rules with aggregation such as count and sum for practical applications. Unfortunately, the meaning of such rules has been a…

Databases · Computer Science 2023-08-29 Yanhong A. Liu , Scott D. Stoller

Biomedical question answering often requires decisions from retrieved literature whose relevance, quality, and support for candidate answers are uneven. Most retrieval-augmented large language model (LLM) methods feed this literature to the…

Computation and Language · Computer Science 2026-05-19 Chang Zong , Hao Ning , Siliang Tang , Jie Huang , Jian Wan

Besides the classical motivation of fusing evidence from multiple sources, modern inferential procedures based on randomization, resampling, and data splitting often introduce analyst-generated multiplicity, where aggregating outputs across…

Methodology · Statistics 2026-05-29 Leonardo Cella

In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to…

Artificial Intelligence · Computer Science 2013-04-12 Lotfi Zadeh , Anca Ralescu

A framework for consensus modelling is introduced using Kleene's three valued logic as a means to express vagueness in agents' beliefs. Explicitly borderline cases are inherent to propositions involving vague concepts where sentences of a…

Multiagent Systems · Computer Science 2018-01-15 Michael Crosscombe , Jonathan Lawry

Norms represent behavioural aspects that are encouraged by a social group of agents or the majority of agents in a system. Normative systems enable coordinating synthesised norms of heterogeneous agents in complex multi-agent systems…

Multiagent Systems · Computer Science 2021-05-04 Maha Riad , Fatemeh Golpayegani

The issue addressed in this paper is that of testing for common breaks across or within equations of a multivariate system. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null…

Statistics Theory · Mathematics 2018-01-12 Tatsushi Oka , Pierre Perron

Long-form generations from large language models (LLMs) contain a mix of factual and non-factual claims, making evaluating factuality difficult. Prior works evaluate the factuality of a long paragraph by decomposing it into multiple facts,…

Computation and Language · Computer Science 2024-06-10 Cheng-Han Chiang , Hung-yi Lee

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis…

Artificial Intelligence · Computer Science 2014-05-14 Yong Deng

We provide finite-sample distribution approximations, that are uniform in the parameter, for inference in linear mixed models. Focus is on variances and covariances of random effects in cases where existing theory fails because their…

Statistics Theory · Mathematics 2025-07-29 Karl Oskar Ekvall , Matteo Bottai

Large Language Models (LLMs) have demonstrated strong performance in question answering (QA) tasks. However, Multi-Answer Question Answering (MAQA), where a question may have several valid answers, remains challenging. Traditional QA…

Computation and Language · Computer Science 2025-08-19 Eviatar Nachshoni , Arie Cattan , Shmuel Amar , Ori Shapira , Ido Dagan

Randomised controlled trials (RCTs) are the most effective approach to causal discovery, but in many circumstances it is impossible to conduct RCTs. Therefore observational studies based on passively observed data are widely accepted as an…

Artificial Intelligence · Computer Science 2016-11-11 Jiuyong Li , Thuc Duy Le , Lin Liu , Jixue Liu , Zhou Jin , Bingyu Sun , Saisai Ma

These last years, there were many studies on the problem of the conflict coming from information combination, especially in evidence theory. We can summarise the solutions for manage the conflict into three different approaches: first, we…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

In the future, competitive advantages will be given to organisations that can extract valuable information from massive data and make better decisions. In most cases, this data comes from multiple sources. Therefore, the challenge is to…

Applications · Statistics 2016-05-11 Igor Barahona , Judith Cavazos , Jian-Bo Yang

Condorcet's Jury Theorem has been invoked for ensemble classifiers to indicate that the combination of many classifiers can have better predictive performance than a single classifier. Such a theoretical underpinning is unknown for…

Machine Learning · Statistics 2016-10-11 Brijnesh J. Jain