On the public citation graph

Simple estimators for relational Bayesian classifiers

https://doi.org/10.1109/icdm.2003.1250989

0 signed · 86 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-36468-4_9openalex-snapshot

1BC2: A True First-Order Bayesian Classifier

inferredcites →https://doi.org/10.1007/3-540-48751-4_10openalex-snapshot

1BC: A First-Order Bayesian Classifier

inferredcites →https://doi.org/10.1007/978-3-540-78652-8_7openalex-snapshot

Basic Principles of Learning Bayesian Logic Programs

inferredcites →https://doi.org/10.1007/978-3-662-04599-2_11openalex-snapshot

Propositionalization Approaches to Relational Data Mining

inferredcites →https://doi.org/10.1007/978-3-662-04599-2_13openalex-snapshot

Learning Probabilistic Relational Models

inferredcites →https://doi.org/10.1023/a:1007413511361openalex-snapshot

On the Optimality of the Simple Bayesian Classifier under Zero-One Loss

inferredcites →https://doi.org/10.1023/a:1009778005914openalex-snapshot

On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality

inferredcites →https://doi.org/10.1109/icdm.2003.1250989openalex-snapshot

Simple estimators for relational Bayesian classifiers

inferredcites →https://doi.org/10.1162/089976698300017197openalex-snapshot

Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms

inferredcites →https://doi.org/10.48550/arxiv.1302.4964openalex-snapshot

Estimating Continuous Distributions in Bayesian Classifiers

inferredcites →https://doi.org/10.5860/choice.33-5144openalex-snapshot

Empirical methods for artificial intelligence

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3199477openalex-extracted

Semantic Web Enabled Software Analysis

inferred← citeshttps://doi.org/10.1007/11564089_5openalex-snapshot

Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources

inferred← citeshttps://doi.org/10.1007/11811305_19openalex-snapshot

Robust Collective Classification with Contextual Dependency Network Models

inferred← citeshttps://doi.org/10.1007/978-3-319-07353-8_62openalex-snapshot

Classification for Multi-Relational Data Mining Using Bayesian Belief Network

inferred← citeshttps://doi.org/10.1007/978-3-319-18032-8_35openalex-snapshot

Graph Based Relational Features for Collective Classification

inferred← citeshttps://doi.org/10.1007/978-3-540-68234-9_36openalex-snapshot

Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods

inferred← citeshttps://doi.org/10.1007/978-3-540-73133-7_13openalex-snapshot

A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring

inferred← citeshttps://doi.org/10.1007/978-3-540-85066-3_12openalex-snapshot

A Survey of First-Order Probabilistic Models

inferred← citeshttps://doi.org/10.1007/978-3-642-05151-7_28openalex-snapshot

Learning Link-Based Naïve Bayes Classifiers from Ontology-Extended Distributed Data

inferred← citeshttps://doi.org/10.1007/978-3-642-14929-0_1openalex-snapshot

Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study

inferred← citeshttps://doi.org/10.1007/978-3-642-15880-3_42openalex-snapshot

Graph Regularized Transductive Classification on Heterogeneous Information Networks

inferred← citeshttps://doi.org/10.1007/978-3-642-23032-5_10openalex-snapshot

Application and Evaluation of Inductive Reasoning Methods for the Semantic Web and Software Analysis

inferred← citeshttps://doi.org/10.1007/978-3-642-23199-5_42openalex-snapshot

GA-TVRC: A Novel Relational Time Varying Classifier to Extract Temporal Information Using Genetic Algorithms

inferred← citeshttps://doi.org/10.1007/978-3-642-25073-6_25openalex-snapshot

Learning Relational Bayesian Classifiers from RDF Data

inferred← citeshttps://doi.org/10.1007/978-3-642-30217-6_1openalex-snapshot

Time-Evolving Relational Classification and Ensemble Methods

inferred← citeshttps://doi.org/10.1007/978-3-642-39712-7_44openalex-snapshot

Pre-release Box-Office Success Prediction for Motion Pictures

inferred← citeshttps://doi.org/10.1007/s10115-007-0093-3openalex-snapshot

Ensembles of relational classifiers

inferred← citeshttps://doi.org/10.1007/s10115-010-0373-1openalex-snapshot

Correcting evaluation bias of relational classifiers with network cross validation

inferred← citeshttps://doi.org/10.1007/s10115-011-0406-4openalex-snapshot

Distribution-free bounds for relational classification

inferred← citeshttps://doi.org/10.1007/s10618-013-0316-zopenalex-snapshot

GA-TVRC-Het: genetic algorithm enhanced time varying relational classifier for evolving heterogeneous networks

inferred← citeshttps://doi.org/10.1007/s10994-006-5832-2openalex-snapshot

XRules: An effective algorithm for structural classification of XML data

inferred← citeshttps://doi.org/10.1007/s10994-006-6064-1openalex-snapshot

Distribution-based aggregation for relational learning with identifier attributes

inferred← citeshttps://doi.org/10.1007/s10994-011-5244-9openalex-snapshot

Gradient-based boosting for statistical relational learning: The relational dependency network case

inferred← citeshttps://doi.org/10.1007/s42979-025-04639-1openalex-snapshot

A Survey of Link Prediction in Temporal Networks

inferred← citeshttps://doi.org/10.1016/j.dss.2009.07.004openalex-snapshot

Exploring optimization of semantic relationship graph for multi-relational Bayesian classification

inferred← citeshttps://doi.org/10.1016/j.dss.2012.11.017openalex-snapshot

Simple decision forests for multi-relational classification

inferred← citeshttps://doi.org/10.1016/j.websem.2010.04.009openalex-snapshot

Semantic web enabled software analysis

inferred← citeshttps://doi.org/10.1109/aici.2009.310openalex-snapshot

Multi-relational Classification Based on the Contribution of Tables

inferred← citeshttps://doi.org/10.1109/bigdata.2015.7363953openalex-snapshot

Learning classifiers from remote RDF data stores augmented with RDFS subclass hierarchies

inferred← citeshttps://doi.org/10.1109/bigdata.congress.2013.22openalex-snapshot

Learning Classifiers from Chains of Multiple Interlinked RDF Data Stores

inferred← citeshttps://doi.org/10.1109/bigdata.congress.2013.47openalex-snapshot

Learning Classifiers from Distributional Data

inferred← citeshttps://doi.org/10.1109/cidm.2013.6597230openalex-snapshot

A hierarchy of independence assumptions for multi-relational Bayes net classifiers

inferred← citeshttps://doi.org/10.1109/cidm.2014.7008657openalex-snapshot

Aggregating predictions vs. aggregating features for relational classification

inferred← citeshttps://doi.org/10.1109/enc.2009.23openalex-snapshot

Meaningful Error Estimations for Data Analysis

inferred← citeshttps://doi.org/10.1109/grc.2008.4664739openalex-snapshot

Fuzzy clustering and iterative relational classification for terrorist profiling

inferred← citeshttps://doi.org/10.1109/grc.2009.5255041openalex-snapshot

Random forest for relational classification with application to terrorist profiling

inferred← citeshttps://doi.org/10.1109/icdm.2005.89openalex-snapshot

Leveraging Relational Autocorrelation with Latent Group Models

inferred← citeshttps://doi.org/10.1109/icdm.2006.135openalex-snapshot

Relational Ensemble Classification

inferred← citeshttps://doi.org/10.1109/icdm.2008.125openalex-snapshot

Temporal-Relational Classifiers for Prediction in Evolving Domains

inferred← citeshttps://doi.org/10.1109/icdm.2008.148openalex-snapshot

Pseudolikelihood EM for Within-network Relational Learning

inferred← citeshttps://doi.org/10.1109/icdmw.2007.15openalex-snapshot

Twin Kernel Embedding with Back Constraints

inferred← citeshttps://doi.org/10.1109/icdmw.2007.27openalex-snapshot

An Examination of Experimental Methodology for Classifiers of Relational Data

inferred← citeshttps://doi.org/10.1109/icdmw.2009.116openalex-snapshot

LNBC: A Link-Based Naive Bayes Classifier

inferred← citeshttps://doi.org/10.1109/ictai.2009.111openalex-snapshot

Learning Link-Based Classifiers from Ontology-Extended Textual Data

inferred← citeshttps://doi.org/10.1109/ictai52525.2021.00098openalex-snapshot

Aggregate Function Generalization to Temporal Data

inferred← citeshttps://doi.org/10.1109/ijcnn.2012.6252762openalex-snapshot

Graph-based coupled behavior analysis: A case study on detecting collaborative manipulations in stock markets

inferred← citeshttps://doi.org/10.1109/tkde.2006.178openalex-snapshot

Learning Contextual Dependency Network Models for Link-Based Classification

inferred← citeshttps://doi.org/10.1109/tmm.2011.2181941openalex-snapshot

A Nonverbal Behavior Approach to Identify Emergent Leaders in Small Groups

inferred← citeshttps://doi.org/10.1137/1.9781611972801.35openalex-snapshot

On the Use of Combining Rules in Relational Probability Trees

inferred← citeshttps://doi.org/10.1145/1014052.1014125openalex-snapshot

Why collective inference improves relational classification

inferred← citeshttps://doi.org/10.1145/1090193.1090200openalex-snapshot

An efficient multi-relational Naïve Bayesian classifier based on semantic relationship graph

inferred← citeshttps://doi.org/10.1145/1348549.1348551openalex-snapshot

Exploiting time-varying relationships in statistical relational models

inferred← citeshttps://doi.org/10.1145/2076623.2076637openalex-snapshot

Boosting tuple propagation in multi-relational classification

inferred← citeshttps://doi.org/10.1145/2898358openalex-snapshot

Leveraging Neighbor Attributes for Classification in Sparsely Labeled Networks

inferred← citeshttps://doi.org/10.1145/2974720openalex-snapshot

inferred← citeshttps://doi.org/10.1145/956750.956830openalex-snapshot

Learning relational probability trees

inferred← citeshttps://doi.org/10.1155/2020/6613896openalex-snapshot

Dynamic Knowledge Inference Based on Bayesian Network Learning

inferred← citeshttps://doi.org/10.14711/thesis-b1115031openalex-snapshot

Latent factor models for statistical relational learning

inferred← citeshttps://doi.org/10.14778/2535573.2488340openalex-snapshot

Scaling factorization machines to relational data

inferred← citeshttps://doi.org/10.1613/jair.3659openalex-snapshot

Transforming Graph Data for Statistical Relational Learning

inferred← citeshttps://doi.org/10.21236/ada436228openalex-snapshot

Analytical Tools for Investigating and Modeling Agent-Based Systems

inferred← citeshttps://doi.org/10.21236/ada452802openalex-snapshot

A Simple Relational Classifier

inferred← citeshttps://doi.org/10.21236/ada472209openalex-snapshot

Spectral Clustering with Links and Attributes

inferred← citeshttps://doi.org/10.2172/926032openalex-snapshot

Leveraging Structure to Improve Classification Performance in Sparsely Labeled Networks

inferred← citeshttps://doi.org/10.31274/etd-180810-1705openalex-snapshot

Abstraction-based probabilistic models for sequence classification

inferred← citeshttps://doi.org/10.31274/etd-180810-1815openalex-snapshot

Learning predictive models from massive, semantically disparate data

inferred← citeshttps://doi.org/10.31274/etd-180810-3573openalex-snapshot

Learning classifiers from linked data

inferred← citeshttps://doi.org/10.48550/arxiv.2003.12169openalex-snapshot

A Collective Learning Framework to Boost GNN Expressiveness

inferred← citeshttps://doi.org/10.5075/epfl-thesis-5662openalex-snapshot

Computational Methods for Audio-Visual Analysis of Emergent Leadership in Teams

inferred← citeshttps://doi.org/10.5555/1248659.1248677openalex-snapshot

Integrating Naïve Bayes and FOIL

inferred← citeshttps://doi.org/10.5555/1577069.1755879openalex-snapshot

Cautious Collective Classification

inferred← citeshttps://doi.org/10.5555/1931390.1931456openalex-snapshot

Discovering missing values in semi-structured databases

inferred← citeshttps://doi.org/10.7551/mitpress/7432.003.0010openalex-snapshot

Relational Dependency Networks

inferred← citeshttps://doi.org/10.7763/ijcce.2013.v2.191openalex-snapshot

A New Model for Web Content Distributed Data Mining Based on SOAP and Ontology

showing the first 74 of 75

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.