On the public citation graph

CrossMine: Efficient Classification Across Multiple Database Relations

https://doi.org/10.1007/11615576_9
0 signed · 97 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/3-540-56602-3_124openalex-snapshot
FOIL: A midterm report
inferredcites →https://doi.org/10.1007/978-3-540-39917-9_3openalex-snapshot
Mining Model Trees: A Multi-relational Approach
inferredcites →https://doi.org/10.1007/bf03037089openalex-snapshot
Inductive logic programming
inferredcites →https://doi.org/10.1007/bf03037227openalex-snapshot
Inverse entailment and progol
inferredcites →https://doi.org/10.1007/bfb0017011openalex-snapshot
Rule induction with CN2: Some recent improvements
inferredcites →https://doi.org/10.1016/s0004-3702(98)00034-4openalex-snapshot
Top-down induction of first-order logical decision trees
inferredcites →https://doi.org/10.1023/a:1009715923555openalex-snapshot
A Tutorial on Support Vector Machines for Pattern Recognition
inferredcites →https://doi.org/10.1023/a:1009839829793openalex-snapshot
RainForest—A Framework for Fast Decision Tree Construction of Large Datasets
inferredcites →https://doi.org/10.1023/a:1009867806624openalex-snapshot
Scaling Up Inductive Logic Programming by Learning from Interpretations
inferredcites →https://doi.org/10.1145/956750.956830openalex-snapshot
Learning relational probability trees
inferredcites →https://doi.org/10.1145/956804.956830openalex-snapshot
Learning relational probability trees
inferredcites →https://doi.org/10.1613/jair.924openalex-snapshot
Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs
inferredcites →https://doi.org/10.48550/arxiv.cs/0011032openalex-snapshot
Top-down induction of clustering trees

What points at this work

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

inferred← citeshttps://doi.org/10.1002/spe.3165openalex-snapshot
Horn rule discovery with batched caching and rule identifier for proficient compressor of knowledge data
inferred← citeshttps://doi.org/10.1007/11536314_5openalex-snapshot
A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment
inferred← citeshttps://doi.org/10.1007/11564126_40openalex-snapshot
Efficient Classification from Multiple Heterogeneous Databases
inferred← citeshttps://doi.org/10.1007/978-3-319-04534-4_9openalex-snapshot
Learning Bayes Nets for Relational Data with Link Uncertainty
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/10.1007/978-3-540-68123-6_12openalex-snapshot
Mining Induced and Embedded Subtrees in Ordered, Unordered, and Partially-Ordered Trees
inferred← citeshttps://doi.org/10.1007/978-3-540-68123-6_2openalex-snapshot
Exploring the Power of Heuristics and Links in Multi-relational Data Mining
inferred← citeshttps://doi.org/10.1007/978-3-540-74976-9_43openalex-snapshot
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
inferred← citeshttps://doi.org/10.1007/978-3-540-74976-9_47openalex-snapshot
Pruning Relations for Substructure Discovery of Multi-relational Databases
inferred← citeshttps://doi.org/10.1007/978-3-540-88192-6_9openalex-snapshot
FARS: A Multi-relational Feature and Relation Selection Approach for Efficient Classification
inferred← citeshttps://doi.org/10.1007/978-3-642-04125-9_5openalex-snapshot
Frequent Itemset Mining in Multirelational Databases
inferred← citeshttps://doi.org/10.1007/978-3-642-17313-4_3openalex-snapshot
A General Multi-relational Classification Approach Using Feature Generation and Selection
inferred← citeshttps://doi.org/10.1007/978-3-642-21916-0_2openalex-snapshot
Relational Mining in Spatial Domains: Accomplishments and Challenges
inferred← citeshttps://doi.org/10.1007/978-3-642-24477-3_11openalex-snapshot
A Methodology for Mining Document-Enriched Heterogeneous Information Networks
inferred← citeshttps://doi.org/10.1007/978-3-642-31537-4_2openalex-snapshot
Transductive Relational Classification in the Co-training Paradigm
inferred← citeshttps://doi.org/10.1007/s10115-008-0127-5openalex-snapshot
Multirelational classification: a multiple view approach
inferred← citeshttps://doi.org/10.1007/s10115-024-02139-xopenalex-snapshot
Methods for concept analysis and multi-relational data mining: a systematic literature review
inferred← citeshttps://doi.org/10.1007/s10618-007-0072-zopenalex-snapshot
CrossClus: user-guided multi-relational clustering
inferred← citeshttps://doi.org/10.1007/s10618-011-0218-xopenalex-snapshot
Using trees to mine multirelational databases
inferred← citeshttps://doi.org/10.1007/s10994-012-5289-4openalex-snapshot
Learning graphical models for relational data via lattice search
inferred← citeshttps://doi.org/10.1007/s10994-012-5308-5openalex-snapshot
Learning directed relational models with recursive dependencies
inferred← citeshttps://doi.org/10.1007/s10994-013-5362-7openalex-snapshot
Modelling relational statistics with Bayes Nets
inferred← citeshttps://doi.org/10.1007/s10994-016-5557-9openalex-snapshot
Fast learning of relational dependency networks
inferred← citeshttps://doi.org/10.1007/s10994-018-5746-9openalex-snapshot
A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data
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.eswa.2007.05.048openalex-snapshot
An approach to mining the multi-relational imbalanced database
inferred← citeshttps://doi.org/10.1016/j.eswa.2009.02.100openalex-snapshot
ILP-based concept discovery in multi-relational data mining
inferred← citeshttps://doi.org/10.1016/j.eswa.2011.03.038openalex-snapshot
A comparative study on ILP-based concept discovery systems
inferred← citeshttps://doi.org/10.1016/j.eswa.2016.10.059openalex-snapshot
A framework for data transformation in Credit Behavioral Scoring applications based on Model Driven Development
inferred← citeshttps://doi.org/10.1016/j.knosys.2010.04.011openalex-snapshot
Concept discovery on relational databases: New techniques for search space pruning and rule quality improvement
inferred← citeshttps://doi.org/10.1016/j.knosys.2011.11.001openalex-snapshot
Improving the scalability of ILP-based multi-relational concept discovery system through parallelization
inferred← citeshttps://doi.org/10.1016/j.patcog.2012.06.015openalex-snapshot
Combining heterogeneous classifiers for relational databases
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/csiec.2016.7482131openalex-snapshot
Multi relational-upgraded methods: Classification and analysis in supervised learning
inferred← citeshttps://doi.org/10.1109/icde.2006.154openalex-snapshot
Systematic Approach for Optimizing Complex Mining Tasks on Multiple Databases
inferred← citeshttps://doi.org/10.1109/icdmw.2009.116openalex-snapshot
LNBC: A Link-Based Naive Bayes Classifier
inferred← citeshttps://doi.org/10.1109/icdmw.2010.33openalex-snapshot
Identifying and Preventing Data Leakage in Multi-relational Classification
inferred← citeshttps://doi.org/10.1109/icgccee.2014.6922401openalex-snapshot
Proposed efficient approach for classification for multi-relational data mining using Bayesian Belief Network
inferred← citeshttps://doi.org/10.1109/iciss.2010.5654933openalex-snapshot
A method of spatial clustering based on the combination of the spatial coordinate and attributes
inferred← citeshttps://doi.org/10.1109/icmla.2007.108openalex-snapshot
Toward Optimal Selection of Feature Clusters
inferred← citeshttps://doi.org/10.1109/icmlc.2007.4370836openalex-snapshot
A Multi-Relational Hierarchical Clustering Algorithm Based on Shared Nearest Neighbor Similarity
inferred← citeshttps://doi.org/10.1109/ijcnn.2006.1716831openalex-snapshot
Multi-view ANNs for Multi-relational Classification
inferred← citeshttps://doi.org/10.1109/iscis.2009.5291821openalex-snapshot
Multi-relational concept discovery with aggregation
inferred← citeshttps://doi.org/10.1109/itaic.2014.7065107openalex-snapshot
Hierarchical semisupervised transfer AdaBoost
inferred← citeshttps://doi.org/10.1109/pst.2012.6297921openalex-snapshot
Aggregation and privacy in multi-relational databases
inferred← citeshttps://doi.org/10.1109/wism.2009.60openalex-snapshot
MrCAR: A Multi-relational Classification Algorithm Based on Association Rules
inferred← citeshttps://doi.org/10.1111/j.1467-8640.2010.00359.xopenalex-snapshot
SELECTING EFFECTIVE FEATURES AND RELATIONS FOR EFFICIENT MULTI‐RELATIONAL CLASSIFICATION
inferred← citeshttps://doi.org/10.1137/1.9781611972757.56openalex-snapshot
Pushing Feature Selection ahead of Join
inferred← citeshttps://doi.org/10.1137/1.9781611972757.64openalex-snapshot
Building Decision Trees on Records Linked through Key References
inferred← citeshttps://doi.org/10.1137/1.9781611972818.40openalex-snapshot
A Tractable Pseudo-Likelihood Function for Bayes Nets Applied to Relational Data
inferred← citeshttps://doi.org/10.1142/s0218194018400260openalex-snapshot
Evolutionary Propositionalization of Multi-Relational Data — Research Notes
inferred← citeshttps://doi.org/10.1145/1081870.1081910openalex-snapshot
Cross-relational clustering with user's guidance
inferred← citeshttps://doi.org/10.1145/1090193.1090197openalex-snapshot
Mining relational databases with multi-view learning
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/10.1145/1134271.1134280openalex-snapshot
Mining hidden community in heterogeneous social networks
inferred← citeshttps://doi.org/10.1145/1150402.1150469openalex-snapshot
Mining relational data through correlation-based multiple view validation
inferred← citeshttps://doi.org/10.1145/1183614.1183637openalex-snapshot
Classification spanning correlated data streams
inferred← citeshttps://doi.org/10.1145/1353343.1353391openalex-snapshot
Cost-based query optimization for complex pattern mining on multiple databases
inferred← citeshttps://doi.org/10.1145/1540276.1540283openalex-snapshot
Scalable mining and link analysis across multiple database relations
inferred← citeshttps://doi.org/10.1145/1557019.1557058openalex-snapshot
A multi-relational approach to spatial classification
inferred← citeshttps://doi.org/10.1145/1557019.1557071openalex-snapshot
Characteristic relational patterns
inferred← citeshttps://doi.org/10.1145/1966874.1966875openalex-snapshot
Regression on evolving multi-relational data streams
inferred← citeshttps://doi.org/10.1145/3448016.3457275openalex-snapshot
Scalable and Usable Relational Learning With Automatic Language Bias
inferred← citeshttps://doi.org/10.1360/jos182752openalex-snapshot
Mining of Multi-Relational Association Rules
inferred← citeshttps://doi.org/10.14778/3157794.3157804openalex-snapshot
Are key-foreign key joins safe to avoid when learning high-capacity classifiers?
inferred← citeshttps://doi.org/10.1613/jair.3659openalex-snapshot
Transforming Graph Data for Statistical Relational Learning
inferred← citeshttps://doi.org/10.18293/seke2018-136openalex-snapshot
Evolutionary propositionalization of multi-relational data
inferred← citeshttps://doi.org/10.3233/ida-130574openalex-snapshot
Interestingness measures for association rules within groups
inferred← citeshttps://doi.org/10.32628/cseit2390656openalex-snapshot
A Survey on Relational Database Based Multi Relational Classification Algorithms
inferred← citeshttps://doi.org/10.3844/jmssp.2008.51.57openalex-snapshot
Framework of Regression-Based Graph Matrix Analysis Approach in Multi-Relational Social Network Problem
inferred← citeshttps://doi.org/10.4018/978-1-60566-010-3.ch094openalex-snapshot
Database Queries, Data Mining, and OLAP
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amr.791-793.1385openalex-snapshot
Simulation on K-Means Optimum Clustering Mining Algorithm Based on Slope Classification
inferred← citeshttps://doi.org/10.48550/arxiv.0811.4458openalex-snapshot
Learning Class-Level Bayes Nets for Relational Data
inferred← citeshttps://doi.org/10.48550/arxiv.2110.09767openalex-snapshot
Pre and Post Counting for Scalable Statistical-Relational Model Discovery
inferred← citeshttps://doi.org/10.5120/10719-5485openalex-snapshot
State of Art of Multi Relational Data Mining Approaches: A Rule Mining Algorithm
inferred← citeshttps://doi.org/10.5120/12153-8126openalex-snapshot
Relational Classification using Multiple View Approach with Voting
inferred← citeshttps://doi.org/10.5120/1740-2366openalex-snapshot
A Study on Classification Approaches across Multiple Database Relations
inferred← citeshttps://doi.org/10.5120/8765-2685openalex-snapshot
Analysis and Comparative Study of Classifiers for Relational Data Mining
inferred← citeshttps://doi.org/10.53730/ijhs.v6ns3.7693openalex-snapshot
Exploring the gender inequality gap
inferred← citeshttps://doi.org/10.5555/1497096.1497101openalex-snapshot
Learning from Skewed Class Multi-relational Databases
inferred← citeshttps://doi.org/10.70675/6a8e2fd3zb9a1z48cfzadeez002302237cafopenalex-snapshot
Vers l’universalité des représentations visuelle et multimodales
inferred← citeshttps://doi.org/10.70675/b951209bz93b6z49dfz8d98z2818f51f13b4openalex-snapshot
Flexible and Scalable methods for Formal Concept Analysis in Distributed Architectures
inferred← citeshttps://doi.org/10.9790/0661-16297481openalex-snapshot
A Multi-Relational Decision Tree Learning (MRDTL) Approach: A Survey
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.