On the public citation graph

A Categorical Representation of Multi-Feature Fusion for Mixed Attribute Data Clustering

https://doi.org/10.2139/ssrn.4690078
0 signed · 43 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-3-030-31254-1_12openalex-extracted
Evaluation of the MRI Images Matching Using Normalized Mutual Information Method and Preprocessing Techniques
inferredcites →https://doi.org/10.1007/s00500-019-04586-zopenalex-extracted
Multi-view heterogeneous fusion and embedding for categorical attributes on mixed data
inferredcites →https://doi.org/10.1007/s10489-019-01583-5openalex-extracted
A dissimilarity measure for mixed nominal and ordinal attribute data in k-Modes algorithm
inferredcites →https://doi.org/10.1007/s10489-023-04899-5openalex-extracted
An attribute-weighted isometric embedding method for categorical encoding on mixed data
inferredcites →https://doi.org/10.1007/s13042-022-01602-xopenalex-extracted
Clustering mixed type data: a space structure-based approach
inferredcites →https://doi.org/10.1016/b978-0-12-818630-5.10070-3openalex-extracted
Categorical data analysis
inferredcites →https://doi.org/10.1016/j.eswa.2021.115591openalex-extracted
Incremental semi-supervised Extreme Learning Machine for Mixed data stream classification
inferredcites →https://doi.org/10.1016/j.ins.2022.09.045openalex-extracted
Multi-view representation learning for data stream clustering
inferredcites →https://doi.org/10.1016/j.ipm.2014.08.007openalex-extracted
Coupling learning of complex interactions
inferredcites →https://doi.org/10.1016/j.is.2020.101592openalex-extracted
Relevance- and interface-driven clustering for visual information retrieval
inferredcites →https://doi.org/10.1016/j.knosys.2022.110161openalex-extracted
A Multi-View Deep Metric Learning approach for Categorical Representation on mixed data
inferredcites →https://doi.org/10.1016/j.neucom.2020.12.032openalex-extracted
A method for mixed data classification base on RBF-ELM network
inferredcites →https://doi.org/10.1016/j.patcog.2016.04.015openalex-extracted
Towards parameter-independent data clustering and image segmentation
inferredcites →https://doi.org/10.1016/j.patcog.2023.109353openalex-extracted
A generalized multi-aspect distance metric for mixed-type data clustering
inferredcites →https://doi.org/10.1016/j.patrec.2017.07.001openalex-extracted
A novel density peaks clustering algorithm for mixed data
inferredcites →https://doi.org/10.1016/j.socnet.2015.03.002openalex-extracted
A note on using the adjusted Rand index for link prediction in networks
inferredcites →https://doi.org/10.1038/s41598-022-12224-2openalex-extracted
Kendall transformation brings a robust categorical representation of ordinal data
inferredcites →https://doi.org/10.1080/03610918.2014.931971openalex-extracted
Overview of Friedman’s Test and Post-hoc Analysis
inferredcites →https://doi.org/10.1101/196840openalex-extracted
The Impact of Random Models on Clustering Similarity
inferredcites →https://doi.org/10.1109/cisis.2016.89openalex-extracted
A Neural Network Based User Identification for Tor Networks: Comparison Analysis of Activation Function Using Friedman Test
inferredcites →https://doi.org/10.1109/dsit55514.2022.9943828openalex-extracted
Clustering Algorithm with Learnable Distance for Categorical Data with Nominal and Ordinal Attributes
inferredcites →https://doi.org/10.1109/ijcnn.2014.6889890openalex-extracted
A new distance metric for unsupervised learning of categorical data
inferredcites →https://doi.org/10.1109/is.2006.348479openalex-extracted
A Method for Fuzzy Clustering with Ordinal Attributes Replaced by Fuzzy Set Parameters
inferredcites →https://doi.org/10.1109/tcyb.2020.2983073openalex-extracted
A New Distance Metric Exploiting Heterogeneous Interattribute Relationship for Ordinal-and-Nominal-Attribute Data Clustering
inferredcites →https://doi.org/10.1109/tkde.2018.2791525openalex-extracted
Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings
inferredcites →https://doi.org/10.1109/tkde.2018.2848902openalex-extracted
CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning
inferredcites →https://doi.org/10.1109/tnnls.2014.2325872openalex-extracted
Coupled Attribute Similarity Learning on Categorical Data
inferredcites →https://doi.org/10.1109/tnnls.2014.2339100openalex-extracted
Ordinal Distance Metric Learning for Image Ranking
inferredcites →https://doi.org/10.1109/tnnls.2015.2436432openalex-extracted
A New Distance Metric for Unsupervised Learning of Categorical Data
inferredcites →https://doi.org/10.1109/tnnls.2019.2899381openalex-extracted
A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering
inferredcites →https://doi.org/10.1109/tnnls.2021.3059874openalex-extracted
Adaptive Transition Probability Matrix Learning for Multiview Spectral Clustering
inferredcites →https://doi.org/10.1109/tpami.2013.50openalex-extracted
Representation Learning: A Review and New Perspectives
inferredcites →https://doi.org/10.1109/tpami.2021.3056510openalex-extracted
Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes
inferredcites →https://doi.org/10.1109/tsmcc.2013.2247595openalex-extracted
Addressing the EU Sovereign Ratings Using an Ordinal Regression Approach
inferredcites →https://doi.org/10.1111/bmsp.12212openalex-extracted
A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation
inferredcites →https://doi.org/10.1137/1.9781611974010.6openalex-extracted
From Categorical to Numerical: Multiple Transitive Distance Learning and Embedding
inferredcites →https://doi.org/10.1145/3206098.3206099openalex-extracted
A new text representation method for clustering based on higher order Markov model
inferredcites →https://doi.org/10.1371/journal.pone.0087357openalex-extracted
Mutual Information between Discrete and Continuous Data Sets
inferredcites →https://doi.org/10.1609/aaai.v32i1.11597openalex-extracted
Metric-Based Auto-Instructor for Learning Mixed Data Representation
inferredcites →https://doi.org/10.3233/jifs-200298openalex-extracted
Auto-weighted concept factorization for joint feature map and data representation learning
inferredcites →https://doi.org/10.3390/e19040157openalex-extracted
Quadratic Mutual Information Feature Selection
inferredcites →https://doi.org/10.3390/e23080964openalex-extracted
Learning Ordinal Embedding from Sets
inferredcites →https://doi.org/10.4324/9780203774441openalex-extracted
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
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.