On the public citation graph

OVWTRE: A program for optimal variable weighting for ultrametric and additive tree fitting

0 signed · 70 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1002/spe.4380040405openalex-snapshot
The pfort verifier
inferredcites →https://doi.org/10.1007/bf00227423openalex-snapshot
Optimal variable weighting for ultrametric and additive tree clustering
inferredcites →https://doi.org/10.1007/bf01908588openalex-snapshot
A validation study of a variable weighting algorithm for cluster analysis
inferredcites →https://doi.org/10.1007/bf02293654openalex-snapshot
Additive Similarity Trees
inferredcites →https://doi.org/10.1007/bf02293884openalex-snapshot
A Least Squares Algorithm for Fitting Additive Trees to Proximity Data
inferredcites →https://doi.org/10.1016/0022-2496(78)90029-9openalex-snapshot
Free trees and bidirectional trees as representations of psychological distance
inferredcites →https://doi.org/10.1016/c2013-0-06161-0openalex-snapshot
Cluster Analysis for Applications
inferredcites →https://doi.org/10.1145/22899.22904openalex-snapshot
Distribution of mathematical software via electronic mail
inferredcites →https://doi.org/10.1145/355780.355783openalex-snapshot
The PORT Mathematical Subroutine Library
inferredcites →https://doi.org/10.1145/355780.355789openalex-snapshot
Algorithm 528: Framework for a Portable Library [Z]
inferredcites →https://doi.org/10.2307/2286880openalex-snapshot
Clustering Algorithms.

What points at this work

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

inferred← citeshttps://doi.org/10.1002/0471264385.wei0207openalex-snapshot
Clustering and Classification Methods
inferred← citeshttps://doi.org/10.1002/0471667196.ess0613openalex-snapshot
C luster Analysis
inferred← citeshttps://doi.org/10.1002/0471667196.ess0613.pub2openalex-snapshot
Cluster Analysis
inferred← citeshttps://doi.org/10.1002/9781118133880.hop202007openalex-snapshot
Clustering and Classification Methods
inferred← citeshttps://doi.org/10.1002/cne.22127openalex-snapshot
Retinal ganglion cells in the eastern newt Notophthalmus viridescens: Topography, morphology, and diversity
inferred← citeshttps://doi.org/10.1002/cne.23489openalex-snapshot
Retinal ganglion cells in the Pacific redfin, Tribolodon brandtii dybowski, 1872: Morphology and diversity
inferred← citeshttps://doi.org/10.1002/j.2333-8504.1994.tb01609.xopenalex-snapshot
VARIABLE SCREENING FOR CLUSTER ANALYSIS
inferred← citeshttps://doi.org/10.1002/j.2333-8504.1994.tb01619.xopenalex-snapshot
A PRELIMINARY STUDY OF THE EFFECTS OF WITHIN‐GROUP COVARIANCE STRUCTURE ON RECOVERY IN CLUSTER ANALYSIS
inferred← citeshttps://doi.org/10.1002/j.2333-8504.1995.tb01670.xopenalex-snapshot
A PRELIMINARY COMPARISON OF THE EFFECTIVENESS OF CLUSTER ANALYSIS WEIGHTING PROCEDURES FOR WITHIN‐GROUP COVARIANCE STRUCTURE
inferred← citeshttps://doi.org/10.1002/j.2333-8504.1999.tb01806.xopenalex-snapshot
THE EFFECTS OF WITHIN‐GROUP COVARIANCE STRUCTURE ON RECOVERY IN CLUSTER ANALYSIS: II. EXTENSION TO THE P‐DIMENSIONAL CASE
inferred← citeshttps://doi.org/10.1002/nav.20059openalex-snapshot
Determining newspaper marketing zones using contiguous clustering
inferred← citeshttps://doi.org/10.1007/978-3-319-17356-6_36openalex-snapshot
An Empirical Assessment of Two Univariate Screening Measures in Cluster Analysis
inferred← citeshttps://doi.org/10.1007/978-3-319-19090-7_35openalex-snapshot
A Clustering-Based Approach to Reduce Feature Redundancy
inferred← citeshttps://doi.org/10.1007/978-3-319-24211-8_13openalex-snapshot
Extending Kmeans-Type Algorithms by Integrating Intra-cluster Compactness and Inter-cluster Separation
inferred← citeshttps://doi.org/10.1007/978-3-319-26187-4_9openalex-snapshot
A Soft Subspace Clustering Method for Text Data Using a Probability Based Feature Weighting Scheme
inferred← citeshttps://doi.org/10.1007/978-3-642-79999-0_1openalex-snapshot
Advances in Cluster Analysis Relevant to Marketing Research
inferred← citeshttps://doi.org/10.1007/bf01202271openalex-snapshot
Weighting and selection of variables for cluster analysis
inferred← citeshttps://doi.org/10.1007/bf01908588openalex-snapshot
A validation study of a variable weighting algorithm for cluster analysis
inferred← citeshttps://doi.org/10.1007/bf02294838openalex-snapshot
A Variable-Selection Heuristic for K-means Clustering
inferred← citeshttps://doi.org/10.1007/s00357-001-0018-xopenalex-snapshot
Optimal Variable Weighting for Ultrametric and Additive Trees and K-means Partitioning: Methods and Software
inferred← citeshttps://doi.org/10.1007/s00357-015-9167-1openalex-snapshot
Feature Relevance in Ward’s Hierarchical Clustering Using the L p Norm
inferred← citeshttps://doi.org/10.1007/s00357-016-9208-4openalex-snapshot
A Survey on Feature Weighting Based K-Means Algorithms
inferred← citeshttps://doi.org/10.1007/s00357-017-9240-zopenalex-snapshot
rCOSA: A Software Package for Clustering Objects on Subsets of Attributes
inferred← citeshttps://doi.org/10.1007/s00357-017-9245-7openalex-snapshot
Editorial
inferred← citeshttps://doi.org/10.1007/s10994-016-5623-3openalex-snapshot
Feature-weighted clustering with inner product induced norm based dissimilarity measures: an optimization perspective
inferred← citeshttps://doi.org/10.1016/j.csda.2008.03.002openalex-snapshot
Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm
inferred← citeshttps://doi.org/10.1016/j.ins.2016.07.060openalex-snapshot
Investigating the role of the rating prediction task in granularity-based group recommender systems and big data scenarios
inferred← citeshttps://doi.org/10.1016/j.jweia.2022.105124openalex-snapshot
A zoning method for the extreme wind pressure coefficients of buildings based on weighted K-means clustering
inferred← citeshttps://doi.org/10.1016/j.knosys.2014.07.009openalex-snapshot
DSKmeans: A new kmeans-type approach to discriminative subspace clustering
inferred← citeshttps://doi.org/10.1016/j.neucom.2012.11.009openalex-snapshot
A weighting k-modes algorithm for subspace clustering of categorical data
inferred← citeshttps://doi.org/10.1016/j.patcog.2009.09.010openalex-snapshot
Enhanced soft subspace clustering integrating within-cluster and between-cluster information
inferred← citeshttps://doi.org/10.1016/j.patrec.2015.06.001openalex-snapshot
Automated feature weighting in clustering with separable distances and inner product induced norms – A theoretical generalization
inferred← citeshttps://doi.org/10.1016/j.sapharm.2007.02.001openalex-snapshot
The uses and benefits of cluster analysis in pharmacy research
inferred← citeshttps://doi.org/10.1016/s1364-8152(02)00094-4openalex-snapshot
An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis
inferred← citeshttps://doi.org/10.1017/s0952523811000320openalex-snapshot
A multivariate approach to structural heterogeneity of retinal ganglion cells
inferred← citeshttps://doi.org/10.1109/access.2019.2924491openalex-snapshot
Sequential Minimax Search for Multi-Layer Gene Grouping
inferred← citeshttps://doi.org/10.1109/icpr.2006.603openalex-snapshot
Genetic-based K-means algorithm for selection of feature variables
inferred← citeshttps://doi.org/10.1109/ieec.2009.17openalex-snapshot
Weighted k-Means Algorithm Based Text Clustering
inferred← citeshttps://doi.org/10.1109/iri.2013.6642535openalex-snapshot
MFWK-Means: Minkowski metric Fuzzy Weighted K-Means for high dimensional data clustering
inferred← citeshttps://doi.org/10.1109/tkde.2007.1048openalex-snapshot
An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data
inferred← citeshttps://doi.org/10.1109/tkde.2011.262openalex-snapshot
TW-k-means: Automated two-level variable weighting clustering algorithm for multiview data
inferred← citeshttps://doi.org/10.1109/tnnls.2013.2293795openalex-snapshot
Extensions of Kmeans-Type Algorithms: A New Clustering Framework by Integrating Intracluster Compactness and Intercluster Separation
inferred← citeshttps://doi.org/10.1109/tpami.2005.95openalex-snapshot
Automated variable weighting in k-means type clustering
inferred← citeshttps://doi.org/10.1111/j.1467-9868.2004.02059.xopenalex-snapshot
Clustering Objects on Subsets of Attributes (with Discussion)
inferred← citeshttps://doi.org/10.1155/jbb.2005.215openalex-snapshot
Finding Groups in Gene Expression Data
inferred← citeshttps://doi.org/10.1177/002224379903600408openalex-snapshot
HINoV: A New Model to Improve Market Segment Definition by Identifying Noisy Variables
inferred← citeshttps://doi.org/10.1177/076737019000500104openalex-snapshot
Analyse structurelle et analyse typologique: Illustration d'une démarche complémentaire
inferred← citeshttps://doi.org/10.1207/s15327906mbr3002_6openalex-snapshot
The Effects of Within-group Covariance Structure on Recovery in Cluster Analysis: I. The Bivariate Case
inferred← citeshttps://doi.org/10.1207/s15327906mbr3003_5openalex-snapshot
Univariate Screening Measures for Cluster Analysis
inferred← citeshttps://doi.org/10.1207/s15327906mbr3502_5openalex-snapshot
Validating Cluster Analysis: Consistent Replication and Symmetry
inferred← citeshttps://doi.org/10.1300/j142v04n01_07openalex-snapshot
An Investigation of the Efficacy of Univariate Screening Measures in Defining Market Structure
inferred← citeshttps://doi.org/10.1348/000711005x48266openalex-snapshot
K‐means clustering: A half‐century synthesis
inferred← citeshttps://doi.org/10.18778/7525-695-6openalex-snapshot
Metody selekcji zmiennych w analizie skupień. Nowe procedury
inferred← citeshttps://doi.org/10.26180/4621684openalex-snapshot
Classification methods for time series
inferred← citeshttps://doi.org/10.3233/ida-163222openalex-snapshot
A co-evolutionary framework for adaptive multidimensional data clustering
inferred← citeshttps://doi.org/10.3390/e21070683openalex-snapshot
An Entropy Regularization k-Means Algorithm with a New Measure of between-Cluster Distance in Subspace Clustering
inferred← citeshttps://doi.org/10.3390/info10060208openalex-snapshot
Latent Feature Group Learning for High-Dimensional Data Clustering
inferred← citeshttps://doi.org/10.3390/su10093095openalex-snapshot
Theoretical Guidance on Evacuation Decisions after a Big Nuclear Accident under the Assumption That Evacuation Is Desirable
inferred← citeshttps://doi.org/10.5220/0004865005640572openalex-snapshot
Using Collaborative Filtering to Overcome the Curse of Dimensionality when Clustering Users in a Group Recommender System
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.