Reference health

Building text classifiers using positive and unlabeled examples

https://doi.org/10.1109/icdm.2003.1250918
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9/9 checkable references clean · checked 2026-07-24

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

26 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 9 checked references that resolve
resolves10.1145/312624.312647
A re-examination of text categorization methods
resolves10.1007/978-1-4757-2440-0
The Nature of Statistical Learning Theory
resolves10.1007/BFb0026683
Text categorization with Support Vector Machines: Learning with many relevant features
resolves10.1016/B978-1-55860-377-6.50048-7
NewsWeeder: Learning to Filter Netnews
resolves10.1007/978-1-4471-2099-5_1
A Sequential Algorithm for Training Text Classifiers
resolves10.1145/279943.279962
Combining labeled and unlabeled data with co-training
resolves10.1007/978-1-4471-2099-5_30
The Effect of Adding Relevance Information in a Relevance Feedback Environment
resolves10.1023/A:1007692713085
Text Classification from Labeled and Unlabeled Documents using EM
The 26 references without a DOI — listed, not checked
no DOI — not checkedEstimating the support of a high-dimensional distribution
no DOI — not checkedref30
no DOI — not checkedThe value of unlabeled data for classification problems
no DOI — not checkedCombining labeled and unlabeled data for multiclass text categorization
no DOI — not checkedEnhancing supervised learning with unlabeled data
no DOI — not checkedAutomatic capacity tuning of very large VC-dimension classifiers
no DOI — not checkedMaking large-scale SVM learning practical
no DOI — not checkedLearning with positive and unlabeled examples using weighted logistic regression
no DOI — not checkedLearning to classify text using positive and unlabeled data
no DOI — not checkedNote on the general case of the Bayes-Laplace formula for inductive or a posteriori probabilities
no DOI — not checkedUsing unlabeled data for text classification through addition of cluster parameters
no DOI — not checkedSupport vector machines: Training and applications
no DOI — not checkedA Semi-supervised support vector machines
no DOI — not checkedRelevant feedback in information retrieval
no DOI — not checkedExploiting relations among concepts to acquire weakly labeled training data
no DOI — not checkedPAC learning from positive statistical queries
no DOI — not checkedMaximum likelihood from incomplete data via the EM algorithm
no DOI — not checkedSemi-supervised clustering by seeding
no DOI — not checkedText classification from positive and unlabeled examples
no DOI — not checkedAthena: Mining-based interactive management of text databases
no DOI — not checkedPartially supervised classification of text documents
no DOI — not checkedA comparison of event models for naïve Bayes text classification
no DOI — not checkedOne-class SVMs for document classification
no DOI — not checkedLearning from the positive data
no DOI — not checkedCombining statistical learning with a knowledge-based approach - A case study in intensive care monitoring
no DOI — not checkedActive + semi-supervised learning = robust multiview learning
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