Who Cited It

Support vector machines for spam categorization

1999 · IEEE Transactions on Neural Networks · 1,480 citations · 6 from inside this corpus

Harris Drucker low, Donghui Wu, Vladimir Vapnik

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Support vector machines for spam categorization (1999)Support vector machines for s…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…C4.5: Programs for Machine Learning (1992)C4.5: Programs for Machine Le…Text categorization with Support Vector Machines: Learning with many relevant features (1998)Text categorization with Supp…Experiments with a new boosting algorithm (1996)Experiments with a new boosti…A Comparative Study on Feature Selection in Text Categorization (1997)A Comparative Study on Featur…Fast Effective Rule Induction (1995)Fast Effective Rule InductionMachine learning in automated text categorization (2002)Machine learning in automated…Semi-Supervised Learning (2006)Semi-Supervised LearningAn introduction to kernel-based learning algorithms (2001)An introduction to kernel-bas…Natural language processing: state of the art, current trends and challenges (2022)Natural language processing: …The text mining handbook: advanced approaches in analyzing unstructured data (2007)The text mining handbook: adv…Adaptive Computation and Machine Learning (2012)Adaptive Computation and Mach…
12 of 12 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
The Nature of Statistical Learning Theory199539,409
C4.5: Programs for Machine Learning199223,704
Text categorization with Support Vector Machines: Learning with many relevant features19988,044
Experiments with a new boosting algorithm19967,582
A Comparative Study on Feature Selection in Text Categorization19974,770
Fast Effective Rule Induction19953,810

What cites it, inside the corpus

PaperYearCited
Machine learning in automated text categorization20027,945
Semi-Supervised Learning20064,334
An introduction to kernel-based learning algorithms20013,498
Natural language processing: state of the art, current trends and challenges20221,807
The text mining handbook: advanced approaches in analyzing unstructured data20071,626
Adaptive Computation and Machine Learning20121,437

Links

DOI · OpenAlex record

Topics

Text and Document Classification TechnologiesComputer Science
Spam and Phishing DetectionComputer Science
Face and Expression RecognitionComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports27 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:58+00:00.

sha256 88a60cdbb94c6a13…