Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,438

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Web mining research: a survey

Open access
Kosala, Raymond, Blockeel, Hendrik·2000·ACM SIGKDD Explorations Newsletter

Abstract

With the huge amount of information available online, the World Wide Web is a fertile area for data mining research.The Web mining research is at the cross road of research from several research communities, such as database, information retrieval, and within AI, especially the sub-areas of machine learning and natural language processing.However, there is a lot of confusions when comparing research eorts from dierent point of views.In this paper, we survey the research in the area of Web mining, point out some confusions regarded the usage of the term Web mining and suggest three Web mining categories.Then we situate some of the research with respect to these three categories.We also explore the connection between the Web mining categories and the related agent paradigm.For the survey, we focus on representation issues, on the process, on the learning algorithm, and on the application of the recent works as the criteria.We conclude the paper with some research issues.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/360402.360406

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 1,438

Metadata

Authors
Kosala, R., & Blockeel, H.
Venue
ACM SIGKDD Explorations Newsletter
Published
2000-06
Volume
2
Issue
1
Pages
1-15
ISSN
  • 1931-0145 (ISSN-L)
  • 1931-0153
OpenAlex
W1989993068
Cited by
1,438
References
1
FWCI
107.02
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Web mining research: a survey. https://app.cochat.ai/papers/10.1145/360402.360406
The paper
Kosala, R., & Blockeel, H. (2000). Web mining research: a survey. ACM SIGKDD Explorations Newsletter. https://doi.org/10.1145/360402.360406

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.