On the public citation graph

WEBKDD 2001 — Mining Web Log Data Across All Customers Touch Points

0 signed · 36 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/3-540-45640-6_1openalex-snapshot
Detail and Context in Web Usage Mining: Coarsening and Visualizing Sequences
inferredcites →https://doi.org/10.1007/3-540-45640-6_2openalex-snapshot
A Customer Purchase Incidence Model Applied to Recommender Services
inferredcites →https://doi.org/10.1007/3-540-45640-6_3openalex-snapshot
A Cube Model and Cluster Analysis for Web Access Sessions
inferredcites →https://doi.org/10.1007/3-540-45640-6_4openalex-snapshot
Exploiting Web Log Mining for Web Cache Enhancement
inferredcites →https://doi.org/10.1007/3-540-45640-6_5openalex-snapshot
LOGML: Log Markup Language for Web Usage Mining
inferredcites →https://doi.org/10.1007/3-540-45640-6_6openalex-snapshot
A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking
inferredcites →https://doi.org/10.1007/3-540-45640-6_7openalex-snapshot
Mining Indirect Associations in Web Data

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.3199332openalex-extracted
Semantic Web Mining. State of the Art and Future Directions
inferred← citeshttps://doi.org/10.1007/11424918_19openalex-snapshot
Integrating Web Content Clustering into Web Log Association Rule Mining
inferred← citeshttps://doi.org/10.1007/11577935_10openalex-snapshot
Discovering Interesting Navigations on a Web Site Using SAM I
inferred← citeshttps://doi.org/10.1007/11615576_14openalex-snapshot
Employing Inductive Databases in Concrete Applications
inferred← citeshttps://doi.org/10.1007/11899402_1openalex-snapshot
Mining Temporally Changing Web Usage Graphs
inferred← citeshttps://doi.org/10.1007/978-3-319-09156-3_22openalex-snapshot
Evaluation of Web Session Cluster Quality Based on Access-Time Dissimilarity and Evolutionary Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-319-09156-3_3openalex-snapshot
Weighted-Frequent Itemset Refinement Methodology (W-FIRM) of Usage Clusters
inferred← citeshttps://doi.org/10.1007/978-3-540-24775-3_14openalex-snapshot
An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams
inferred← citeshttps://doi.org/10.1007/978-3-540-30207-0_1openalex-snapshot
ART Based Predictive Caching System for XML P2P Database
inferred← citeshttps://doi.org/10.1007/978-3-540-30214-8_20openalex-snapshot
Product Recommendation in e-Commerce Using Direct and Indirect Confidence for Historical User Sessions
inferred← citeshttps://doi.org/10.1007/978-3-540-30564-4_18openalex-snapshot
Collision Attack and Pseudorandomness of Reduced-Round Camellia
inferred← citeshttps://doi.org/10.1007/978-3-540-30577-4_25openalex-snapshot
Adjustment of Indirect Association Rules for the Web
inferred← citeshttps://doi.org/10.1007/978-3-540-45175-4_12openalex-snapshot
Others Also Use: A Robust Recommender System for Scientific Libraries
inferred← citeshttps://doi.org/10.1007/978-3-540-73597-7_10openalex-snapshot
A Hybrid Cache and Prefetch Mechanism for Scientific Literature Search Engines
inferred← citeshttps://doi.org/10.1007/978-3-540-73871-8_27openalex-snapshot
A Consensus Recommender for Web Users
inferred← citeshttps://doi.org/10.1007/978-3-540-74951-6_2openalex-snapshot
Combining Web Usage Mining and XML Mining in a Real Case Study
inferred← citeshttps://doi.org/10.1007/978-3-540-74951-6_5openalex-snapshot
Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles
inferred← citeshttps://doi.org/10.1007/978-3-540-75530-2_22openalex-snapshot
A Web-Page Usage Prediction Scheme Using Weighted Suffix Trees
inferred← citeshttps://doi.org/10.1007/978-3-642-02794-9_1openalex-snapshot
Innovations in Web Personalization
inferred← citeshttps://doi.org/10.1007/978-3-642-14171-3_38openalex-snapshot
Enhancing Web Caching Using Web Usage Mining Techniques
inferred← citeshttps://doi.org/10.1007/978-3-642-20573-6_4openalex-snapshot
Mining Indirect Association Between Itemsets
inferred← citeshttps://doi.org/10.1007/978-3-642-25725-4_33openalex-snapshot
Investigative Behavior Profiling with One Class SVM for Computer Forensics
inferred← citeshttps://doi.org/10.1007/978-3-642-25856-5_30openalex-snapshot
XML Document Clustering Using Structure-Preserving Flat Representation of XML Content and Structure
inferred← citeshttps://doi.org/10.1007/978-3-642-33326-2_4openalex-snapshot
Web Usage Mining: Discovering Usage Patterns for Web Applications
inferred← citeshttps://doi.org/10.1007/978-3-642-41278-3_42openalex-snapshot
Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism
inferred← citeshttps://doi.org/10.1016/j.websem.2006.02.001openalex-snapshot
Semantic Web Mining
inferred← citeshttps://doi.org/10.1145/1046456.1046484openalex-snapshot
WebKDD 2004
inferred← citeshttps://doi.org/10.1145/956750.956791openalex-snapshot
Golden Path Analyzer
inferred← citeshttps://doi.org/10.13005/ojcst/09.03.03openalex-snapshot
An Introduction to Data Mining Applied to Health-Oriented Databases
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.