Demo Data from VLDB 2026 / reviewers in the wild / expert
Jan Peter Patist
dblp:20/4400
· DBLP profile ↗
5ranked-venue papers
3as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 5 · 3 first-authorArtificial intelligence and machine learning · 3 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Web and social media mining · 44% Data mining · 44% Recommender systems · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining › time series analysis › change point detection
online change-point detection |
0.1 | 1 | 2008 | Online change detection in individual web user behaviour · WWW 2008 |
Web and social media mining › user behavior analysis
user behavior modeling |
0.1 | 1 | 2008 | Online change detection in individual web user behaviour · WWW 2008 |
Recommender systems
web personalization |
0.0 | 1 | 2008 | Online change detection in individual web user behaviour · WWW 2008 |
Methods — techniques the papers use, named apart from their topics
field study · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Supporting Customer Retention through Real-Time Monitoring of Individual Web Usage
Peter Hofgesang, Jan Peter Patist |
ADMA | 2 |
| 2008 | Maintaining the Maximum Normalized Mean and Applications in Data Stream Mining
Jan Peter Patist |
ADMA | 1 |
| 2008 | Fast Online Estimation of the Joint Probability Distribution
Jan Peter Patist |
PAKDD | 1 |
| 2008 | Online change detection in individual web user behaviourabstractBased on our field studies and consultations with field experts, we identified three main problems that are of key importance to online web personalization and customer relationship management: 1) detecting changes in individual behaviour, 2) reporting on user actions that may need special care, and 3) detecting changes in visitation frequency. Peter Hofgesang, Jan Peter Patist |
WWW | 2 |
| 2006 | A Fast Implementation of the EM Algorithm for Mixture of Multinomials
Jan Peter Patist |
ADMA | 1 |