Demo Data from SIGIR 2026 / reviewers in the wild / expert
Karim Hussein
dblp:44/2710
· DBLP profile ↗
4ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3Artificial intelligence and machine learning · 2 · 1 first-author
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 |
Data integration and cleaning · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning › information mediation
mediated data access |
0.0 | 1 | 1997 | The COntext INterchange Mediator Prototype · SIGMOD Conference 1997 |
Data integration and cleaning › semantic integration
semantic conflict resolution |
0.0 | 1 | 1997 | The COntext INterchange Mediator Prototype · SIGMOD Conference 1997 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | CAIRO: a concurrent engineering meeting environment for virtual design teams
Feniosky Peña-Mora, Karim Hussein, Sanjeev Vadhavkar, Karim Benjamin |
Artif. Intell. Eng. | 2 |
| 1999 | A knowledge-based segmentation algorithm for enhanced recognition of handwritten courtesy amounts
Karim Hussein, Arun Agarwal, Amar Gupta, Patrick Shen-Pei Wang |
Pattern Recognit. | 1 |
| 1997 | The COntext INterchange Mediator PrototypeabstractThe Context Interchange strategy presents a novel approach for mediated data access in which semantic conflicts among heterogeneous systems are not identified a priori, but are detected and reconciled by a context mediator through comparison of contexts. This paper reports on the implementation of a Context Interchange Prototype which provides a concrete demonstration of the features and benefits of this integration strategy. Stéphane Bressan, Cheng Hian Goh, Kofi Fynn, Marta Jessica Jakobisiak, Karim Hussein, Henry B. Kon, Thomas Lee, Stuart E. Madnick, Tito Pena, Jessica Qu, Annie W. Shum, Michael D. Siegel |
SIGMOD Conference | 5 |
| 1995 | Detection of courtesy amount block on bank checksabstractThis paper discusses a technique for locating the courtesy amount block on bank checks. In the analysis and recognition process, connected components in the image are identified first. Then, strings are constructed on the basis of proximity and horizontal alignment of characters. Next, a set of rules and heuristics are applied to these strings to choose the correct one. The chosen string is only accepted if it passes a verification test, which includes an attempt to recognize the currency sign. A deterministic finite automaton system is then used for segmenting the handprinted courtesy amount. Finally, the separated components are passed on to a neural network based recognition system. Arun Agarwal, Len Granowetter, Karim Hussein, Amar Gupta, Patrick Shen-Pei Wang |
ICDAR | 3 |