Dawid Weiss

1.4k citations
14 papers · 551 indexed · h-index 8

Dawid Weiss

14 papers receiving 481 citations

Peers

Dawid Weiss
Comparison fields: 5 of 70
  • Information Systems 326
  • Computer Science Applications 72
  • Artificial Intelligence 325
  • Signal Processing 100
  • Computer Vision and Pattern Recognition 73
Replace Maheedhar Kolla with:
Maheedhar Kolla Canada
Peter Anick United States
Hema Raghavan United States
Kenji Hatano Japan
Dmitry Pavlov United States
Marta Rey-López Spain
Abdallah Yousif China
Doug Cutting United States
Idan Szpektor Israel
Petros Venetis United States
Dawid Weiss relative to Maheedhar Kolla Canada Maheedhar Kolla's profile →
Citations per field
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Citations per year

Countries citing papers authored by Dawid Weiss

Since Specialization
Citations

This map shows the geographic impact of Dawid Weiss's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dawid Weiss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawid Weiss more than expected).

Fields of papers citing papers by Dawid Weiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dawid Weiss. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dawid Weiss. The network helps show where Dawid Weiss may publish in the future.

Co-authorship network

The 11 scholars most cited alongside Dawid Weiss, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dawid Weiss Line = papers co-authored together Dawid Weiss links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 200920
2 2009232
3
Carrot2: Making Sense of the Haystack.
20085
4 20081
5 200851
6
Fighting Web Spam
20081
7
Extending k-means with the description comes first approach
20072
8 20078
9
Clustering Search Results with Carrot 2
20072
10
A Large Crawl and Quantitative Analysis of Open Source Projects Hosted on SourceForge
200518
11 2005164
12
Measuring success of open source projects using web search engines
200528
13
Quantitative analysis of open source projects on SourceForge
200517
14
Introduction to Search Results Clustering
20022

About Dawid Weiss

Dawid Weiss is a scholar working on Signal Processing, Computer Science Applications and Information Systems, having authored 14 papers that have together received 551 indexed citations. Recurring topics across this work include Data Management and Algorithms (6 papers), Web Data Mining and Analysis (4 papers), Open Source Software Innovations (3 papers), Algorithms and Data Compression (3 papers), Data Mining Algorithms and Applications (3 papers), Spam and Phishing Detection (2 papers), Software Engineering Research (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Information Systems (326 citations), Computer Science Applications (72 citations) and Artificial Intelligence (325 citations). Dawid Weiss has collaborated with scholars based in Poland, Italy and Canada. Frequent co-authors include Stanisław Osiński, Claudio Carpineto, Giovanni Romano, Marcin Sydow, Jakub Piskorski, Jerzy Stefanowski, Wojtek Michalowski, Ken Farion, Dympna O’Sullivan and Szymon Wilk. Their work appears in journals such as ACM Computing Surveys, IEEE Intelligent Systems and Methods of Information in Medicine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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