Michael Cafarella
About
In The Last Decade
Michael Cafarella
94 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 3.3k
- Information Systems 2.0k
- Management Science and Operations Research 1.1k
- Computer Networks and Communications 992
- Signal Processing 623
Countries citing papers authored by Michael Cafarella
This map shows the geographic impact of Michael Cafarella'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 Michael Cafarella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Cafarella more than expected).
Fields of papers citing papers by Michael Cafarella
This network shows the impact of papers produced by Michael Cafarella. 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 Michael Cafarella. The network helps show where Michael Cafarella may publish in the future.
Co-authorship network of co-authors of Michael Cafarella
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Cafarella. A scholar is included among the top collaborators of Michael Cafarella based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Cafarella. Michael Cafarella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | Constructing Expressive Relational Queries with Dual-Specification Synthesis. | 2 |
| 6 | 3 | |
| 7 | 38 | |
| 8 | Runtime Support for Human-in-the-Loop Feature Engineering System. | 4 |
| 9 | 7 | |
| 10 | Brainwash: A data system for feature engineering | 68 |
| 11 | Ringtail: Feature Selection For Easier Nowcasting. | 7 |
| 12 | Extracting and Querying a Comprehensive Web Database. | 22 |
| 13 | Uncovering the Relational Web | 91 |
| 14 | Structured querying of web text | 21 |
| 15 | Open information extraction from the web breakdown → | 831 |
| 16 | Navigating Extracted Data with Schema Discovery. | 15 |
| 17 | Structured Querying of Web Text Data: A Technical Challenge. | 39 |
| 18 | Machine reading | 68 |
| 19 | Ontology-driven information extraction with OntoSyphon | 10 |
| 20 | Methods for domain-independent information extraction from the web: an experimental comparison | 73 |
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.