Countries citing papers authored by Daniel P. Miranker
Since
Specialization
Citations
This map shows the geographic impact of Daniel P. Miranker'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 Daniel P. Miranker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel P. Miranker more than expected).
Fields of papers citing papers by Daniel P. Miranker
This network shows the impact of papers produced by Daniel P. Miranker. 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 Daniel P. Miranker. The network helps show where Daniel P. Miranker may publish in the future.
Co-authorship network of co-authors of Daniel P. Miranker
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel P. Miranker.
A scholar is included among the top collaborators of Daniel P. Miranker 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 Daniel P. Miranker. Daniel P. Miranker is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Sequeda, Juan & Daniel P. Miranker. (2015). Ultrawrap mapper: A semi-automatic relational database to RDF (RDB2RDF) mapping tool. International Semantic Web Conference. 1486.7 indexed citations
2.
Kejriwal, Mayank & Daniel P. Miranker. (2014). A two-step blocking scheme learner for scalable link discovery. 1317. 49–60.9 indexed citations
3.
Kejriwal, Mayank & Daniel P. Miranker. (2014). On linking heterogeneous dataset collections. International Semantic Web Conference. 1272. 217–220.3 indexed citations
Sequeda, Juan, et al.. (2008). A bootstrapping architecture for integration of relational databases to the semantic web. International Semantic Web Conference. 30–31.1 indexed citations
Miranker, Daniel P., et al.. (1996). An Overview of the VenusDB Active Multidatabase System.. 108–117.2 indexed citations
13.
Bayardo, Roberto J. & Daniel P. Miranker. (1996). A complexity analysis of space-bounded learning algorithms for the constraint satisfaction problem. National Conference on Artificial Intelligence. 298–304.52 indexed citations
14.
Bayardo, Roberto J. & Daniel P. Miranker. (1995). On the space-time trade-off in solving constraint satisfaction problems. International Joint Conference on Artificial Intelligence. 558–562.27 indexed citations
Brant, David A., et al.. (1991). Effects of Database Size on Rule System Performance: Five Case Studies. Very Large Data Bases. 287–296.33 indexed citations
17.
Miranker, Daniel P., et al.. (1990). Parallelizing Compilation of Rule-Based Programs.. Proceedings of the International Conference on Parallel Processing. 247–251.13 indexed citations
18.
Miranker, Daniel P., et al.. (1990). On the performance of lazy matching in production systems. National Conference on Artificial Intelligence. 685–692.56 indexed citations
19.
Miranker, Daniel P.. (1987). TREAT: a better match algorithm for AI production systems. National Conference on Artificial Intelligence. 42–47.150 indexed citations
20.
Miranker, Daniel P.. (1987). TREAT: A Better Match Algorithm for AI Production System Matching.. National Conference on Artificial Intelligence. 42–47.19 indexed citations
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.