This map shows the geographic impact of Ken Barker'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 Ken Barker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Barker more than expected).
This network shows the impact of papers produced by Ken Barker. 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 Ken Barker. The network helps show where Ken Barker may publish in the future.
Co-authorship network of co-authors of Ken Barker
This figure shows the co-authorship network connecting the top 25 collaborators of Ken Barker.
A scholar is included among the top collaborators of Ken Barker 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 Ken Barker. Ken Barker 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.
Glaß, Michael & Ken Barker. (2012). Focused Grounding for Markov Logic Networks.. The Florida AI Research Society.2 indexed citations
Barker, Ken, et al.. (2010). Building an end-to-end text reading system based on a packed representation. North American Chapter of the Association for Computational Linguistics. 10–14.1 indexed citations
4.
Barker, Ken, James Fan, Noah S. Friedland, et al.. (2007). Learning by reading: a prototype system, performance baseline and lessons learned. National Conference on Artificial Intelligence. 280–286.32 indexed citations
Yeh, Peter Z., Bruce Porter, & Ken Barker. (2006). A unified knowledge based approach for sense disambiguationm and semantic role labeling. National Conference on Artificial Intelligence. 305–310.9 indexed citations
Friedland, Noah S., Michael Witbrock, Jürgen Angele, et al.. (2004). Towards a quantitative, platform-independent analysis of knowledge systems. Principles of Knowledge Representation and Reasoning. 507–514.16 indexed citations
Barker, Ken, Vinay K. Chaudhri, Peter E. Clark, et al.. (2004). A question-answering system for AP chemistry: assessing KR&R technologies. Principles of Knowledge Representation and Reasoning. 488–497.24 indexed citations
11.
Barker, Ken, Jim Blythe, Vinay K. Chaudhri, et al.. (2003). A Knowledge Acquisition Tool for Course of Action Analysis. ScholarWorks@UMassAmherst (University of Massachusetts Amherst). 43–50.26 indexed citations
12.
Fan, James, Ken Barker, & Bruce Porter. (2003). The knowledge required to interpret noun compounds. International Joint Conference on Artificial Intelligence. 1483–1485.14 indexed citations
Barker, Ken, et al.. (2000). A formal perspective to specification of transaction systems. South African Computer Journal. 2000(26). 34–44.1 indexed citations
16.
Barker, Ken, et al.. (1999). Partial Re-execution: Reconciling Transactions to Increase Concurrency in Object-bases.. Parallel and Distributed Processing Techniques and Applications. 1469–1475.1 indexed citations
Barker, Ken & Stan Śzpakowicz. (1996). Review of Natural language processing for prolog programmers by Michael A. Covington. Prentice-Hall 1994.. Computational Linguistics. 22(1). 137–139.13 indexed citations
20.
Bukhres, Omran, et al.. (1995). The integration of database systems. 37–56.2 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.