Open information extraction from the web

831 indexed citations

Abstract

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About

This paper, published in 2007, received 831 indexed citations. Written by Michele Banko, Michael Cafarella, Stephen Soderland and Oren Etzioni covering the research area of Artificial Intelligence and Information Systems. It is primarily cited by scholars working on Artificial Intelligence (750 citations), Information Systems (300 citations) and Management Science and Operations Research (123 citations). Published in International Joint Conference on Artificial Intelligence.

In The Last Decade

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Countries where authors are citing Open information extraction from the web

Specialization
Citations

This map shows the geographic impact of Open information extraction from the web. 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 Open information extraction from the web with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Open information extraction from the web more than expected).

Fields of papers citing Open information extraction from the web

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Open information extraction from the web. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Open information extraction from the web.

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.

This paper is also available at doi.org/w5040592.

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