Optimizing Semantic Coherence in Topic Models
- Journal
- ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
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doi.org/w15056282 →Countries where authors are citing Optimizing Semantic Coherence in Topic Models
This map shows the geographic impact of Optimizing Semantic Coherence in Topic Models. 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 Optimizing Semantic Coherence in Topic Models with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Optimizing Semantic Coherence in Topic Models more than expected).
Fields of papers citing Optimizing Semantic Coherence in Topic Models
This network shows the impact of Optimizing Semantic Coherence in Topic Models. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Optimizing Semantic Coherence in Topic Models.
About Optimizing Semantic Coherence in Topic Models
This paper, published in 2011, received 816 indexed citations . Written by David Mimno, Hanna Wallach, Edmund M. Talley and Andrew McCallum covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (519 citations), General Social Sciences (201 citations) and Sociology and Political Science (142 citations). Published in ScholarWorks@UMassAmherst (University of Massachusetts Amherst).
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/w15056282.