Abstract
This paper presents dynamic exploratory search technology for the analysis of scientific corpora. The unique dynamic features of the system allow users to analyze quantitative corpus statistics beyond document counts, and to switch between corpus exploration and corpus filtering. To demonstrate the innovation of our approach, we apply our technology to the IR Anthology, a comprehensive corpus of information retrieval publications. We showcase, among others, how to query for potential PC members and the “Salton number” of an author.
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CITATION STYLE
Gollub, T., Brockmeyer, J., Stein, B., & Potthast, M. (2023). Dynamic Exploratory Search for the Information Retrieval Anthology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13982 LNCS, pp. 242–247). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-28241-6_21
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