Abstract
We deal with the task of generating a query that retrieves a given set of documents. In its abstract form, this can be seen as a “compression” of the document set to a short query. But the task also has a real-world application: cluster labeling (e.g., for faceted search). Our solution to cluster labeling is the usage of queries that approximately retrieve a cluster’s documents. To be generalizable, our approach does not require access to a search index but only a public interface like an API. This way, our approach can also be implemented at client side.
In an experimental evaluation, a basic version of our approach using a simple retrieval model is on par with standard cluster labeling techniques. A further user study reveals that queries as labels are often preferred when they are not too long.
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Notes
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Hagen, M., Michel, M., Stein, B. (2015). What was the Query? Generating Queries for Document Sets with Applications in Cluster Labeling. In: Biemann, C., Handschuh, S., Freitas, A., Meziane, F., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2015. Lecture Notes in Computer Science(), vol 9103. Springer, Cham. https://doi.org/10.1007/978-3-319-19581-0_10
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