Faceted Search of Structured Text Dataset with Narrative Fields

Lisham L. Singh, Srini Ramaswamy, and Mariofanna Milanova


Faceted search, semantic text mining, decision tree


In this paper, we present a faceted search on a dataset of reports having same structure, which consists of both non-narrative and narrative fields. Our approach exploits prop- erties associated with the dataset especially non-narrative fields, and at the same time gets enjoys full semantic lever-ages of the terms present under the narrative fields. We use some greedy algorithms for finding facets and constructing of their hierarchies, which are the core components in de- signing a faceted search application, for both narrative as well as non-narrative field values. These components are dynamically computed depending on the user query. We evaluated our approach on MAUDE dataset.

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