Faceted Search of Structured Text Dataset with Narrative Fields

Lisham L. Singh, Srini Ramaswamy, and Mariofanna Milanova

Keywords

Faceted search, semantic text mining, decision tree

Abstract

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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