CLSep 18, 2023

Hierarchy Builder: Organizing Textual Spans into a Hierarchy to Facilitate Navigation

AI2
arXiv:2309.10057v1222 citationsh-index: 52
Originality Synthesis-oriented
AI Analysis

This addresses the challenge for users needing to manage and explore extensive extracted data, though it appears incremental as it builds on existing grouping and hierarchy methods.

The paper tackles the problem of organizing large sets of extracted text strings into a hierarchical structure to improve user navigation and overview in exploratory settings, with results applied to medical information extraction.

Information extraction systems often produce hundreds to thousands of strings on a specific topic. We present a method that facilitates better consumption of these strings, in an exploratory setting in which a user wants to both get a broad overview of what's available, and a chance to dive deeper on some aspects. The system works by grouping similar items together and arranging the remaining items into a hierarchical navigable DAG structure. We apply the method to medical information extraction.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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