Finding Needles in Document Haystacks: Augmenting Serendipitous Claim Retrieval Workflows

要旨

Preliminary exploration of vast text corpora for generating and validating hypotheses, typical in academic inquiry, requires flexible navigation and rapid validation of claims. Navigating the corpus by titles, summaries, and abstracts might neglect information, whereas identifying the relevant context-specific claims through in-depth reading is unfeasible with rapidly increasing publication numbers. Our paper identifies three typical user pathways for hypothesis exploration and operationalizes sentence-based retrieval combined with effective contextualization and provenance tracking in a unified workflow. We contribute an interface that augments the previously laborious tasks of claim identification and consistency checking using NLP techniques while balancing user control and serendipity. Use cases, expert interviews, and a user study with 10 participants demonstrate how the proposed workflow enables users to traverse literature corpora in novel and efficient ways. For the evaluation, we instantiate the tool within two independent domains, providing novel insights into the analysis of political discourse and medical research.

著者
Moritz Dück
ETH Zurich, Zuerich, Switzerland
Steffen Holter
ETH Zurich, Zurich, Switzerland
Robin Shing Moon. Chan
ETH Zürich, Zürich, Switzerland
Rita Sevastjanova
ETH Zurich, Zurich, Switzerland
Mennatallah El-Assady
ETH Zürich, Zürich, Switzerland
DOI

10.1145/3706598.3713715

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713715

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Storytelling and Sense-Making

G302
6 件の発表
2025-04-28 20:10:00
2025-04-28 21:40:00
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