What Set of Documents to Present to an Analyst?

Richard Schwartz, John Makhoul, Lee Tarlin, Damianos Karakos

Abstract
We describe the human triage scenario envisioned in the Cross-Lingual Information Retrieval (CLIR) problem of the [REDUCT] Program. The overall goal is to maximize the quality of the set of documents that is given to a bilingual analyst, as measured by the AQWV score. The initial set of source documents that are retrieved by the CLIR system is summarized in English and presented to human judges who attempt to remove the irrelevant documents (false alarms); the resulting documents are then presented to the analyst. First, we describe the AQWV performance measure and show that, in our experience, if the acceptance threshold of the CLIR component has been optimized to maximize AQWV, the loss in AQWV due to false alarms is relatively constant across many conditions, which also limits the possible gain that can be achieved by any post filter (such as human judgments) that removes false alarms. Second, we analyze the likely benefits for the triage operation as a function of the initial CLIR AQWV score and the ability of the human judges to remove false alarms without removing relevant documents. Third, we demonstrate that we can increase the benefit for human judgments by combining the human judgment scores with the original document scores returned by the automatic CLIR system.
Anthology ID:
2020.clssts-1.9
Volume:
Proceedings of the workshop on Cross-Language Search and Summarization of Text and Speech (CLSSTS2020)
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Kathy McKeown, Douglas W. Oard, Elizabeth, Richard Schwartz
Venue:
CLSSTS
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
52–57
Language:
English
URL:
https://aclanthology.org/2020.clssts-1.9
DOI:
Bibkey:
Cite (ACL):
Richard Schwartz, John Makhoul, Lee Tarlin, and Damianos Karakos. 2020. What Set of Documents to Present to an Analyst?. In Proceedings of the workshop on Cross-Language Search and Summarization of Text and Speech (CLSSTS2020), pages 52–57, Marseille, France. European Language Resources Association.
Cite (Informal):
What Set of Documents to Present to an Analyst? (Schwartz et al., CLSSTS 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2020.clssts-1.9.pdf
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