Abstract
We present the Bullseye system for scholarly search. Given a collection of research papers, Bullseye: 1) identifies relevant passages using any off-the-shelf algorithm; 2) automatically detects document structure and restricts retrieved passages to user-specified sections; and 3) highlights those passages for each PDF document retrieved. We evaluate Bullseye with regard to three aspects: system effectiveness, user effectiveness, and user effort. In a system-blind evaluation, users were asked to compare passage retrieval using Bullseye vs. a baseline which ignores document structure, in regard to four types of graded assessments. Results show modest improvement in system effectiveness while both user effectiveness and user effort show substantial improvement. Users also report very strong demand for passage highlighting in scholarly search across both systems considered.
Original language | English |
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Title of host publication | ACSW 2017 |
Subtitle of host publication | Proceedings of the Australasian Computer Science Week Multiconference |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery |
Number of pages | 4 |
ISBN (Electronic) | 9781450347686 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Event | Australasian Computer Science Week 2017 - Geelong, Australia Duration: 31 Jan 2017 → 3 Feb 2017 |
Other
Other | Australasian Computer Science Week 2017 |
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Country/Territory | Australia |
City | Geelong |
Period | 31/01/17 → 3/02/17 |
Keywords
- Implementations of information systems
- Focused Retrieval
- Interactive Information Retrieval
- Focused retrieval
- Interactive information retrieval