Bullseye: structured passage retrieval and document highlighting for scholarly search

Xi Zheng, Akanksha Bansal, Matthew Lease

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review


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 languageEnglish
Title of host publicationACSW 2017
Subtitle of host publicationProceedings of the Australasian Computer Science Week Multiconference
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450347686
Publication statusPublished - 2017
Externally publishedYes
EventAustralasian Computer Science Week 2017 - Geelong, Australia
Duration: 31 Jan 20173 Feb 2017


OtherAustralasian Computer Science Week 2017


  • Implementations of information systems
  • Focused Retrieval
  • Interactive Information Retrieval
  • Focused retrieval
  • Interactive information retrieval

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