Subject-Based Virtual Reference: Avenues, Attitudes, and Vehicles for Success

Sponsored by SIG STI

Julie Arnold [Moderator] Engineering and Physical Sciences Library, University of Maryland, Mathematics Building, Room 1403, College Park, MD 20742. Email: jh276@umail.umd.edu

Jiangping Chen Center for Natural Language Processing, School of Information Studies, Syracuse University, 4-206 CST, Syracuse University, Syracuse NY 13244. Email: jchen06@syr.edu

Jennifer Edelman Science Library, Massachusetts Institute of Technology, Bldg. 14S-I 34, 77 Massachusetts Ave., Cambridge, MA 021 39-4307. Email: jedelman@mit.edu

Jeffrey Pomerantz School of Information and Library Science, University of North Carolina at Chapel Hill, 100 Manning Hall, Chapel Hill, NC 27599-3360. Email: pomerantz@ils.unc.edu

Diane Kresh Library of Congress, Washington, DC, 20540. Email: dkre@loc.gov

This panel will discuss research and opportunities in the area of subject-based virtual reference. With larger numbers of users utilizing the internet for reference, and many libraries offering virtual reference desks, there are many opportunities for success and some potential problems. Today's internet user expects "instant answers," which may not be possible unless they can tap into some subject expertise, or expert system. In this panel, three different avenues of subject-based virtual reference will be discussed. Presentations will focus on the following topics: 1) the potential of multi-library systems and consortia offering virtual reference services staffed by subject specialists in a particular area of expertise; 2) a discussion of progress in automatic question answering systems, and a strategy to take advantage of automatic answering systems and subject specialists to best satisfy users' needs 3) question

categorization and automatic routing; and 4) automated question routing based on fielded data. Specific topics are summarized as follows.

Jiangping Chen Both digital reference systems using subject specialists

and automatic question answering (QA) systems have limitations in terms of providing prompt, accurate QA service to the users. Current digital reference systems using subject specialists have the potential to handle complex questions. However, they may not provide the answers right away. Automatic QA systems are capable of providmg answers to simple, fact-based questions promptly, but they are ineffective at interpreting complex questions. An ideal strategy is to take advantage of these two types of systems to best satisfy users' information need. In th is presentation, we will introduce current progress of automatic question answering systems to identify the challenges and opportunities for virtual reference systems and research. We will then focus on the discussion of how subject specialists can work together with an automatic QA

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system to provide prompt, accurate answers to users questions and help the users to achieve their goals. A funded research project is taken as an example to illustrate the role of the subject specialists and the QA system in helping undergraduate students majoring in aeronautical engineering to learn and to conduct collaborative work.

Jennifer Edelman There are many difficulties inherent in staffing a multi-

library virtual reference service with subject specialist librarians. One alternative is to create subject-based virtual reference consortia. The discussion will focus on the practical issues surrounding the use of subject specialists to staff virtual reference services in multi-library systems and consortia. The discussion will offer a model of this service and discuss potential challenges and successes in this type of service.

Diane Kresh QuestionPoint is an online reference management tool

and a global network of librarians exchanging reference queries and building a global knowledgebase. QuestionPoint participation is based on profiles. Each member builds a profile. Profiled information includes subject (based on LC class), geographic subject, formats, education levels served, open hours, weekly quota, languages served, etc. When a librarian wishes to send a question to the global reference network the librarian “codes” the question in regard to the above mentioned elements. The question is sent to the network where a two- step process is employed. The first step is exclusionary and all profiles not supporting the defined subject‘geographc areas are eliminated, as are those who have met their weekly quota, are not open during the life of the question, or don’t serve the education level. Step two utilizes a best-

fit matching algorithm wherein all remaining members are scored based on a series of weights and values. Question metadata meets profile metadata and a match is made. Exploration is ongoing on ways to incorporate linguistic analysis into this process. The technology is beginning to mature and is able to map to established taxonomies like LC class and Dewey making the coding and process more intuitive.

Jeffery Pomerantz A review of the literature was conducted

the profiling

in fields in which questions are of central importance: specifically, the fields of desk and digital reference, question answering, and linguistics. This review reveals four levels of linguistic analysis according to which questions have been classified in these fields, and taxonomies of questions at each of these levels. The levels of linguistic analysis are the syntactic, semantic, discourse, and pragmatic levels of linguistic analysis. The taxonomies of questions at these levels of analysis are the wh- word in the question, the subject of the question, the function of the expected answer, and the form of the expected answer, respectively. A study is described that analyzed digital reference triage - the assignment of a question to a reference or subject expert ‘answerer’ - in order to discover how a question’s type affects its triage assignment. A moderately strong correlation was discovered between question type and triage action in digital reference services of all types. The argument is made that in developing systems for performing machine- assisted triage on questions received by digital reference services, no one of these taxonomies describes a question sufficiently, but that all four taxonomies should be employed as a faceted scheme.

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