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Ask Njit Library: A Natural Language Knowledge Base Self Service Solution

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Collection

2009 Annual Conference & Exposition

Location

Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009

ISSN

2153-5965

Conference Session

Using Information Technology to Create New Information Resources

Tagged Division

Engineering Libraries

Page Count

8

Page Numbers

14.234.1 - 14.234.8

Permanent URL

https://peer.asee.org/5560

Download Count

59

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Paper Authors

biography

Haymwantee Singh New Jersey Institute of Technology

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Haymwantee P. Singh,
Technical Reference Librarian,
Robert W. Van Houten Library,
New Jersey Institute of Technology,
singhh@njit.edu

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biography

Richard Sweeney New Jersey Institute of Technology

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Richard T. Sweeney,
University Librarian,
Robert W. Van Houten Library,
New Jersey Institute of Technology,
richard.sweeney@njit.edu

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

ASK NJIT LIBRARY: A Natural Language Knowledge Base Self-Service Solution

Abstract

As library websites proliferated over the years, librarians have developed ways of enhancing users’ experiences as they navigate a vast ocean of valuable library resources. Librarians have also been creative in handling high volume inquiries via online help desk service that include FAQ, chat service and email reference that have some 24/7 elements. These services are necessary but still not sufficient for today’s impatient library users looking for instant gratification. This paper addresses a 24/7 website self-service experience that makes it easy for website visitors to type a question in natural language and get one right answer. It will be demonstrated how ready reference questions can now be answered through a natural language knowledgebase powered by IntelliResponse that can be updated every time a user asks a new but important question. There are many benefits of this empowering program such as reduction of email volume, phone calls and chat sessions and reduced navigation linked with website Q&A or FAQ solutions. The quality of end user experience is measured objectively via system generated reports. Potential exists for institutions to collaborate and build such knowledgebases more efficiently and for development of self-learning tools.

Introduction

Ask the library, ask the registrar, ask the IT help desk, ask the calculus professor, ask the XXXXXX, and receive an immediate, consistent and accurate online answer to your question 24x7, 365 days per year. Imagine that each time a librarian is asked a question, s/he may not have to answer the same or similar question in the future. Imagine that students can ask questions online and are able to receive their professor’s answers even while that professor is off doing his or her research, on sabbatical, or just on down time. A natural language knowledge management system could be the solution. An integral component of knowledge management systems, a knowledge base, is used to optimize information collection, organization, and retrieval for an organization, or for the general public [1]. Functions of a natural language knowledge base make it possible to answer specific questions that are likely to be asked repeatedly by other users but perhaps in a slightly different manner. Natural language knowledge bases currently used by some academic departments such as libraries, registrars, and information technology may also be exploited by individual faculty and academic degree programs. They too must answer the same questions that are asked repeatedly by different students in different sections or even over different semesters.

S.R. Ranganathan (1892-1972), renowned international librarian, proposed five laws of library science. His fourth law states “save the time of the reader”[2]. On Ranganathan’s fourth law, Noruzi explains that in order to save the time of the user, web sites need to be designed with an efficiency factor that will enable users to find what they are looking for quickly and accurately, as well as to explore the vast collection of information available that could potentially be useful.[3] According to Steckel, this law has both a front-end component (make sure people quickly find what they are looking for) and a back-end component (make sure our data is structured in a way that information can be retrieved quickly) [4]. In short, the best way to save

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