<?xml version="1.0" encoding="UTF-8"?>
<XML><RECORDS>
<RECORD>
	<REFERENCE_TYPE>31</REFERENCE_TYPE>
	<AUTHORS>
		<AUTHOR>J.A. Konstan</AUTHOR>
		<AUTHOR>N. Kapoor</AUTHOR>
		<AUTHOR>S.M. McNee</AUTHOR>
		<AUTHOR>J.T. Butler</AUTHOR>
	</AUTHORS>
	<YEAR>2005</YEAR>
	<TITLE>TechLens: Exploring the Use of Recommenders to Support Users of Digital Libraries</TITLE>
	<SECONDARY_TITLE>Coalition for Networked Information Fall 2005 Task Force Meeting</SECONDARY_TITLE>
	<PLACE_PUBLISHED>Phoenix, AZ</PLACE_PUBLISHED>
	<ABSTRACT>&lt;p&gt;The immense collection of valuable information in digital libraries is changing the way students and scholars access information. Indeed, just as library users are accessing libraries and research librarians remotely, the potential is increasing for value-added services that promise to help patrons use digital libraries in ever more powerful ways, moving beyond basic search to a new collection of awareness, field summary, and people-finding services. For the past four years we've been exploring means by which recommender systems technology&acirc;€”the technology used today by e-commerce vendors to help customers find products&acirc;€”can be adapted to serve the needs of students and scholars exploring scientific literature. The model shown here illustrates the types of data that can be used to fulfill a user's need. We have already demonstrated the success of some of the basic approaches&acirc;€”using citations, keywords, and abstracts to find works a researcher is unfamiliar with. Much work remains, however, as we explore ways to meet a more diverse set of information needs.&lt;/p&gt;</ABSTRACT>
	<URL>http://www.grouplens.org/papers/pdf/CNI-TechLens-Final.pdf</URL>
</RECORD>
</RECORDS></XML>
