recommendation and the library
DESCRIPTION
Services recommending books = BibTip, LibraryThing, University of Huddersfield borrowing recommendations, and articles – bX from Ex Libris, PubMed, Synthese (CISTI) now exist in the academic context. JISC in the UK is sponsoring a major project, MOSAIC: “Making Our Shared Activity Information Count.” This session will provide an overview of these recommendation systems, describe their different approaches to data mining, and discuss their role in improving information retrieval and user experience in a now nearly fully online scholarly information world.TRANSCRIPT
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Recommendations and the Library
Nettie Lagace
Product Manager, Ex Libris
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Copyright Statement
All of the information and material inclusive of text, images, logos, product names is either the
property of, or used with permission by Ex Libris Ltd. The information may not be distributed,
modified, displayed, reproduced – in whole or in part – without the prior written permission of
Ex Libris Ltd.
TRADEMARKS
Ex Libris, the Ex Libris logo, Aleph, SFX, SFXIT, MetaLib, DigiTool, Verde, Primo, Voyager,
MetaSearch, MetaIndex, bX and other Ex Libris products and services referenced herein are
trademarks of Ex Libris, and may be registered in certain jurisdictions. All other product names,
company names, marks and logos referenced may be trademarks of their respective owners.
DISCLAIMER
The information contained in this document is compiled from various sources and provided on an
"AS IS" basis for general information purposes only without any representations, conditions or
warranties whether express or implied, including any implied warranties of satisfactory quality,
completeness, accuracy or fitness for a particular purpose.
Ex Libris, its subsidiaries and related corporations ("Ex Libris Group") disclaim any and all liability
for all use of this information, including losses, damages, claims or expenses any person may
incur as a result of the use of this information, even if advised of the possibility of such loss or
damage.
© Ex Libris Ltd., 2009
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Agenda
• What will the future be like?
• Recommender systems in general
• “In the Wild”
• New scholarly environments
• Article recommenders
• Interfaces
• Contributions
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http://www.idealog.com/stay-ahead-of-the-shift-what-publishers-can-do-to-flourish-in-a-community-centric-web-world
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Recommender Systems
http://en.wikipedia.org/wiki/Recommendation_systems
Recommender systems form a specific type of information filtering (IF) technique that attempts to present information items (movies, music, books, news, images, web pages, etc.) that are likely of interest to the user.
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Library Book Recommendations
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http://library.hud.ac.uk/data/usagedata/
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• Greater focus on content users create and choices & preferences they make
• User contribution increasingly important
• Contributed explicitly by individuals
• The Web is multi-directional
Changes in Scholarly Communication
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• Greater focus on content users create and choices & preferences they make
• User contribution increasingly important
• Contributed explicitly by individuals
• The Web is multi-directional
• Implicitly - usage data captured by the system (‘clickstreams’)
Changes in Scholarly Communication
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There is a need
• Information overload calls for new tools that assist users in finding relevant information
• Useful in the context of:
• learning
• exploring new fields of interest
• inter-disciplinary work
• specific information needs that are outside one’s field of expertise
• Search is NOT the only way to find…
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Scholarly Recommender Service
Need to:
• Focus on scholarly materials – particularly
articles (core unit of use)
• Be based on structural analysis of usage and
not just based on popularity
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CiteULike Recommendations
/embedded video removed from PPT – see http://www.youtube.com/watch?v=ium2fS1LW5w
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What is bX?
• A service which taps into the power of the networked scholarly community to generate recommendations based on article usage
• Based on data mining and structural analysis of aggregated usage data, across libraries and scholarly information environments
• Massive repository of user data -growing
• Derives from research done at Los Alamos National Laboratory by Johan Bollen and Herbert Van de Sompel
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Interest in usage-based measures
• COUNTER – www.projectcounter.org
• SUSHI - www.niso.org/workrooms/sushi
• JISC MOSAIC – www.sero.co.uk/jisc-mosaic.html
• Metrics for scholarly evaluation:
• UKSG Usage Factors project
- uksg.org/usagefactors
• Project MESUR - www.mesur.org
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Implicit user contribution
• Circulation data
• Clickstreams, recording a search process
• Actions
• Item viewed
• Item downloaded
• Item sent
• Item bookmarked
• Item printed
• Item stored
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Potential uses of implicit contribution
• Collection development
• Evaluation
• Trend analysis
• Relevance ranking
• Recommendations
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bX Demo
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bX Demo
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bX Demo
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bX Demo
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bX Demo
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Link resolver usage logs
• A good basis:
• Represent users’ information-seeking paths in a standardized way
• Are across information providers
• Are across institutions
• There are a lot of them
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Citation databases
Link Resolver
GoogleScholar
E-journal publisher
site
E-journal publisher
site
A&I databases
Library interface
E-Book publisher
site
Document Delivery
OpenURL OpenURL
OpenURL
OpenURL
Link resolver usage paths
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Built on OpenURL
• Usage data –OpenURL context objects-- is harvested from link resolver logs through OAI-PMH
• Build a (very large) aggregate of usage data
• Mine the aggregate to derive scholarly recommender services: a structure describing relationships between scholarly materials is created
• bX receives OpenURL requests
• A list of recommended materials is generated per request
• open interface - accessible via API
• viewable via SFX menu, other discovery interfaces
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Bollen J, Van de Sompel H, Hagberg A, Bettencourt L, Chute R, et al. (2009) Clickstream Data Yields High-Resolution Maps of Science. PLoS ONE 4(3): e4803. doi:10.1371/journal.pone.0004803
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bX Research
http://pu
blic.lanl.g
ov/herbe
rtv/
papers/jc
dl06_acce
pted_versi
on.pdf
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More about the interaction with bX
• Request to bX is sent through an API
• Results are returned as
• XML (default)
• Text
• ATOM
• RSS
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Recommendations in Primo V3
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Benefits of bX Contribution
• Ongoing analysis of SFX usage data created by library users
• Continual improvement of recommendations
• Cooperation with other research library sites – on a grand scale
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What do people say?“JSTOR meets Amazon!?”
- ELUNA twitterer
“On May 5, Ex Libris rolled out the shiny new fabulousness that is bX. … (turns) the Services Menu into a point-of-need discovery tool. I think this is awesome. ”
- Jamene Brooks-Kieffer, Kansas State Univ.
“I found exactly what I wanted. I've already found even more relevant articles in 10 minutes than I've found in the last 10 months using more traditional methods of research.”
- Ph.D. student, Arizona State University
“I’m always trying to find new connections between biological systems. This looks like a really useful tool for this discovery. I’m interested in seeing others’ connections. An unknown system can link to one which is well-studied.”
- Laboratory director, University of Ottawa Heart Institute
“One thing I've noticed and got a few comments about is that the increase in amount of recommendations has been noticeable from last summer to now. Now it's much easier (to find recommendations). The recommendations seem … relevant”
- Systems librarian, FinELib
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“The Web, they say, is leaving the era of search and entering one of discovery. What's the difference? Search is what you do when you're looking for something. Discovery is when something wonderful that you didn't know existed, or didn't know how to ask for, finds you.“
Jeffrey M. O’Brien, "The race to create a 'smart' Google“http://money.cnn.com/magazines/fortune/fortune_archive/2006/11/27/8394347/