Library Innovation Lab: Difference between revisions
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=About= | =About= | ||
The Library Innovation Lab is a small group within the Harvard University Library system that implements in software ideas about how libraries can be ever more valuable. We hack libraries...in the good sense of discovering and delivering more capability and value. Find more information on the Library Innovation Lab here: [http://librarylab.law.harvard.edu/ librarylab.law.harvard.edu] | The Library Innovation Lab is a small group within the Harvard University Library system that implements in software ideas about how libraries can be ever more valuable. We hack libraries...in the good sense of discovering and delivering more capability and value. Find more information on the Library Innovation Lab here: [http://librarylab.law.harvard.edu/ librarylab.law.harvard.edu] | ||
==Long Tail Browser (Library Interestingness)== | ==Long Tail Browser (Library Interestingness)== |
Latest revision as of 13:55, 20 March 2012
About
The Library Innovation Lab is a small group within the Harvard University Library system that implements in software ideas about how libraries can be ever more valuable. We hack libraries...in the good sense of discovering and delivering more capability and value. Find more information on the Library Innovation Lab here: librarylab.law.harvard.edu
Long Tail Browser (Library Interestingness)
The Harvard Library system has available a rich set of metadata about the 12 million books and other items in its collection. This includes "event" data such as circulation records broken down by school and borrower type, which works have been called back from loans early, items on reserve, items ordered by the Harvard Coop, and more. It isn't hard to come up with useful ranking algorithms that employ this data. It is more challenging to devise interestingness algorithms. And it is more challenging still to devise algorithms that will find interesting and relevant works in the long tail. We are therefore proposing a project that explores using every scrap of metadata to provide search results based on interestingness, and that discerns interestingness in items in the long tail.
Mentor: mphillips@law.harvard.edu
General Questions: berkmancenterharvard@gmail.com