Automatic Recommendation of Astronomy Literature

Details Automatic Recommendation of Astronomy Literature Automatic Recommendation of Astronomy Literature

Jan 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21711608h&link_type=abstract

American Astronomical Society, AAS Meeting #217, #116.08; Bulletin of the American Astronomical Society, Vol. 43, 2011

Astronomy and Astrophysics

Astrophysics

Scientific paper

Authors publish because they want to transfer information. An essential ingredient for this transfer is being able to find this information. As the Literature Universe is expanding rapidly, finding your way in this deluge of information can be a daunting task. How do you find what you are looking for in a reasonable amount of time and more importantly, information you could not have found using the normal information discovery model? When you have some prior information (like author names and/or subject keywords), you can use your favorite search engine and apply that information as filters. There are also more sophisticated services like the myADS service of the SAO/NASA Astrophysics Data System (ADS), that do intelligent filtering for you and provide you with customized suggestions. Alternatively, you can ask somebody you consider to be an expert. On this poster we describe a method (the "recommender system") that mimics this information "ask the export" discovery model, argue that it is practically feasible to incorporate this method as a useful addition to the existing ADS service and show that it is able to produce meaningful results. The ADS is funded by NASA Grant NNX09AB39G.

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