New Article Provides Details on “Building the Next New York Times Recommendation Engine”
On The NY Times OPEN Blog Alexander Spangher writes:
In this post, I’ll discuss our recent work revamping The New York Times’s article recommendation algorithm, which currently serves behind the Recommended for You section of NYTimes.com.
By modeling article content and reader preferences with topics, then adjusting based on reading patterns, we’ve reconceptualized our recommendation engine. Our system is now a successful, large-scale implementation of cutting-edge research in collaborative topic modeling, and it provides significant performance increases when compared with previous algorithms used to make recommendations.
Read the Complete Article (approx. 1600 words)
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About Gary Price
Gary Price (firstname.lastname@example.org) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.