In the first month we focused on applying learning to rank to sparse metadata and to investigate the applicability of inverted index based metrics and lookups for near duplicate search. Results in both directions seem to be promising. Especially inverted indices using simple word grams or bi-word grams provide efficient near duplicate search facilities.
Next, learn to rank will find its way into tag recommendation in particular and recommendation in general. Basically, will learn to rank outperform traditional recommendation approaches? Lets see.
Donnerstag, 5. Mai 2011
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