4 ms·

Hi Justin, do you have a link to a technical paper on the anonymous? click algorithm. Was curious if you applied it to domains other than products/shopping.

• justin_vanw 12y ago
  I linked to the patent application (which has been denied). The algorithm is actually very very simple. 1. produce a set of 'features' for every document. This is what you will index into the inverted index. Features can be words from the document, or they can be things like 'price_between_0_100'. 2. Build a set of pairs (search_phrase, clicked_on_document_id). 3. For each search_phrase in your set of pairs, run the search_phrase through your search engine. The set of all results we will call SET_A. 4. SET_B is the set of documents for a search_phrase that have been clicked on. SET_B is a subset of SET_A. Using mutual information, it is possible to determine which features best differentiate documents from SET_B from (SET_A - SET_B) for a specific search_phrase. These are the features you will 'boost' when you see that search_phrase. As an example, one of the features this pulled out in practice was the word 'Oceanic' for the search_phrase "lost". It basically zeroed in on the fact that the word 'Oceanic' appearing in the description of a product differentiated 'good' results from 'bad' results for the query 'lost'. Edit: Here is a hard to follow presentation on it: https://docs.google.com/presentation/d/1xzQbQ1cM3GnaS_LoCvmJGUunXpaYS_z3y4dO_poFfUA/edit?usp=sharing https://docs.google.com/presentation/d/1xzQbQ1cM3GnaS_LoCvmJ... Edit2: Another presentation, easy to follow but without most of the technical depth: https://drive.google.com/file/d/0B_eNCTyNa0DHcy1UOGpSUk41NDA/view?usp=sharing https://drive.google.com/file/d/0B_eNCTyNa0DHcy1UOGpSUk41NDA...