INFER PRODUCT CORRELATIONS BY INTEGRATING TRANSACTIONS AND CONTEXTUAL USER BEHAVIOR SIGNALS
Systems and methods for determining correlation scores for product pairs are provided. Contextual user behavior indicator data relating to a plurality of user behavior indicator types is received. A correlation score is computed for a first product and a second product for each user behavior indicator type from the plurality of user behavior indicator types. A final correlation score is computed for the first product and the second product by combining the computed correlation scores for each user behavior indicator type. The computed final correlation score for the first product and the second product is stored into a first data storage.
1 . A method for inferring product correlations, the method comprising:
receiving contextual user behavior indicator data relating to a plurality of user behavior indicator types;
computing a correlation score for a first product and a second product for each user behavior indicator type from the plurality of user behavior indicator types;
computing a final correlation score for the first product and the second product by combining the computed correlation scores for each user behavior indicator type; and
storing the computed final correlation score for the first product and the second product into a first data storage.
2 . The method of claim 1 , further comprising:
computing a correlation score for additional products for each behavior indicator from the plurality of behavior indicators; and
computing a final correlation score for each product pair in the plurality of additional product products by combining the computed correlation scores for each behavior indicator type.
3 . The method of claim 2 , further comprising:
receiving a user query; and
determining one or more correlated products based on the user query and the computed final correlation scores.
4 . The method of claim 1 , wherein combining the computed correlation scores includes summing the computed correlation scores using one or more weights, with each behavior indicator having an assigned weight.
5 . The method of claim 1 , wherein the plurality of behavior indicators include a search keyword behavior indicator.
6 . The method of claim 1 , wherein the plurality of behavior indicators include an merchant website search keyword behavior indicator.
7 . The method of claim 1 , wherein the plurality of behavior indicators include an website click URL behavior indicator.
8 . The method of claim 1 , wherein the plurality of behavior indicators include a referral source behavior indicator.
9 . A system for inferring product correlations, the system comprising:
a receiver configured to receive contextual user behavior indicator data relating to a plurality of user behavior indicator types;
a recommender module configured to compute a correlation score for a first product and a second product for each user behavior indicator type from the plurality of user behavior indicator types, and compute a final correlation score for the first product and the second product by combining the computed correlation scores for each user behavior indicator type; and
a data storage configured to store the computed final correlation score for the first product and the second product into a first data storage.
10 . The system of claim 9 , wherein the recommender module further configured to:
compute a correlation score for additional products for each behavior indicator from the plurality of behavior indicators; and
compute a final correlation score for each product pair in the plurality of additional product products by combining the computed correlation scores for each behavior indicator type.
11 . The system of claim 10 , wherein the receiver further configured to receive a user query; and the recommender module further configured to determine one or more correlated products based on the user query and the computed final correlation scores.
12 . The system of claim 9 , wherein combining the computed correlation scores includes summing the computed correlation scores using one or more weights, with each behavior indicator having an assigned weight.
13 . The system of claim 9 , wherein the plurality of behavior indicators include a search keyword behavior indicator.
14 . The system of claim 9 , wherein the plurality of behavior indicators include an merchant website search keyword behavior indicator.
15 . The system of claim 9 , wherein the plurality of behavior indicators include an website click URL behavior indicator.
16 . The system of claim 9 , wherein the plurality of behavior indicators include a referral source behavior indicator.
17 . A computer-readable storage medium having machine instructions stored therein, the instructions being executable by a processor to cause the processor to perform operations comprising:
receiving a request for a product recommendation for a first product;
determining a product recommendation based on computed final correlation scores of product pairs including the first product, the final correlation scores computed by combining correlation scores for two or more behavior indicator types; and
transmitting the determined product recommendation.
18 . The computer-readable storage medium of claim 17 , the correlation scores are computed for each product pair and at least some behavior indicator types from a plurality of user behavior indicator types.
19 . The computer-readable storage medium of claim 18 , wherein the plurality of behavior indicators include a search keyword behavior indicator.
20 . The computer-readable storage medium of claim 18 , wherein the plurality of behavior indicators include an merchant website search keyword behavior indicator.
21 . The computer-readable storage medium of claim 18 , wherein the plurality of behavior indicators include an website click URL behavior indicator.
22 . The computer-readable storage medium of claim 18 , wherein the plurality of behavior indicators include a referral source behavior indicator.