US 11,720,940 B2
System and apparatus for models based on data augmented with conceivable transitions
Choudur K. Lakshminarayan, Austin, TX (US); and Ram Kosuru, Austin, TX (US)
Assigned to MICRO FOCUS LLC, Santa Clara, CA (US)
Appl. No. 15/770,899
Filed by ENTIT SOFTWARE LLC, Sanford, NC (US)
PCT Filed Oct. 29, 2015, PCT No. PCT/US2015/058109
§ 371(c)(1), (2) Date Apr. 25, 2018,
PCT Pub. No. WO2017/074398, PCT Pub. Date May 4, 2017.
Prior Publication US 2018/0315103 A1, Nov. 1, 2018
Int. Cl. G06Q 30/0601 (2023.01); G06N 20/00 (2019.01); G06Q 30/06 (2023.01)
CPC G06Q 30/0601 (2013.01) [G06N 20/00 (2019.01); G06Q 30/06 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
an input/output interface to communicate with a client device;
a processor readable non-transitory data storage medium; and
a processor, in communication with the processor readable data non-transitory storage medium and the input/output interface, to:
augment historical interaction data of prior buyers and non-buyers that browsed a website by imputing connections among links between URLs of the website and estimating an augmented set of transition probabilities based on conceivable transitions arising from the imputed connections, each of the conceivable transitions including a multi-step transition between a first URL and a second URL via at least one intermediate URL of the website;
train each of a plurality of different models using the historical interaction data and/or augmented historical interaction data;
receive from a client device, interaction data of a user browsing the website;
provide a plurality of different models for an intent of the user based on the interaction data, the plurality of different models comprising at least one augmented buyer model based on the augmented set of transition probabilities of the conceivable transitions and an alternate buyer model based on an actual transition between the first URL and the second URL;
compare a transition probability of the augmented set of transition probabilities associated with the augmented buyer model based on a conceivable transition to a significance threshold measure;
when the transition probability of the augmented set of transition probabilities exceeds the significance threshold measure, select the augmented buyer model;
when the transition probability of the augmented set of transition probabilities does not exceed the significance threshold measure, select the alternate buyer model;
determine when the user is likely to be a buyer, based on the interaction data and the selected one of the augmented buyer model and the alternate buyer model; and
present the user with an offer to buy from the website upon the determination that the user is likely to be the buyer.