Tuning a trained data record matching model using customer data and representation learning
AssigneeInternational Business Machines Corporation
InventorsAbhishek Seth, Devbrat Sharma, Mahendra Singh Kanyal, Soma Shekar Naganna
Life of this patent
Estimating the term…
Abstract
A method, system, and computer program product are configured to create a tuned data record matching model by adjusting values of one or more parameters in a data record matching model based on a second training data set labeled at a data record level, wherein the data record matching model is initially trained using a first training data set labeled at an attribute level.
Claims20
A method which provides an accurate matching model which is tuned by adjusting values based on customer data, comprising:
- training, by a processor set, a classification model to determine adjusted distance measures using distance vectors as inputs and labels of a second training data set as target outputs;
- training, by the processor set, at least one regression model to determine an adjusted comparison coefficient vector for each attribute using the determined adjusted distance measures from the trained classification model;
- obtaining, by the processor set, a data record matching model trained using a first training data set labeled at an attribute level;
- and
- creating, by the processor set, a tuned data record matching model by adjusting values of one or more parameters in the data record matching model based on the second training data set labeled at a data record level.
A computer program product which provides an accurate matching model which is tuned by adjusting values based on customer data, the computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:
- train a classification model to determine adjusted distance measures using distance vectors as inputs and labels of a second training data set as target outputs;
- train at least one regression model to determine an adjusted comparison coefficient vector for each attribute using the determined adjusted distance measures from the trained classification model;
- create a tuned data record matching model by adjusting values of one or more parameters in a data record matching model based on the second training data set labeled at a data record level, wherein the data record matching model is initially trained using a first training data set labeled at an attribute level;
- and
- use the tuned data record matching model to classify pairs of data records as matching or unmatching.
A system which provides an accurate matching model which is tuned by adjusting values based on customer data, the system comprising:
- a processor set, one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:
- train a classification model to determine adjusted distance measures using distance vectors as inputs and labels of a second training data set as target outputs;
- train at least one regression model to determine an adjusted comparison coefficient vector for each attribute using the determined adjusted distance measures from the trained classification model;
- create a tuned data record matching model by adjusting values of one or more parameters in a data record matching model based on the second training data set labeled at a data record level, wherein the data record matching model is initially trained using a first training data set labeled at an attribute level;
- and
- provide the tuned data record matching model to a customer for the customer to use the tuned data record matching model to classify pairs of data records as matching or unmatching.
Dependencies are inferred from the claim text.