METHOD AND SYSTEM FOR PRODUCT DATA CATEGORIZATION BASED ON TEXT AND ATTRIBUTE FACTORIZATION
This disclosure relates generally to method and system for product data categorization based on text and attribute factorization. The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous...
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creator | BARUAH, Sudesna VASUDEVAN, Bagya Lakshmi |
description | This disclosure relates generally to method and system for product data categorization based on text and attribute factorization. The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous text based on a predefined template. Further a dictionary for the set of product data based on a set of attributes comprising a product key with its corresponding product value. Further, a multi-level contextual data for the set of product data are extracted by assigning a weight to each product data based on likelihood and creating a set of datapoints for each product data. The set of product data are categorized by feeding the set of data points to a set of predefined parameters to compute a minimum count, a total size, total number of epochs, a skip gram value and a hierarchical softmax. |
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The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous text based on a predefined template. Further a dictionary for the set of product data based on a set of attributes comprising a product key with its corresponding product value. Further, a multi-level contextual data for the set of product data are extracted by assigning a weight to each product data based on likelihood and creating a set of datapoints for each product data. 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The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous text based on a predefined template. Further a dictionary for the set of product data based on a set of attributes comprising a product key with its corresponding product value. Further, a multi-level contextual data for the set of product data are extracted by assigning a weight to each product data based on likelihood and creating a set of datapoints for each product data. 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The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous text based on a predefined template. Further a dictionary for the set of product data based on a set of attributes comprising a product key with its corresponding product value. Further, a multi-level contextual data for the set of product data are extracted by assigning a weight to each product data based on likelihood and creating a set of datapoints for each product data. The set of product data are categorized by feeding the set of data points to a set of predefined parameters to compute a minimum count, a total size, total number of epochs, a skip gram value and a hierarchical softmax.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
title | METHOD AND SYSTEM FOR PRODUCT DATA CATEGORIZATION BASED ON TEXT AND ATTRIBUTE FACTORIZATION |
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