Wipro Limited

Srinivas Adyapak

Raghavendra Hosabettu

Mohit Sharma

A system and method for data cleansing are disclosed. The method includes receiving by a data classifier, a data corpus comprising one or more words. The method further includes grouping the one or more words into a plurality of pre-defined categories and determining an overlap ratio between each pair of the plurality of pre-defined categories based on a comparison between each of the plurality of pre-defined categories. A normalized overlap ratio is computed for each of the plurality of pre-defined categories based on a combination of each overlap ratio. At least one of the plurality of pre-defined categories is determined based on a comparison between each of the normalized overlap ratio and an ideal overlap ratio. Finally, one or more common words from the selected at least one of the plurality of pre-defined categories is removed based on a frequency of occurrence of the one or more common words.

System and method of data cleansing for improved data classification

In certain embodiments, the method may comprise, determining one or more features associated with each of one or more concepts from at least one sentence; determining at least one concept feature matrix based on the one or more features; determining one or more contribution factors among the one or more concepts, based on the at least one concept feature matrix; determining incremental synchronization data by storing current timestamp associated with the one or more concepts and comparing it with knowledge data; generating at least one new concept feature matrix based on the incremental synchronization data; determining one or more new contribution factors among the one or more concepts, based on the at least one new concept feature matrix; determining differential value between the one or more contribution factors and the one or more new contribution factors; and dynamically updating the knowledge data, in the repository system.

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Bengaluru, India

Srinivas Adyapak