Conduent Business Services, LLC

Microsoft Technology Licensing, LLC

Sandipan Dandapat

Shourya Roy

Himanshu Sharad Bhatt

Ragunathan Mariappan

Raksha Sharma

Shreshtha Mundra

The present disclosure relates to methods and systems for controlling content distribution. The methods and systems receive an original search query and expand the original search query by adding one or more neutral words to create an expanded search query. The methods and systems automatically classify the original search query using the expanded search query in an accurate manner and use the classification to control content distribution.

Content distribution control

The disclosed embodiments illustrate methods of data processing for training a target domain classifier to label text segments. The method includes identifying a set of common keywords with same label from a set of source keywords and a set of target keywords. The method includes training a first classifier, based on the set of common keywords, to label a first set of target text segments. The method includes training a second classifier based on at least a subset of the labeled first set of target text segments. The method includes training a third classifier, based on the first classifier and the second classifier, to label a second set of target text segments, wherein a subset of the labeled second set of target text segments is utilized for re-training the second classifier. The method further includes determining labels of another plurality of target text segments based on the re-trained second classifier.

Method and system for training a target domain classifier to label text segments

The disclosed embodiments illustrate methods data processing for real-time text analysis. The method includes receiving text content from a plurality of user-computing devices, wherein the text content comprises at least a current text segment and a previous text segment. The method further includes extracting one or more first features from the current text segment, wherein at least a first feature of the one or more first features corresponds to a difference between timestamps associated with each of the current text segment and the previous text segment. The method further includes categorizing the current text segment into a predetermined category of one or more predetermined categories, based on at least the one or more first features, automatically by utilizing a classifier. Further, the method includes predicting a likelihood of evolution of an attribute in the text content, based on the predetermined category associated with the current text segment.

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Kolkata, India

Sandipan Dandapat