Xerox Corporation

Conduent Business Services, LLC

Sumit Bhatia

Tong Sun

Wei Hua Peng

Saurabh Singh Kataria

Arvind Agarwal

Quanzeng You

Juan Li

Chandrima Sarkar

Jingxuan Li

The disclosed embodiments illustrate methods and systems for creating a classifier for predicting a personality type of users. The method includes receiving a first tag for messages, from a crowdsourcing platform. The first tag relates to personality type of users. Further, the messages, tagged with first tag are segregated into a training data and a testing data. Further, parameters associated with set of messages in the training data are determined based on type of messages. Further, classifiers are trained for a personality type. Further, a second tag for set of messages in testing data is predicted using trained classifiers for a combination of parameters. A performance of classifiers is determined by comparing the second tag and the first tag associated with set of messages in the testing data. A classifier is selected from classifiers, which is indicative of a best combination of parameters to predict personality type of users.

Methods and systems for creating a classifier capable of predicting personality type of users

The technical solution under the present disclosure automatically analyzes conversations between users by receiving a training dataset having a text sequence including sentences of a conversation between the users; extracting feature(s) from the training dataset based on features; providing equation(s) for a plurality of tasks, the equation(s) being a mathematical function for calculating value of a parameter for each of the tasks based on the extracted feature; determining value of the parameter for tasks by processing the equation(s); assigning label(s) to each of the sentences based on the determined value of the parameter, a first label being selected from a plurality of first labels, and a second label being selected from a number of second labels; and storing and maintaining with the database a pre-defined value of the parameter, first labels, conversations, second labels, a test dataset, equation(s), and pre-defined features.

Methods and systems for automatic analysis of conversations between customer care agents and customers

Methods and systems provide electronic instructions to a non-transitory electronic storage hardware device to record images uploaded by a user over a computerized network to a social networking site, and to record categories of network site locations to which the images are uploaded by the user. These methods and systems also provide electronic instructions to a computerized electronic image processor hardware device to analyze features within the images to identify content of each of the images, and to determine the user characteristics based on the categories of network site locations to which the images are uploaded by the user and on the content of the images uploaded by the user. Also, such methods and systems provide electronic instructions to the computerized electronic image processor hardware device to output the user characteristics on a graphic user interface hardware device.

User characteristic prediction using images posted in online social networks

A system and method for analyzing social media data by obtaining social media data from a social media platform, where the social media data includes documents from multiple users of the social media platform; classifying the documents using a sentiment classifier; tokenizing the documents into terms; associating a sentiment with each term; detecting a first event based on a number of occurrences of a first term in the documents; and providing information associated with the event to a user, where the information includes the first term and a sentiment associated with the first term.

Methods and systems for monitoring and analyzing social media data

A method, non-transitory computer readable medium, and apparatus for extracting text from a social media document are disclosed. For example, the method indexes a plurality of social media documents into a plurality of snippets, receives a query including one or more keywords and a purpose, identifies one or more of the plurality of snippets that include the one or more keywords in an index, ranks the one or more of the plurality of snippets in accordance with the purpose and provides the one or more plurality of snippets that are ranked in accordance with the purpose.

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Webster, NY, United States of America

Sumit Bhatia