Abstract: 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.

Abstract: Systems and methods of data analytics, which in various embodiments enable business analysts to apply certain machine learning and analytics algorithms in a self-service manner by binding them to generic business questions that they can be used to answer in particular domains. The general approach may be to define the application of an algorithm to solve specific problems (questions) for particular combinations of a business domain and a data category. At design time, the algorithm may be linked to canonical data within a data category and programmed to run with this canonical data set. At runtime, given a dataset and its category, and a business domain, a user may choose from the corresponding questions and the system may run the algorithm bound to that question.

Abstract: A method, non-transitory computer readable medium, and apparatus for recommending a topic-cohesive and interactive implicit community are disclosed. For example, the method receives a request for customer care, selects an implicit community identified from a plurality of individual users of a social media website based upon a relevance score related to a topic of the request for customer care and recommends the implicit community in response to the request for customer care.

Abstract: A method, system, and computer program product for determining skills of an employee is disclosed. The method includes determining a first likelihood of at least one keyword from a plurality of keywords being relevant to a topic. The plurality of keywords is extractable from one or more publications associated with the employee, the one or more publications being accessible from a plurality of sources. The method further includes determining a second likelihood of the employee being associated with the topic for at least one source from the plurality of sources. A first set of keywords from the plurality of keywords is assigned to the employee based on the first likelihood and the second likelihood. The first set of keywords is indicative of the skills of the employee.

Abstract: Automated font mapping is performed for one or more document fonts of a document to map the one or more document fonts to at least one replacement font. The font mapping is limited by at least one document-specific font mapping limitation. The document is rendered using the at least one replacement font. The automated font mapping may include performing a constrained optimization of an objective function measuring similarity of the one or more document fonts and the corresponding mapped at least one replacement font, the constrained optimization being constrained by at least one constraint embodying at least one document-specific font mapping limitation. The automated font mapping may include selecting a subset of the set of fonts available for the rendering based on the at least one document-specific font mapping limitation, and performing the optimization respective to the selected subset of the set of fonts available for the rendering.