Abstract: Described and claimed is a computer-implemented method of preparing a training dataset for a natural language processing, NLP, or natural language understanding, NLU, machine learning algorithm from an original text dataset, the method comprising the steps of selecting one or more sentences from the original text dataset as selected sentences, determining for each selected sentence one or more grammatical elements of the selected sentence that can be negated as negatable elements, determining for one or more negatable words in each negatable element one or more antonyms, based on each determined antonym creating a negated sentence by replacing the respective negatable element in the selected sentence for which the negatable element was determined with the determined antonym, and adding the negated sentences to the training dataset. Further, a computer-implemented method of training a word embedding or an NLP or NLU machine learning algorithm, a system and a computer program product are described and claimed.

Abstract: The present disclosure provides techniques for capturing, processing, and displaying panoramic content such as video content and image data with a panoramic camera system. In one embodiment, a method for processing panoramic video content may include communicating captured video content to a virtual sensor of a panoramic camera; applying a machine learning algorithm to the captured video content; identifying content of interest information suitable for use by at least one smart application; and executing a smart application in connection with the identified content of interest information. The machine learning algorithm may include at least one of a pattern recognition algorithm or an object classification algorithm.

Abstract: Provided is a system and method for aggregating, classifying, and enriching social media. Machine learning techniques and automatic analysis is performed on posts aggregated from different social media sites. The posts are curated to be sourced from the official accounts of popular or well-performing public figures, brands, and business entities. Posts are classified in two levels to better organize the posts into differentiated feeds by first categorizing the sources by an identity category, such as musician, actor, athlete, miscellaneous celebrity, news and lifestyle, brand, or business entity, and the posts themselves into music, videos, photos, upcoming events, location-specific, concerts, news and lifestyle, and community interaction. Posts are enhanced and enriching by adding hyperlinks, modifying appearance, and integrating with a calendar or a map for organizing the posts.