Abstract: In an approach, a processor obtains at least one media file. A processor receives a request to create a segment sequence using the at least one media file, wherein the segment sequence comprises a plurality of segments of the at least one media file. A processor creates the segment sequence from the at least one media file. A processor shares the segment sequence to a social computing platform. A processor receives a request for a social computing operation to be performed on the segment sequence. A processor performs the social computing operation on the segment sequence.

Abstract: An illustrative embodiment includes processing parse tree data. A parse tree data structure that is representative of a document object model (DOM) tree data structure is received. Concomitant to receiving the parse tree data structure, an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node is received by the processor. Requests to manipulate the parse tree data structure that include node inserts and document order comparisons are also performed.

Abstract: An illustrative embodiment includes processing parse tree data. A parse tree data structure that is representative of a document object model (DOM) tree data structure is received. Concomitant to receiving the parse tree data structure, an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node is received by the processor. Requests to manipulate the parse tree data structure that include node inserts and document order comparisons are also performed.

Abstract: A mechanism is provided in a data processing system for text classification. A domain terms selector component, executing on a processor of the data processing system, receives an input text. A domain terms selector component executing on a processor of the data processing system identifies at least one domain term in the input text. A domain terms replacer component executing on a processor of the data processing system replaces the at least one identified domain term in the input text with a corresponding replacement term to form a revised input text. A text classifier component configured with a trained text classifier machine learning model classifies the revised input text to form a class determination.

Abstract: Embodiments can provide a computer implemented method in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to cause the processor to implement a system for providing profile photo enhancement, the method comprising receiving, from a specification source, one or more specifications for image acceptance criteria; receiving, from an uploading user, an image; examining, through an image processing toolbox, the image to determine if all of the image acceptance criteria are met; if all image acceptance criteria are met, accepting the image; and if one or more image acceptance criteria are not met, processing the image.

Abstract: Embodiments can provide a computer implemented method in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to cause the processor to implement a system for providing profile photo enhancement, the method comprising receiving, from an online platform, one or more specifications for image acceptance criteria; receiving, through an uploading user, a plurality of images; receiving, through a requesting user, a request to view an image; selecting a particular specification for image acceptance criteria; for each image in the plurality of images: examining, through an image processing toolbox, the image to determine if the image acceptance criteria are met; if all acceptance criteria are met, providing the image to the requesting user; if one or more acceptance criteria are not met, taking one or more actions to process the image, reexamining, through the image processing toolbox, the processed image to determine if the image acceptan

Abstract: A mechanism is provided in a data processing system for text classification. A domain terms selector component, executing on a processor of the data processing system, receives an input text. A domain terms selector component executing on a processor of the data processing system identifies at least one domain term in the input text. A domain terms replacer component executing on a processor of the data processing system replaces the at least one identified domain term in the input text with a corresponding replacement term to form a revised input text. A text classifier component configured with a trained text classifier machine learning model classifies the revised input text to form a class determination.

Abstract: A mechanism is provided in a data processing system for text classifier training. The data processing system receives a training set of text and class specification pairs to be used as a ground truth for training a text classifier machine learning model for a text classifier. Each text and class specification pair comprises a text and a corresponding class specification. A domain terms selector component executing on a processor of the data processing system identifies at least one domain term in the texts of the training set. A domain terms replacer component executing on a processor of the data processing system replaces the at least one identified domain term in the texts of the training set with a corresponding replacement term to form a revised set of text and class specification pairs. A text classifier trainer component executing on a processor of the data processing system trains the text classifier machine learning model using the revised set to form a trained text classifier machine learning model.

Abstract: An answer to a question may selected from answers from a set of answering pipelines. Question answer data can be generated for a question, using a first answering pipeline. Another set of question answer data can be generated for the second question, using the second answering pipeline. The question answer data can include answers and confidence values for each answer. Using a weighting formula and a blending profile for the first answering pipeline, a vote weight can be determined for an answer with the highest confidence value. The same weighting formula and a second blending profile may be used to determine a vote weight for another answer with the highest confidence value. An answer to the question may be selected from the answers, based on the overall highest vote weight.

Abstract: A first and second blending profile may be created for a set of question answering pipelines. A set of test answer data may be generated for a first answering pipeline. The test answer data may be generated based on a set of test question and using an answer key associated with the test questions. Based on the test answer data, a first blending profile can be created for the first answering pipeline. Using the set of test questions and a second answer key, another set of test answer data may be generated. This set may be generated for the second answering pipeline. Using this second answering pipeline test answer data, a second blending profile can be generated for the second answering pipeline. Each blending profile may have metadata about a confidence of each pipeline.

Abstract: In analyzing learning content, a social learning system receives from at least one client system in the social learning system a creation of at least one informal course by a learning content creator. Each informal course comprises learning content and metadata describing the learning content and the learning content creator. The social learning system further receives social data from a plurality of client systems in the social learning system for the at least one informal course. When the social learning system receives a query from a learning content administrator system in the social learning system including query parameters, the social learning system searches at least one of the metadata and the social data for one or more informal courses matching the query parameters and returns a list of one or more informal courses matching the query parameters as a query result.

Abstract: In analyzing learning content, a social learning system receives from at least one client system in the social learning system a creation of at least one informal course by a learning content creator. Each informal course comprises learning content and metadata describing the learning content and the learning content creator. The social learning system further receives social data from a plurality of client systems in the social learning system for the at least one informal course. When the social learning system receives a query from a learning content administrator system in the social learning system including query parameters, the social learning system searches at least one of the metadata and the social data for one or more informal courses matching the query parameters and returns a list of one or more informal courses matching the query parameters as a query result.

Abstract: A system for presenting and executing a multiplicity of interactive forms as a single document includes a server having one or more copies of a multi-form package and configured to deliver a copy of the package to a requesting device upon request. The system also includes a client computing device configured to request and receive the multi-form package, the first computing device including an application program and a multi-form document engine configured to receive commands from the application program and, in response, cause forms from the multi-form package to be presented and executed.

Abstract: A mechanism is provided in a data processing system to improve ground truth in a question answering cognitive system. The mechanism trains a similar passage machine learning model for a similar passage cognitive system using a question and answer key to form a trained similar passage machine learning model. The question and answer key comprises a list of question and answer specification pairs forming a ground truth for the question answering cognitive system. Each question is a text string and each answer specification references one or more text passages from a corpus of information.

Abstract: A system for presenting and executing a multiplicity of interactive forms as a single document includes a server having one or more copies of a multi-form package and configured to deliver a copy of the package to a requesting device upon request. The system also includes a client computing device configured to request and receive the multi-form package, the first computing device including an application program and a multi-form document engine configured to receive commands from the application program and, in response, cause forms from the multi-form package to be presented and executed.

Abstract: A method for providing group-based attention management of electronic messages may include receiving an electronic message, the electronic message defining a plurality of recipients. One or more candidate tuples are then identified from the plurality of recipients. The one or more candidate tuples are compared with one or more stored tuples to identify one or more relevant tuples from the candidate tuples. Based on the one or more relevant tuples, an attention score for one or more of the plurality of recipients is determined. Based on the attention score for one or more of the plurality of recipients, the presentation of the electronic message to one or more of the plurality of recipients is modified.

Abstract: A mechanism is provided in a data processing system for aggregating sentiment about an entity from a corpus of documents. The mechanism identifies a plurality of sentiment passages in the corpus of documents. Each of the plurality of sentiment passages includes a statement of sentiment about the entity. The mechanism determines a plurality of passage sentiment scores for the plurality of sentiment passages and an actual aggregate sentiment score from the plurality of passage sentiment scores based on a k-valued model. The mechanism determines a sentiment confidence score for the actual aggregate sentiment score based on the raw aggregate sentiment score and the actual aggregate sentiment score and presents the actual aggregate sentiment score and the sentiment confidence score.

Abstract: A method, system and computer program product for determining whether the social learning playlist is effective in educating participants. The text of the collection of online materials of a social learning playlist is scanned to identify key concepts (i.e., the most important points) using natural language processing. The user selects a concept from a list of key concepts, which includes these identified key concepts, and a type of question (e.g., true/false) to be used in assessing the understanding of the selected key concept. The selected type of question and answer to the question are generated using analytic analysis and artificial intelligence on the online materials of the playlist. In this manner, by generating appropriate question and answer pairs, where the questions are inserted at selected locations within the playlist, the creator of the playlist is able to assess whether the participants are understanding the key concepts in the playlist.

Abstract: A method, system and computer program product for determining whether the social learning playlist is effective in educating participants. The text of the collection of online materials of a social learning playlist is scanned to identify key concepts (i.e., the most important points) using natural language processing. The user selects a concept from a list of key concepts, which includes these identified key concepts, and a type of question (e.g., true/false) to be used in assessing the understanding of the selected key concept. The selected type of question and answer to the question are generated using analytic analysis and artificial intelligence on the online materials of the playlist. In this manner, by generating appropriate question and answer pairs, where the questions are inserted at selected locations within the playlist, the creator of the playlist is able to assess whether the participants are understanding the key concepts in the playlist.

Abstract: An illustrative embodiment includes processing parse tree data. A parse tree data structure that is representative of a document object model (DOM) tree data structure is received. Concomitant to receiving the parse tree data structure, an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node is received by the processor. Requests to manipulate the parse tree data structure that include node inserts and document order comparisons are also performed.