Abstract: An approach is described for adjusting prominence of a participant profile in a social networking interface. An associated method may include receiving an activity stream update of the participant and calculating a relevancy score based on content in the activity stream update. The method further may include adjusting a visibility level of the participant profile in the social networking interface based upon the calculated relevancy score. Adjusting the visibility level may include increasing the visibility level of the participant profile upon determining that the calculated relevancy score is greater than or equal to a first predefined threshold value. Adjusting the visibility level further may include decreasing the visibility level of the participant profile upon determining that the calculated relevancy score is less than a second predefined threshold value.

Abstract: Mechanisms are provided for performing entity differentiation. A cognitive medical system ingests a corpus of medical content having references to medical entities, and performs entity recognition on the medical content to identify the medical entities. Responsive to the cognitive medical system identifying a medical entity having a plurality of annotations for a same medical entity attribute, an entity differentiation component executes an ordered set of entity differentiation algorithms, corresponding to the medical entity, for differentiating medical entity attribute values. The entity differentiation component runs the ordered set of entity differentiation algorithms, in order, on the plurality of annotations for the attribute to generate a ranked list of medical entity attribute values corresponding to the annotations in the plurality of annotations. The cognitive medical system performs a cognitive operation on the medical entity based on the ranked list of medical entity attribute values.

Abstract: An approach is described for adjusting prominence of a participant profile in a social networking interface. An associated method may include receiving an activity stream update of the participant and calculating a relevancy score based on content in the activity stream update. The method further may include adjusting a visibility level of the participant profile in the social networking interface based upon the calculated relevancy score. Adjusting the visibility level may include increasing the visibility level of the participant profile upon determining that the calculated relevancy score is greater than or equal to a first predefined threshold value. Adjusting the visibility level further may include decreasing the visibility level of the participant profile upon determining that the calculated relevancy score is less than a second predefined threshold value.

Abstract: Automatic semantic analysis for characterizing and correlating literary elements within a digital work of literature is accomplished by employing natural language processing and deep semantic analysis of text to create annotations for the literary elements found in a segment or in the entirety of the literature, a weight to each literary element and its associated annotations, wherein the weight indicates an importance or relevance of a literary element to at least the segment of the work of literature; correlating and matching the literary elements to each other to establish one or more interrelationships; and producing an overall weight for the correlated matches.

Abstract: Embodiments relate to an intelligent computer platform to receive a request for processing against a corpus. The request is analyzed and a lexical answer type (LAT), a first concept relevant to the received request and a second concept related to the identified first concept, are each identified. The LAT, together with the first and second concepts are utilized to create a first cluster and a second cluster. Documents are selectively populated into the clusters based on the respective LAT and concept qualifiers. The clusters are subject to sorting based on relevancy to the received request.

Abstract: A method, computer program product, and computer system for defining, at a first computing device, at least a portion of a display area associated with the first computing device. A specialized communication from a second computing device is received at the first computing device. The specialized communication is rendered at the first computing device in at least the portion of the display area. Use of an application within at least the portion of the display is prevented at least while the specialized communication is accessed.

Abstract: A first list that includes a first set of one or more concept terms may be obtained. The first set of one or more concept terms may be candidates for being conceptually related to a seed concept term. Prior to the obtaining, a first client computing device may provide a first plurality of individual characters and the seed concept term to a first user using the first client computing device. The first client computing device may prompt the first user to generate the first set of one or more concept terms that are conceptually related to the seed concept term using one or more of the first plurality of individual characters. In response to the obtaining, one or more particular categories to which each of the first set of one or more concept terms belongs to may be determined.

Abstract: A computer system utilizes a dataset to support a research study. One or more regions of interestingness are determined within a model of a first set of data records that are authorized for the research study by associated entities. A second set of data records is represented within the model, wherein the second set of data records are relevant for supporting objectives of the research study after de-identification. Records from the second dataset that are particularly useful for supporting objectives of the research study are identified, and authorization is requested from the corresponding entities of the identified data records from the second set of data records. After receiving authorization, those records are included with the first set to generate a resulting dataset. Embodiments of the present invention further include a method and program product for processing requests for health information in substantially the same manner described above.

Abstract: A computer-implemented method includes receiving first lossy converted documents. The computer-implemented method includes generating corrected documents for the first lossy converted documents. Each of the corrected documents includes edit markers that reflect structure changes relative to a corresponding document of the first lossy converted documents. The computer-implemented method includes generating feature vectors for the first lossy converted documents. The feature vectors include structure features of the first lossy converted documents. The computer-implemented method includes training one or more models based on the structure features and the edit markers. The computer-implemented method includes applying the trained one or more models to second lossy converted documents to determine proposed structure edits. The computer-implemented method includes transforming the second lossy converted documents to second corrected documents by applying one or more of the proposed structure edits.

Abstract: A method, system, and computer program product for using a natural language processor is disclosed. Included are importing highlighted and non-highlighted training text each including training nodes, one-hot encoding the training text, training a projection model using the training text, processing the highlighted training text using the projection model, and training a classifier model using the highlighted processed training text. Also included are importing new text including new nodes, one-hot encoding the new text, processing the new text using the projection model, and determining, using the classifier model, whether one of the new nodes is in a sought-after class.

Abstract: Embodiments relate to a system, program product, and method for use with an intelligent computer platform to decipher analogical phrases. A phrase is parsed into a set of terms to reveal an analogical pattern. The set of terms are categorized according to syntactic placement and each term is placed into two or more categories according to word type patterns in the phrase to produce metadata. The metadata is matched to outcome metadata generated from a set of outcomes produced from data storage and a set of grammatical data is generated for each potential outcome. A statistical model is trained, whereby the training includes weighing and ranking each potential outcome according to degree of congruence with the syntactic placement and word type patterns of the phrase. A highest outcome is selected, the highest outcome being the potential outcome with the highest rank and a confidence level data metric is then applied.

Abstract: Aspects of the present disclosure relate to identifying semantic relationships. Natural language content is received. A part of speech is determined for respective terms within the natural language content. A semantic type is determined for each of two or more terms within the natural language content. A parse tree representation containing a plurality of nodes is then generated based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms. A bounding box identifying a semantic relationship is then generated around a set of nodes on the parse tree representation, the set of nodes including the two or more terms.

Abstract: A method, system, and computer program product include providing a list of triggers, training the natural language processor with the list of triggers, providing to the natural language processor a text including one trigger, selecting nodes in the text to create an original potential span, predicting whether the original potential span includes another trigger, and adjusting, in response to predicting that the original potential span includes another trigger, the original potential span to exclude the another trigger to create a new potential span.

Abstract: Exemplary embodiments described herein disclose a method, a computer program product, and a computer system for facilitating a consented exchange of data between mobile applications. A computer may be configured to receive registration information corresponding to one or more mobile applications, in addition to data publications and data subscriptions from the one or more mobile applications. Furthermore, the computer may be configured to receive a bid from a subscribing application for data of a publishing application, and forward the bid from the subscribing application to the publishing application. Moreover, the computer may be configured to determine whether the publishing application accepts the bid, as well as whether an owner of the data consents to the exchange. Lastly, the computer may be configured to process the exchange based on determining that both the publishing application and owner of the data consent to the proposed exchange.

Abstract: Exemplary embodiments described herein disclose a method, a computer program product, and a computer system for facilitating an exchange of data between a user and a data consumer. A computer may receive registration information of both a user and data consumer. The computer may determine a value of the user data based on source, type, quantity, post-processing cost, and inclusion of rare data types or events. The computer may be configured to provide the user an offer for the data based on the determined value, and may determine whether the user accepts the offer or provides a counteroffer. Based on determining that the user has accepted the offer or, in the alternative, that the counteroffer is acceptable, the computer may be configured to process the offered data exchange.

Abstract: Mechanisms are provided for collecting and applying drug-to-drug interaction information from natural language documents. The mechanisms perform natural language processing of natural language documents in a corpus of natural language documents, to identify content in the natural language documents that describe a drug-to-drug interaction. The mechanisms categorize the drug-to-drug interaction and calculate, for a first drug in the drug-to-drug interaction, an exclusion weighting factor for use in evaluating treatments for patients that include a second drug of the drug-to-drug interaction based on the categorization of the drug-to-drug interaction. The mechanisms store the drug-to-drug interaction as a drug-to-drug interaction data structure that specifies the first drug, the second drug, the categorization of the drug-to-drug interaction, and the exclusion weighting factor associated with the drug-to-drug interaction.

Abstract: In an approach to content selection, one or more computer processors receive a first query from a user. The one or more computer processors retrieve a first response for the first query. The one or more computer processors determine whether the first response exceeds a threshold for a policy for content usage associated with the first response, wherein the policy for content usage specifies one or more restrictions for usage of a content asset. In response to determining the first response exceeds the threshold for the policy for content usage, the one or more computer processors select a first subset of the first response to meet the threshold for the policy for content usage. The one or more computer processors send the first subset of the first response to the user.

Abstract: A technique for dynamic augmented reality media creation includes an analysis of reality content received by a device. Augmentation data is identified based on the analysis of the reality content, and then the augmentation data is displayed to the user via the device. A capture module determines whether the reality content meets capture event criteria and, if the criteria is met, augmented reality content is created and captured prior to a display of the augmentation data to the user.

Abstract: A method, system and computer-usable medium for classifying a source document using sub-documents identified in the source document. The method, system, and computer-usable medium are used to access the source document from electronic memory. The source document is electronically searched to detect markers indicative of whether the source document includes one or more sub-documents. Incongruities in the source document are located using the detected markers and the source document is split into sub-documents at the located incongruities. Each of the sub-documents is classified. The sub-documents are joined as a re-assembled source document with classifications including classifications for one or more of the sub-documents.

Abstract: Methods and systems privatize a dataset while controlling discoverability of patterns of the dataset. In an embodiment, values are assigned to discoverable patterns of a dataset. Privacy constraints are determined to privatize the dataset. Pattern constraints are determined to preserve a first set of patterns of the dataset and to conceal a second set of patterns of the dataset. A model is generated to satisfy all of the privacy constraints and a subset of the pattern constraints that do not conflict with the privacy constraints, with minimal loss of data. The dataset is modified based on the model. Discoverable patterns of the modified database are determined from the subset of privacy constraints. And a monetary value of the modified dataset is determined based on the patterns that remain discoverable in the modified dataset.