Abstract: Presenting ancestral origin information, comprising: receiving a request to display ancestry data of an individual; obtaining ancestry composition information of the individual, the ancestry composition information including information pertaining to a proportion of the individual's genotype data that is deemed to correspond to a specific ancestry; and presenting the ancestry composition information to be displayed.

Abstract: The present invention provides an attribute estimation system capable of acquiring an image of a person whose attributes are to be estimated accurately and informing the person of an attribute estimation result. The attribute estimation system (1) includes: a mirror (11) equipped with an information display terminal (12); and an attribute estimation device (3). The information display terminal (12) includes an image acquisition unit. The information display terminal (12) is disposed on the mirror (11) in such a manner that the information display terminal (12) can display information on a surface of the mirror (11) and that the image acquisition unit can acquire an image of a user of the mirror (11). The information display terminal (12) and the attribute estimation device (3) can be connected to each other via a communication line network (2). The attribute estimation device (3) generates attribute information estimated from the acquired image of the user of the mirror (11).

Abstract: A system and method for analyzing documents, such as posts, on-line reviews and comments from people based on topics of the documents, to determine general sentiment of users is disclosed. Topics from the documents and their corresponding sentiment polarities are extracted. The documents are regarded to be constituted by a series of topics. The sentiment for a topic is represented by a quadruple (k, so, h, i), where k is the topic, so is the sentiment opinion, h is the comment or post holder, and i is the document. A quintuple (k, sup, p, n, ne) is used to illustrate the topics and corresponding sentiments and is stored in S, where sup indicates the frequency of the topic, and p (positive), n (negative) and ne (neutral) are different types of opinions of the users. From the quintuple set S, every topic is related to three kinds of sentiment opinions (positive, negative, and neutral), enabling determination of popular topics in documents as well as the users' sentiment polarities.

Abstract: A domain-adapted classification system and method are disclosed. The method includes mapping an input set of representations to generate an output set of representations, using a learned transformation. The input set of representations includes a set of target samples from a target domain. The input set also includes, for each of a plurality of source domains, a class representation for each of a plurality of classes. The class representations are representative of a respective set of source samples from the respective source domain labeled with a respective class. The output set of representations includes an adapted representation of each of the target samples and an adapted class representation for each of the classes for each of the source domains. A class label is predicted for at least one of the target samples based on the output set of representations and information based on the predicted class label is output.

Abstract: The present invention relates to an apparatus and method for changing alarm information based on weather, and more particularly to an apparatus and method for changing alarm information based on weather, which can collect locations, time and weather information for a path, routinely used by a user, and a destination and actively adjust alarm time based on a weather condition, which can measure the gap between a weather forecast and real-time observation data, determine whether a gap notification condition has been satisfied and provide notification to a user, and which can collect location information and weather information via a report message, determine the urgency level of a disaster situation and generate a disaster information list that enables the disaster situation to be effectively determined.

Abstract: A method and system are provided. The method includes deriving a set of user attributes from an aggregate analysis of images and videos of a user. The deriving step includes recognizing, by a set of visual classifiers, semantic concepts in the images and videos of the user to generate visual classifier scores. The deriving step further includes deriving, by a statistical aggregator, the set of user attributes. The set of user attributes are derived by mapping the visual classifier scores to a taxonomy of semantic categories to be recognized in visual content. The deriving step also includes displaying, by an interactive user interface having a display, attribute profiles for the attributes and comparisons of the attribute profiles.

Abstract: Proposed are a method and device for constructing an event knowledge. The method comprises: identifying text to obtain an event mining candidate sentence; dividing the event mining candidate sentence into syntax fragments; generating an event knowledge instance according to the syntax fragments and a preset event knowledge construction, in which the number of the event knowledge instances is equal to the number of verb-object fragments and subject-predicate fragments in the syntax fragments; obtaining an event mining target sentence according to the verb-object fragments and the subject-predicate fragments in the syntax fragments, dividing the event mining target sentence, and writing divided members into an event knowledge instance correspondingly, so as to accomplish construction of the event knowledge base.

Abstract: A mechanism is provided in a data processing system for comparing similarity of questioning answer system ground truth answers to question answering system result answers. The mechanism receives question answering system results. The question answering system results comprise questions posed to the question answering system, answers returned by the question answering system for each question posed to the question answering system, and a confidence value for each answer. The question answering system is trained or tested using the ground truth questions and answers. The mechanism performs a matching operation comparing each result answer in the question answering system results to a corresponding ground truth answer. The matching operation is an asymmetric containment comparison and wherein the matching operation determines similarity of each result answer to the corresponding ground truth answer. The mechanism determines whether each result answer is right or wrong based on results of the matching operation.

Abstract: Methods and systems are provided for a tool that operates on a local user machine that is coupled to a remote storage. Data may be aggregated by the tool by combining raw data from multiple sources with different file types, where the data is stored in remote storage. Concepts and relationships existent within the inputted/loaded data may be learned by the tool. The data may be reconciled using the tool by a process of data scrubbing. The data may be analyzed using data manipulation techniques and statistical analysis. The work data flow from the data analysis may be captured by the tool and stored in the remote storage for later use. Visualizations (e.g., charts and graphs) may be generated by the tool for the analyzed data.

Abstract: Various embodiments of systems and methods for generating predictive models are described herein. A computer system deployed in a distributed may receive configuration data from multiple electronic devices. The system may select a set of configuration data with respect to a device category and a subcategory to generate a prediction model. The predictive model includes hypothesis, an average deviation and information pertaining to optimal configuration data for the given subcategory and the device category. The computer system may also receive monitoring requests from electronic devices and retrieve appropriate predictive model with respect to the device category and subcategory. The system may reconfigure the electronic device based on the retrieve predictive model.

Abstract: A method for global data flow optimization for machine learning (ML) programs. The method includes receiving, by a storage device, an initial plan for an ML program. A processor builds a nested global data flow graph representation using the initial plan. Operator directed acyclic graphs (DAGs) are connected using crossblock operators according to inter-block data dependencies. The initial plan for the ML program is re-written resulting in an optimized plan for the ML program with respect to its global data flow properties. The re-writing includes re-writes of: configuration dataflow properties, operator selection and structural changes.

Abstract: A method for selecting bit widths for a fixed point machine learning model includes evaluating a sensitivity of model accuracy to bit widths at each computational stage of the model. The method also includes selecting a bit width for parameters, and/or intermediate calculations in the computational stages of the mode. The bit width for the parameters and the bit width for the intermediate calculations may be different. The selected bit width may be determined based on the sensitivity evaluation.

Abstract: Described is a system for modeling probability matching in human subjects. Features related to probability matching are extracted from a set of human subject responses from behavioral tasks. Neural network model instances are trained on the set of features, resulting in a set of trained neural network model instances. A set of model parameters are derived from the set of trained neural network instances, and the set of derived model parameters are used to emulate human performance on novel data.

Abstract: A deep collaborative filtering (DCF) approach is employed in a recommender system to provide item recommendations to users. The DCF approach combines deep learning models with matrix factorization based collaborative filtering. To provide item recommendations, a user-item rating matrix, user side information, and item side information are provided as input to a recommender system. The recommender system learns user latent factors and item latent factors by jointly: (1) decomposing the user-item rating matrix to extract latent factors, and (2) extracting latent factors from hidden layers of deep learning models using the user side information and item side information. The learned user latent factors and item latent factors are used to predict item ratings for missing ratings in the user-item rating matrix. The predicted item ratings are then used to select item recommendations for a given user, which are then communicated to a user device of the user.

Abstract: An approach for dynamically providing a prioritized list of relevant cases includes a computer generating a set of tags for a case and retrieving a set of tags for completed cases. The approach includes the computer sorting the set of tags for the case and the set of tags for the completed cases into a set of tag types. The approach includes the computer determining a set of matching tags for each of the set of tag types between the case and completed cases. Furthermore, the approach includes the computer determining an ordered list of the completed cases. The ordered list is based, at least in part, on a number of matching tags in the set of matching tags corresponding to the completed case in the completed cases, and a number of matching tags in the set of matching tags in a tag type in the set of tag types.

Abstract: A method is used in managing knowledge-based authentication systems. A set of factors is evaluated for gathering organization based information from a set of information sources for authenticating a user in a knowledge-based authentication system. The organization based information is collected based on the evaluation.

Abstract: Methods, apparatus and computer program products for interactive reports are disclosed herein. In some examples, a method for generating an output report that is an interactive report may include identifying one or more messages to be hyperlinked in an output report, wherein the one or more messages are data structures that are configured to linguistically describe at least a portion of raw input data; determining one or more interactive responses based on the one or more messages to be hyperlinked; determining one or more words in a phrase specification that are related to the one or more messages to be hyperlinked; and generating the output report, wherein the one or more words are hyperlinked in the output report such that when selected at least one of the one or more interactive responses is performed.

Abstract: A device for estimating a deleted fluid consumption during a deletion phase, where said device comprises: a collection module configured to collect: a) first consumption data comprising information about the consumption of fluid from n fluid meters coming from a first group, and b) second consumption data comprising information about the consumption of fluid from m fluid meters coming from a second group, a computer analysis module which is configured for calculating, as a function of the first and second consumption data weighting coefficients ?i minimizing the distance between the fluid consumptions of the first and second groups, where i is a positive integer included between 1 and m.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may depend on user models, context information, preference information, and/or preference models.

Abstract: A platform and related components are provided for managing and executing various processes involving distributed, crowd and automated resources, including human and machine language-based translation, are described, including methods and systems for creating and intelligently distributing cognizable translation units among internal workers, outsourcing centers, and crowd workers and methods and systems for on-demand translation.