Abstract: Methods, systems and computer program products are disclosed for detecting patterns in a data stream that match multi-pattern rules. One embodiment of the invention provides a method of recognizing a specified group of patterns in a data stream. The method comprises identifying a rule for said specified group of patterns in the data stream, and using a first array of finite state machines to scan the data stream for at least some of the patterns in the specified group. For patterns in the specified group that are found in the data stream by the first array of finite state machines, pattern identifiers are sent to a second array of finite state machines. The second array of finite state machines determines if the specified group of patterns is in the data stream in accordance with the identified rule by, at least in part, using said pattern identifiers.

Abstract: A social networking system receives messages from users that include hashtags. The social networking system may use a natural language model to identify terms in the hashtag corresponding to words or phrases of the hashtag. The words or phrases may be used to modify a string of the hashtag. The social networking system may also generate computer models to determine likely membership of a message with various hashtags. Prior to generating the computer models, the social networking system may filter certain hashtags from eligibility for computer modeling, particularly hashtags that are not frequently used or that more typically appear as normal text in a message instead of as a hashtag. The social networking system may also calibrate the computer model outputs by comparing a test message output with outputs of a calibration group that includes positive and negative examples with respect to the computer model output.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, a synthesis engine having a controller, and a storage medium for storing instructions to be executed by the controller. The instructions, when executed by the controller, can cause the controller to retrieve collected information associated with a behavior of an individual, synthesize from the information a measure of a mood of the individual to interact with others, and transmit the measure to a system associated with the individual to manage requests between the individual and the entity. The measure of the mood of the individual can indicate an availability of the individual and a receptiveness of the individual to accept a request to interact with an entity. The measure can be described by a plurality of dimensions. Other embodiments are disclosed.

Abstract: Training a machine to provide specialized health care apparatus may include receiving text describing a user's health condition via a user interface. Text may be converted into corresponding medical terms. A database may be searched for a list of health care providers treating health conditions associated with the medical terms. A machine learning model may be built that may include user preference for a predefined set of features associated with the user's health condition and health care provider preference for the predefined set of features in treating the user's health condition. The machine learning model may predict one or more of the health care providers that provide treatment for the user's health condition that matches the user's preference. The machine learning model may be retrained based on one or more of feedback from the user, the health care providers, and updated traits of the users and the health care providers.

Abstract: A mechanism is provided for identifying a set of top-in clusters from a set of top-k plans. A planning problem and an integer value k indicating a number of top plans to be identified are received. A set of top-k plans are generated with at most size k, where the set of top-k plans is with respect to a given measure of plan quality. Each plan in the set of top-k plans is clustered based on a similarity between plans such that each cluster contains similar plans and each plan is grouped only into one cluster thereby forming the set of top-m clusters. A representative plan from each top-m cluster is presented to the user.

Abstract: A mechanism is provided for identifying a set of top-m clusters from a set of top-k plans. A planning problem and an integer value k indicating a number of top plans to be identified are received. A set of top-k plans are generated with at most size k, where the set of top-k plans is with respect to a given measure of plan quality. Each plan in the set of top-k plans is clustered based on a similarity between plans such that each cluster contains similar plans and each plan is grouped only into one cluster thereby forming the set of top-m clusters. A representative plan from each top-m cluster is presented to the user.

Abstract: A social networking system selects a subset of keywords from a set of master keywords found in user profiles. The method includes selecting a first and second group of user profiles including one or more keywords and computing the number of occurrences of each of the master keywords in the first and second group of profiles. A value may be computed for each of the master keywords based on a comparison of the number of occurrences in the first group of profiles and the number of occurrences in the second group of profiles. The computed value may be used for selecting the subset of keywords from the master keywords and/or ranking the master keywords.

Abstract: A management system and method for remediating poor-performing clients running in a distributed computer system uses a machine learning technique to automatically detect one or more poor-performing clients among a plurality of clients running in the distributed computer based on at least performance data and resource usage data of the clients. An action is then initiated to mitigate the effects of the poor-performing clients.

Abstract: Methods, apparatuses, and computer readable mediums for exercise behavior prediction are provided. In a particular embodiment, the prediction evaluation controller is configured to generate an exercise activity pattern based on correlations between scheduling of a user's historical non-exercise events and the user's historical exercise events. In the particular embodiment, the prediction evaluation controller is also configured to generate, based on the generated exercise activity pattern, by the prediction evaluation controller, a future exercise event to correspond with a future non-exercise event scheduled on the user's calendar. In the particular embodiment, the prediction evaluation controller is also configured to provide an indication of the generated future exercise event.

Abstract: A method, devices, computer program products and an internet service is disclosed for adapting a context model. In the method a media clip is received. Also sensor data captured at least partly when the media clip was captured is received. A context is derived using a context model based at least partly on the sensor data and an indication on the context is provided to a user by receiving a search query having at least one context-related search criterion, deriving a similarity between the context and the at least one context-related search criterion and causing at least a part of the media clip to be presented as a response to the search query. Feedback on the relevance of the context is received from the user. Based on the feedback, the context model may then be adapted.

Abstract: A computer implemented method for generating a set of updates for a database comprising multiple records including erroneous, missing and inconsistent values, the method comprising using a set of partitioning functions for subdividing the records of the database into multiple subsets of records, allocating respective ones of the records to at least one subset according to a predetermined criteria for mapping records to subsets, applying multiple machine learning models to each of the subsets to determine respective candidate replacement values representing a tuple repair for a record including a probability of candidate and current values for the record, computing probabilities to select replacement values for the record from among the candidate replacement values which maximise the probability for values of the record for an updated database.

Abstract: Systems and methods are provided for automatically adjusting content composition rules based on evaluation of user feedback information obtained through a haptic interface. For example, a method includes accessing user feedback information collected by a haptic interface executing on a computing device, wherein the user feedback information comprises information indicative of a user's reaction towards digital content rendered by the computing device. The digital content includes content that is automatically generated using content composition rules. The method further includes evaluating a quality of the digital content based on the user feedback information, generating an evaluation report that includes information regarding the quality of the digital content, and adjusting one or more content composition rules based on the evaluation report.

Abstract: Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Abstract: A method for transforms input signals, by first defining a model for transforming the input signals, wherein the model is specified by constraints and a set of model parameters. An iterative inference procedure is derived from the model and the set of model parameters and unfolded into a set of layers, wherein there is one layer for each iteration of the procedure, and wherein a same set of network parameters is used by all layers. A neural network is formed by untying the set of network parameters such that there is one set of network parameters for each layer and each set of network parameters is separately maintainable and separately applicable to the corresponding layer. The neural network is trined to obtain a trained neural network, and then input signals are transformed using the trained neural network to obtain output signals.

Abstract: An online system extracts features from an application linked to the online system. The application is used by users of the online system and posts content to the online system. A trained model is applied to the extracted features to generate a quality score for the application. The trained model is trained using features extracted from a set of training applications and quality scores manually assigned to the training applications, wherein the manually assigned quality scores indicate whether each training application satisfies a set of criteria and the generated quality score represents a probability of the application satisfying the set of criteria. Based on the quality score, content provided by the application is ranked for presentation to a user of the online system in relation to other content of the online system. The online system presents the content provided by the application to the user according to the ranking.

Abstract: A social networking system receives messages from users that include hashtags. The social networking system may use a natural language model to identify terms in the hashtag corresponding to words or phrases of the hashtag. The words or phrases may be used to modify a string of the hashtag. The social networking system may also generate computer models to determine likely membership of a message with various hashtags. Prior to generating the computer models, the social networking system may filter certain hashtags from eligibility for computer modeling, particularly hashtags that are not frequently used or that more typically appear as normal text in a message instead of as a hashtag. The social networking system may also calibrate the computer model outputs by comparing a test message output with outputs of a calibration group that includes positive and negative examples with respect to the computer model output.

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: At least one rule specification is received for a graph-based computation having data processing components connected by linking elements representing data flows. The rule specification defines rules that are each associated with one or more rule cases that specify criteria for determining one or more output values that depend on input data. A transform is generated for at least one data processing component in the graph-based computation based on the received rule specification, including providing an interface for configuring characteristics of a log associated with the generated transform. At least one data flow is transformed using the generated transform, including: tracing execution of the data processing components in the graph-based computation at run time, generating log information based on the traced execution according to the configured log characteristics, and storing or outputting the generated log information.

Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a case from a user, determining a level of sophistication of the user, determining a level of sophistication associated with each of a plurality of items of supporting evidence in a corpus of information, selecting a subset of the plurality of items of supporting evidence based on the determined levels of sophistication, and returning the selected subset to the user as part of a response to the case.