Abstract: The present invention provides a method for identifying trends and correlation of content items characteristics in relation to user emotional reaction. The method comprising the steps of: receiving plurality of rating/votes originated by different users relating one or more content item, wherein the user is required to selection emotion icon from multiple choice emotion icons, analyzing statistics of users selections by identifying characteristics of the news/article item, including at least one of; timing of news item publication, subject of content item, source/writer of the content, context of the content, style of content, key words/image appearing in the content and identifying correlations of content item characteristics in relation user emotion reaction according to the said analysis identifying trends.

Abstract: A disclosed method may include receiving geographic coordinates of a location at which two parties are to rendezvous, generating a human-understandable geospatial descriptor for the request location, and sending the descriptor to respective devices of the two parties for presentation to the two parties. Generating the human-understandable geospatial descriptor may include identifying a human-visible feature in the vicinity of the request location that is labeled within available map data, selecting, based on a descriptor generation model, a reference expression relative to the identified feature, and applying a grammar-based constructor to the label and the selected reference expression to form the human-understandable geospatial descriptor. The model may be tuned using machine learning. The two parties may include a ride requestor and a ride provider in a ridesharing service. The identified feature may be a point of interest, landmark, street name, intersection, marker, or structure.

Abstract: A system and computer-implemented method is provided for a neural network for the optimal display of hotels on a graphical user interface. Computation is undertaken on a dataset wherein combinatorial complexity is reduced by obtaining a metric that can be a subset of a larger universe of user displays. A desired result set is obtained that can improve traveller satisfaction, travel agent revenues, and overall utility. This is accomplished by computing a first combination of displays, weighted as appropriate, and obtaining the results of an expression defined by factoring in a probability to sell a hotel based on a selected display on a user interface.

Abstract: A display method is provided. The method includes: acquiring media data within a collection range of a first acquisition device; determining a target object associated with the media data; determining associated data corresponding to the target object; and outputting the associated data corresponding to the target object to a user.

Abstract: Techniques for using different data sources for a predictive model are described. According to various implementations, techniques described herein enable different data sets to be used to generate a predictive model, while minimizing the risk that individual data points of the data sets will be exposed by the predictive model. This aids in protecting individual privacy (e.g., protecting personally identifying information for individuals), while enabling robust predictive models to be generated using data sets from a variety of different sources.

Abstract: Techniques for projecting household-level viewing events are described herein. Population data may be accessed including classes of a plurality of demographic attributes for households in a market. Representative household units (RHUs) may be generated, and the RHUs may be assigned a class for each of the demographic attributes and a quota based on the demographic attributes of a plurality of panelist households. Each of the panelist households may be assigned to one of the RHUs based on at least one panelist classes matching the classes for respective demographic attributes of the RHU, and the number of matching panelist households assigned to each of the RHU may be based on the quota. Panelist viewing data representing viewing events associated with the panelist household may be accessed. A report may be generated with the classes of the RHUs and the panelist viewing data of the assigned panelist households.

Abstract: Various systems and methods related to disaster recovery (DR). For example, one method involves automatically discovering infrastructure information for one or more assets located in one or more primary sites and/or one or more recovery sites. The method also involves storing the infrastructure information in a database. The method also involves generating DR configuration information.

Abstract: Techniques and arrangements for dynamically adjusting activity metrics and merchant states based, in part, on how many mobile electronic devices are currently located at the merchant. For example, if a number of mobile electronic devices is greater than a history of a number of devices, then it may be determined that the merchant is busy. If the number is less than the history of the number of devices, then it may be determined that the merchant is not busy.

Abstract: An approach is provided in which a system displays a user interface that includes cloud environment configuration parameters on a display. Each of the cloud environment configuration parameters is selectable by a user and corresponds to a new cloud environment. The system receives a set of user selections from the user that selects at least one of the cloud environment configuration parameters. Then, the system generates a recommended cloud profile based, at least in part, on the set of user selections, and configures the new cloud environment based on the recommended cloud profile.

Abstract: Methods, systems, and apparatus, including computer programs encoded on one or more computer storage devices, for training predictive models. Multiple training data records are received that each include an input data portion and an output data portion. A training data type is determined that corresponds to the training data. For example, a training data type can be determined by inputting the output data portions into one or more trained predictive classifiers. In other example, the training data type can be determined by comparison of the output data portions to data formats. Based on the determined training data type, a set of training functions are identified that are compatible with the training data of the determined training data type. The training data and the identified set of training functions are used to train multiple predictive models.

Abstract: The disclosed embodiments relate to a system that updates a context that facilitates evaluating qualitative search terms for an attribute during query processing. During operation, the system extracts a value for the attribute from each data item in a set of data items. Next, the system updates the context based on the extracted attribute values, wherein the context includes a concept-mapping for one or more qualitative search terms applied to the attribute, and wherein each concept-mapping associates a given attribute value with a numerical compatibility index that indicates a compatibility between the given attribute value and a corresponding qualitative search term.

Abstract: Techniques for detecting and correcting anomalies in computer-based reasoning systems are provided herein. The techniques can include obtaining current context data and determining a contextually-determined action based on the obtained context data and a reasoning model. The reasoning model may have been determined based on one or more sets of training data. The techniques may cause performance of the contextually-determined action and, potentially, receiving an indication that performing the contextually-determined action in the current context resulted in an anomaly. The techniques include determining a portion of the reasoning model that caused the determination of the contextually-determined action based on the obtained context data and causing removal of the portion of the model that caused the determination of the contextually-determined action, to produce a corrected reasoning model.

Abstract: A multivariate clustering-based anomaly detector can generate an event for consumption by an APM manager that indicates detection of an anomaly based on multivariate clustering analysis after topology-based feature selection. The anomaly detector accumulates time-series data across a series of time instants to form a multivariate time-series data slice or multivariate data slice. The anomaly detector then performs multivariate clustering analysis with the multivariate data slice. The anomaly detector determines whether a multivariate data slice is within a cluster of multivariate data slices. If the multivariate data slice is within the cluster and the cluster is a known anomaly cluster, then the anomaly detector generates an anomaly detection event indicating detection of the known anomaly. The anomaly detector can also determine that a multivariate data slice is within an unknown cluster and generate an event indicating detection of an unknown anomaly.

Abstract: Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.

Abstract: A system, method, and computer-readable medium for performing a domain specific evaluation operation comprising: storing domain specific data within a business query repository; determining and understanding variations within language for a domain specific category; performing a test planner operation on an identified NLP system, the test planner operation allowing a user to select a test plan to apply to the identified NLP system; and, evaluating the identified NLP system using a text planner output.

Abstract: A method, computer system, and a computer program product for migrating a service from one container to another container is provided. The present invention may include obtaining a first group of requests that are accessing a service launched in a first container instance and a second group of requests that are waiting for accessing the service. The present invention may also include generating a migrated service in a second container instance by migrating the service from the first container instance to the second container instance based on the obtained first and second groups of requests. The present invention may further include directing the second group of requests to the migrated service in the second container instance.

Abstract: A method, system and computer readable medium for generating a cognitive insight comprising: receiving information regarding a temporal sequence of events; performing a temporal topic machine learning operation on the temporal sequence of events; generating a cognitive profile based upon the information generated by performing the temporal topic machine learning operation; and, generating a cognitive insight based upon the cognitive profile generated using the temporal topic machine learning operation.

Abstract: A system and method of operation embeds a three-dimensional structure in a topology of an analog processor, for example a quantum processor. The analog processor may include a plurality of qubits arranged in tiles or cells. A number of qubits and communicatively coupled as logical qubits, each logical qubit which span across a plurality of tiles or cells of the qubits. Communicatively coupling between qubits of any given logical qubit can be implemented via application or assignment of a first ferromagnetic coupling strength to each of a number of couplers that communicatively couple the respective qubits in the logical qubit. Other ferromagnetic coupling strengths can be applied or assigned to couplers that communicatively couple qubits that are not part of the logical qubit. The first ferromagnetic coupling strength may be substantially higher than the other ferromagnetic coupling strengths.

Abstract: A system and method to configure a rule set used in connection with a medical monitoring system for monitoring patients and patient care equipment, especially medication delivery pumps, based on a variety of conditions and parameters associated with monitored biometric information and equipment information and for providing user-defined responses to those conditions and parameters.

Abstract: In some aspects, the described systems and methods provide for a method for training a model to predict survival time for a patient. The method includes accessing annotated pathology images associated with a first group of patients in a clinical trial. Each of the annotated pathology images is associated with survival data for a respective patient. Each of the annotated pathology images includes an annotation describing a tissue characteristic category for a portion of the image. Values for one or more features are extracted from each of the annotated pathology images. A model is trained based on the survival data and the extracted values for the features. The trained model is stored on a storage device.

Abstract: Techniques are provided for evolutionary computer-based optimization and artificial intelligence systems, and include receiving first and second candidate executable code (with ploidy of at least two and one, respectively) each selected at least in part based on a fitness score. The first candidate executable code and the second candidate executable code are combined to produce resultant executable code of the desired ploidy. A fitness score is determined for the resultant executable code, and a determination is made whether the resultant executable code will be used as a future candidate executable code based at least in part on the third fitness score. If an exit condition is met, then the resultant executable code is used as evolved executable code.

Abstract: A method for determining occupancy of a parking space using a heat map includes receiving sensor data from one or more sensors positioned such that a surface area is within a field of view, the sensor data at least indicating a speed and location of a traffic participant. Generating the heat map based on the traffic participant(s) and determining a heat index associated with each portion of the heat map. Determining a traffic participant is stopping, parking, or leaving a parking space based upon the change of speed movement between, high and low, and moving or parking, heat index portions.

Abstract: Systems and methods for concept based searching or recommendation based on a concept networks are disclosed. More particularly, embodiments of a concept based approach to the search and analysis of data, including the creation, update or use of concept networks in searching and analyzing data are disclosed, including embodiments of the usage of such concept networks in artificial intelligence systems that are capable of utilizing concepts expressed by users to return or evaluate associated entities or content.

Abstract: The disclosure notably relates to a computer-implemented method for forming a dataset. The dataset is configured for learning a function. The function takes as inputs images of instances of one or more classes of real objects. The method comprises, for each class, providing a parametric model of the class, generating a plurality of 3D modeled objects with the parametric model, and adding to the dataset, for each one of the plurality of 3D modeled objects, one or more corresponding images. The generating includes traversing one or more of the set of ranges. The method constitutes an improved solution for forming a dataset configured for learning a function.

Abstract: Embodiments of the present disclosure provide voice interaction method and device. The method includes: determining whether a first query statement currently received is a query statement first received within a preset time period; if not, obtaining a second query statement, where the second query statement is a query statement lastly received before receiving the first query statement; obtaining a third sentence vector according to a first sentence vector of the first query statement and a second sentence vector of the second query statement; and obtaining, from a bottom corpus, a first question and answer result corresponding to a fourth sentence vector a similarity between which and the third sentence vector satisfies a preset condition, and returning the first question and answer result. The method provided in the embodiment can return a bottom reply irrelevant to the query statement to the user, thereby improving the user experience.

Abstract: Techniques of intelligent management of calendar items in computing systems are disclosed herein. In one embodiment, a calendar server can be configured to determine whether to accept a requested meeting utilizing a decision tree pre-configured at the server by a service provider. The decision tree contains one or more hierarchical decision nodes individually comparing one or more of parameters provided by a meeting requester to a corresponding criterion previously provided by the service provider. The calendar server can also be configured to invoke an application identified in the decision tree and provide results of the invoked application to the meeting requester in lieu of accepting the requested meeting.

Abstract: There is provided a system and method of pre-processing discrete datasets for use in machine learning. The method includes: determining a median and a standard deviation of an input discrete dataset; determining a probability mass function including a probability of finding a particular data point in the input discrete dataset within a particular bin of a histogram representative of the input discrete dataset; transforming the probability mass function into a continuously differentiable probability density function using the standard deviation, the probability density function determined using a parametric control function, the parametric control function including a lognormal derivative of the probability density function, the parameters within the control function are estimated using optimization that minimizes a mean-squared error of an objective function; and outputting the probability density function for use an input to a machine learning model.

Abstract: A central authority receives a wake word associated with a service request from a user of a client device. The central authority sends the received wake word to a set of wake word engines. The central authority receives a signal from a selected wake word engine indicating that an assistant associated with the selected wake word engine has been selected by the user based on the received wake word. The central authority transmits a signal blocking the remainder of the wake word engines from receiving additional wake words, and sends the service request to the assistant. Responsive to the assistant receiving the service request, the central authority transmits a signal unblocking the remainder of the wake word engines from receiving wake words.

Abstract: Disclosed is a system and method for providing poll-based reviews of various businesses and service providers. In particular, a reviewer provides a review by answering poll-based review questions and/or adding new poll-based review questions to provide the most relevant feedback. The review questions can be ranked in order of relevance and/or importance to each reviewer. The data from the review is summarized and presented so that information related to each reviewee is presented in order of preference to the reviewer. Additionally, the present invention gathers data from each reviewer by using polls to tailor suggestions for new reviewees to the reviewer.

Abstract: [Object] To provide an information processing system and an information processing method capable of grasping propagation of acts in a society. [Solution] An information processing system including: a communication unit configured to acquire act information indicating occurrence of a first act from a first user to a second user; an accumulation unit configured to accumulate at least a user who has performed the act, a user influenced by the act, and a type of the act in units of acts in order of occurrence of the acts; and a control unit configured to, when a second act determined to have influenced the first act is found from among acts that are accumulated in the accumulation unit and from which the first user has received influence in past, perform control to record the first act and the second act in association with each other in the accumulation unit.

Abstract: Systems and methods for maintaining a current database of point of interest (POI) by automatically detecting a change associated with a POI based on cohort analysis are provided. A networked system accesses trip data associated with the POI. Using the analyzed trip data, the networked system generates a cohort associated with the POI. The networked system monitors for, and detects a change in, trip behavior in the cohort associated with the POI. In response to detecting the change in trip behavior, the networked system updates a database in a data store to indicate a status update.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed that involve a user profile based on clustering tiered descriptors. An example method includes grouping descriptors into a cluster of descriptors based on an association between the descriptors and each of a first item and a second item, accessing, via a user device, biometric data of a user, determining a first activity in which the user is engaged based on contextual data that correlates the cluster of descriptors with the biometric data of the user received from the user device via the network, generating a user profile based on the first activity of the user and the cluster of descriptors, and generating, in response to a second activity of the user matching the first activity associated with the cluster of descriptors within the user profile, a recommendation including a third item based on the user profile.

Abstract: Embodiments herein provide a method and system that determines an underlying social network from user interaction graphs based on mobile service usage and derive social influence scores for various contexts based on user interaction parameters. The present disclosure pertains to a method of determining social influence score for a user of a social network, said method comprising creating, using a social network analyzer, a social graph based on usage data generated by a plurality of users, said usage data being obtained from a mobile communication network, wherein vertices of the created social graph represent the plurality of users along with edge weights that are based on weighted linear or non-linear combinations of key performance indicators (KPIs) representing actions made by each user; and deriving, by the social network analyzer, influencer score for each user in the social graph based on user interactions from online social networks and mobile interaction patterns.

Abstract: The present disclosure provides a method, computer system and computer program product facilitating generation of a conversation content. A computer-implemented method comprises: obtaining, by a device operatively coupled to one or more processors, history conversation data of an user; determining, by the device, a professional level of the user based on the history conversation data; and generating, by the device, a conversation content for the user based on the professional level of the user.

Abstract: Dental images processed with artificial intelligence for e-commerce is described. In an example scenario, a processing device receives a dental image. The dental image is processed with a deep neural network and matched to anatomy and pathology datasets in real time. The matched and identified dental image is matched to a dental treatment recommendation dataset to further produce a real time dental product recommendation for a patient. One or more artificial intelligence entities may provide in real time dental treatment recommendations and/or real time dental product recommendations to a dental professional and/or an individual. The process may also produce a diagnostic treatment aid and/or a product recommendation such as an orthodontic aligner.

Abstract: In an example, a first graph representing a first set of combinations of computing elements and logical elements used in a computing environment is compared with a second set of combinations of computing elements and logical elements. The first set of combinations includes a plurality of element combinations. The comparison may be performed to identify a potentially faulty element combination among the first set of combinations.

Abstract: A form compliance manager configured to create a policy graph corresponding to an electronic image of an offline form and a corresponding instruction set. The form compliance manager further configured to generate an electronically fillable form corresponding to the offline form and including at least a first context cue for a first field in the electronically fillable form. The first context cue can be based on a subgraph of the policy graph associated with the first field, and the subgraph can include field completion information for the first field, field value information for the first field, and field format information for the first field. The electronically fillable form configured to present the first context cue in response to selection of the first field.

Abstract: Systems, methods, and devices, including computer-readable media, for reducing medication side effects using digital therapeutics. In some implementations, a system analyzes tracking data, user data, and medication data for various users to determine a degree to which different digital therapeutics program parameters reduce a likelihood or severity of undesired effects of medications. The system generates data that associates the parameters of the digital therapeutics programs with effects of the medications. The system receives data indicating a medication prescribed for a user of a mobile device and, based on the generated data, selects one or more digital therapeutics program parameters to activate or adjust a particular digital therapeutic program to provide interactions to the user.

Abstract: Data is classified using corrected semi-supervised data. Cluster centers are defined for unclassified observations. A class is determined for each cluster. A distance value is computed between a classified observation and each cluster center. When the class of the classified observation is not the class determined for the cluster center having a minimum distance, a first distance value is selected as the minimum distance, a second distance value is selected as the distance value computed to the cluster center having the class of the classified observation, a ratio value is computed between the second distance value and the first distance value, and the class of the classified observation is changed to the class determined for the cluster center having the minimum distance value when the computed ratio value satisfies a label correction threshold. A classification matrix is defined using corrected observations to determine the class for the unclassified observations.

Abstract: A method providing a computerized environment for human expert analyst community/ies including human expert analyst end users, including for at least one human expert analyst community: defining a prediction ontology stored in computer memory, including predetermined grammatical structure/s for predictions generated by human expert analysts in the community, the structure for conditional predictions including antecedent and consequence clauses; providing digitally represented analyst predictions, including individual analyst prediction/s expressed in the prediction ontology, being conditional, and associated with individual known network location/s from a universe thereof within the organization's computerized data network at which location, resource/s pertaining to the individual analyst prediction is stored; and generating and storing a uniform resource identifier-embedded prediction graph comprising: nodes which represent the analyst prediction's clauses, and at least one directional edge extending between

Abstract: Systems and methods for models utilizing siloed data are disclosed. For example, data stored with and/or available to one or more systems may be siloed such that it may not be aggregated and/or shared with other systems. The presently-disclosed systems and methods generate and utilize predictive layers and models to allow each system to predict outcomes using its own data and then models are shared between systems to allow each associated system to gain the benefits of the data of other systems without aggregating such data or otherwise sharing the data.

Abstract: A user performing a first process on a first computing device is detected. The first process includes one or more discrete tasks. A process flow graph, that is generated before performance of the first task, related to the first process is retrieved based on detection of the first process. A user action that relates to the one or more discrete tasks of the first process is identified based on the first process and based on the process flow graph. A current state of the first process is determined based on the first process and based on the process flow graph. A first video is generated based on the current state of the first process and based on the user action. The first video depicts one or more future actions that may be performed by the user to successfully perform the first process on the first computing device.

Abstract: A distributed computing device calculates word counts for each of a set of documents. The word counts are represented as values, each representing a number of times a corresponding word appears in one of the set of documents. The distributed computing device randomly samples the word counts to calculate sampled word counts. The distributed computing device and additional distributed computing devices iteratively execute a process to determine a consensus result for the sampled word counts based on the sampled word counts and additional sampled word counts calculated by the additional distributed computing devices. The distributed computing device determines a latent semantic index (LSI) subspace based on the consensus result for the sampled word count and reflecting contents of the set and additional sets of documents. The distributed computing device projects a document into the LSI subspace to determine the latent semantic content of the document.

Abstract: Systems, methods, and non-transitory computer readable media can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection. One or more ephemeral content item collections from the first ranking to provide in an ephemeral content feed of the user can be selected. A second ranking to rank each ephemeral content item collection of the plurality of ephemeral content item collections other than the selected ephemeral content item collections from the first ranking based on a probability of the user spending time on the ephemeral content item collection can be performed. One or more ephemeral content item collections from the second ranking to provide in the ephemeral content feed of the user can be selected.

Abstract: A method of identifying a root cause in a distributed computing environment is provided including collecting metric data of a plurality of application components, collecting metric correlation relationship data, collecting topology relationship data, and collecting transaction tracking relationship data that indicates a group of the application components used to execute a requested transaction. A graph is generated including a plurality of nodes corresponding to the application components by merging the metric correlation relationship data, the topology relationship data, and the transaction tracking relationship data. The nodes of the graph are traversed in an order based on a bi-directional weight for each of a plurality of edges connecting neighboring nodes among the plurality of nodes. A recommendation list is generated including at least one abnormal application component.

Abstract: Generally discussed herein are devices, systems, and methods for machine-learning. A method may include projecting an input feature vector of a first dimensional space into a second dimensional space to create a lower dimensional feature vector, the second dimensional space smaller than the first dimensional space, determining a first prediction vector for an internal node of the tree, determining whether to pass the first prediction vector to a first child or a second child of the internal node based on a sparse vector and the lower dimensional feature vector, determining a second prediction vector at a leaf node of the tree, and determining an overall prediction by combining the first and second prediction vectors.

Abstract: A system and method of managing a system include receiving data indicating problems in the system that includes at least one computer system. The method also includes generating a hypothesis of a correlation between two or more of the problems, and determining whether the hypothesis of the correlation is correct following a resolution of at least one of the two or more of the problems. The two or more of the problems are identified as a new combination problem based on determining that the hypothesis of the correlation is correct.

Abstract: A cognitive alteration system includes a storage unit at least to store one or more scripts, each to control a cognitive alteration process where the process comprises first and second in session media-based treatment processes and an out of session reinforcement stimulus process between the first and second in session processes, and where the storage unit stores both a script per in session process and a script per out of session process; a script handler at least to run at least one script; at least one of a wearable and a non-wearable element to sense an attribute of a subject or to provide an output to the subject during one of the in session and out of session processes; an information analyzer at least to perform analysis of the readings of the at least one element, an integrator to integrate the analysis and a script updater to update at least one of the scripts.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: A system and method for controlling the display of markup on a textual interface measures the difference between edited and unedited text, and utilizes values for hidden-copy tokens to create an incremental scale of values to generate different complexity levels of marked-up text to display on a user interface.