Abstract: Detecting a volumetric attack on a computer network with fewer false positives and while also requiring fewer processing resources is provided. The systems and methods described herein use observations taken at the network level to observe network traffic to form a predictive model for future traffic. When the network's future traffic sufficiently exceeds the predictive model, the monitoring systems and methods will indicate to the network to take security measures. The traffic to the network may be observed in subsets, corresponding to various groupings of sources, destinations, and protocols so that security measures may be targeted to that subset without affecting other machines in the network.

Abstract: A computerized method of classifying network accessible storage transactions at network accessible storage. The method comprises obtaining an client predictive security model for anomaly or malfunctioning detection, the client predictive security model is dynamically created by an analysis of a plurality of client transactions made to access target data stored in an client computing device, monitoring a plurality of network accessible storage transactions made to access a replica of the target data when the replica is stored in an network accessible storage, and classifying at least some of the plurality of network accessible storage transactions based on the client predictive security model.

Abstract: A query network is disclosed, comprising sets of nodes and edges connecting pairs of nodes. The nodes of the query network are associated with edge-defining queries. A method is taught for fully evaluating such a query network. A language is further disclosed for constructing queries. The query network may be used to model a social network, a professional network or the like.

Abstract: A recommendation system for recommending a target feature value for a target feature for a target deployment is provided. The recommendation system, for each of a plurality of deployments, collects feature values for the features of that deployment. The recommendation system then generates a model for recommending a target feature value for the target feature based on the collected feature values of the features for the deployments. The recommendation system applies the model to the features of the target deployment to identify a target feature value for the target feature. The recommendation system then provides the identified target feature value as a recommendation for the target feature for the target deployment.

Abstract: Data from social networking applications and other applications that can be used to communicate are combined for a user to generate a graph of the various relationships that the user has with other users in the social networking applications and other applications. In addition, the behaviors of each user with respect to communicating through the various social networking applications and other applications are monitored to generate task data that describes user preferences for communicating using each social networking application or other application for different tasks. At a later time, when a user is looking to connect with another user for an indicated task such as networking, the graph can be used to recommend paths to other users in the various social networking applications and other applications, and the generated task data can be used to rank the recommended paths based on the indicated task.

Abstract: A query network is disclosed, comprising sets of nodes and edges connecting pairs of nodes. The nodes of the query network are associated with edge-defining queries. A method is taught for fully evaluating such a query network. A language is further disclosed for constructing queries. The query network may be used to model a social network, a professional network or the like.

Abstract: Systems, methods, and media for proposing similar applications to a candidate application are provided. A similar results server may surface similar applications to a user of an application store. The applications can be selected based on similarity between features of the application. The features may be extracted from graphical user interface information rendered by a device that executes the applications. The applications that are identified as similar (e.g., based on the features) are displayed to the user.

Abstract: A network-accessible computer includes a network-communications interface, configured to receive health metrics of a user over a computer network. The network-accessible computer also includes a logic machine, which is configured to localize the user in a virtual space based on the health metrics, identify k nearest neighbors in the virtual space having k shortest Euclidean distances to the user, and generate a health insight comparing the user to the k nearest neighbors. The network-communications interface is further configured to send the health insight to a computing device associated with the user via the computer network.

Abstract: Aspects of the technology described herein provide a mechanism to authenticate a task request received by a personal digital assistant. The authentication mechanism improves security for transactions facilitated by the personal digital assistant. The authentication mechanism can also improve machine and user efficiency by streamlining a transaction process. In one aspect, the request is a verbal request made by a person and received by the personal digital assistant through a microphone. The personal assistant can generate an authentication questions using data from a semantic knowledge base accessible to the personal digital assistant.

Abstract: A method for managing communication among a plurality of social network members. The method comprises defining a multi participant task, setting at least one forward rule limiting the distribution an invitation message for participating in the multi participant task, forwarding the invitation message to at least one addressee from a plurality of social network members, allowing the at least one addressee to forward the invitation message to at least one additional addressee from the plurality of social network members under the at least one forward rule, monitoring a plurality of feedbacks to the invitation message to determine whether the multi participant task is achieved, and updating a status of the multi participant task according to the determination.

Abstract: Disclosed herein is a system and method for automatically identifying potential malware files or benign files in files that are not known to be malware. Vector distances for select features of the files are compared to vectors both known malware files and benign files. Based on the distance measures a malware score is obtained for the unknown file. If the malware score exceeds a threshold a researcher may be notified of the potential malware, or the file may be automatically classified as malware if the score is significantly high.

Abstract: A method for managing communication among a plurality of social network members. The method comprises defining a multi participant task, setting at least one forward rule limiting the distribution an invitation message for participating in the multi participant task, forwarding the invitation message to at least one addressee from a plurality of social network members, allowing the at least one addressee to forward the invitation message to at least one additional addressee from the plurality of social network members under the at least one forward rule, monitoring a plurality of feedbacks to the invitation message to determine whether the multi participant task is achieved, and updating a status of the multi participant task according to the determination.

Abstract: Disclosed herein is a system and method for generating a user profile for a user from multiple different data sources and providing recommendations to a user that are directed to benefiting the user and not benefiting a particular merchant or service provider. This disparate data is taken from multiple different data sources that are often competitors of one another. From the multiple data sources the same transaction or event can be determined and correlated with each other. This information is then processed to generate the user's profile which is used to generated recommendations for the user based on the user's needs. Recommendations that are presented can be positive or negative recommendations.

Abstract: A method includes acts for filtering auto consumption recommendations and auto consumption actions. The method includes receiving from a recommendation system, a recommendation of an asset for consumption. The asset for consumption is evaluated in the context of one or more filter rules regarding auto consumption. The filter rules are configured to filter recommended assets from being consumed when certain criteria are met or to permit recommended assets to be consumed when certain criteria are met. As a result, the method includes identifying one or more constraints on how recommended asset should be consumed. The method further includes filtering consumption of the recommended asset based on the one or more constraints.

Abstract: One or more web-behavior-augmented recommendation servers augment catalog interaction data between consumers and a catalog of products with collected online web behavior data associated with individual users. The online web behavior data represents online web behavior of the each consumer outside of the catalog of products and can improve the accuracy of product recommendations, which then be presented to an individual consumer via a computer user interface.

Abstract: Disclosed herein is a system and method for a system and method for determining whether the protection level of a protection system is appropriate for the way the user of a computing system is using the device. The protection system monitors the user's activity while they are using the various applications on the device. The protection system identifies an activity record that is the most similar to the user's activity and compares the current protection level with the associated record's protection level. The protection system may change the protection level when the user's protection level and the associated record's protection level are different.

Abstract: Disclosed herein is a system and method for automatically identifying potential malware files or benign files in files that are not known to be malware. Vector distances for select features of the files are compared to vectors both known malware files and benign files. Based on the distance measures a malware score is obtained for the unknown file. If the malware score exceeds a threshold a researcher may be notified of the potential malware, or the file may be automatically classified as malware if the score is significantly high.

Abstract: Systems, methods, and media for proposing similar applications to a candidate application are provided. A similar results server may surface similar applications to a user of an application store. The applications can be selected based on similarity between features of the application. The features may be extracted from graphical user interface information rendered by a device that executes the applications. The applications that are identified as similar (e.g., based on the features) are displayed to the user.

Abstract: Disclosed herein is a system and method for identifying features of items that are more relevant for making recommendations to consumers for content that they may be interested in. The system determines the similarity between items that are recommend and items in the user's history and compares that similarity measure to the similarity measure calculated for a random item on the same features. From this similarity measure the relative impactfullness of a particular feature on a recommendation can be determined.

Abstract: Disclosed herein is a system and method for generating a user profile for a user based on the way the user interacts with consumable content in an application, such as an electronic book in an e-reader. The actions of the user with regards to the content are monitored and the associated with characteristics of the content. This association is used to build the user's profile of their likes and dislikes which are then provided to a recommender system to provide more relevant and personalize recommendations.