Abstract: The privacy-preserving cookie generator implementations described herein create a privacy-preserving data structure (also called a privacy-preserving cookie herein) that is used to provide personalization for online services without user tracking. In some implementations the privacy-preserving cookie generator encodes a user profile (for example, based on a user's online activity) into a data structure that has naturally occurring noise and that efficiently supports noise addition. In one implementation a Bloom filter is used to create the encoded profile. Additional noise is injected into the encoded profile to create an obfuscated user profile in the form of a privacy-preserving data structure. The privacy-preserving data structure or cookie can be attached to an online service request and sent over a network to an online service provider which can use it fulfill the services request, providing a somewhat personalized result while the user's privacy is maintained.

Abstract: A “Context-Aware Crowdsourced Task Optimizer” provides various processes to optimize task recommendations for workers in mobile crowdsourcing scenarios by automatically identifying and recommending bundles of tasks compatible with workers' contexts (e.g., worker history, present or expected locations, travel paths, working hours, skill sets, capabilities of worker's mobile computing devices, etc.). The Context-Aware Crowdsourced Task Optimizer bundles tasks to both maximize expected numbers of completed tasks and to dynamically price tasks to maximize the system's utility, which is a function of task values and task completion rates. Advantageously, the resulting task identification and recommendation process incentivizes individual workers to perform more tasks in a shorter time period, thereby helping tasks to complete faster, even with smaller budgets.

Abstract: Technologies related to crawling computer-executable applications are described. A full crawl is executed over an application, where executing the full crawl includes causing the application to output a plurality of pages. The application retrieves content from the World Wide Web when generating the pages for output. Thereafter, a fast crawl is executed over the application, where executing the fast crawl takes less time when compared to the time needed to execute the full crawl.

Abstract: Technologies related to crawling computer-executable applications are described. A full crawl is executed over an application, where executing the full crawl includes causing the application to output a plurality of pages. The application retrieves content from the World Wide Web when generating the pages for output. Thereafter, a fast crawl is executed over the application, where executing the fast crawl takes less time when compared to the time needed to execute the full crawl.

Abstract: The privacy-preserving cookie generator implementations described herein create a privacy-preserving data structure (also called a privacy-preserving cookie herein) that is used to provide personalization for online services without user tracking. In some implementations the privacy-preserving cookie generator encodes a user profile (for example, based on a user's online activity) into a data structure that has naturally occurring noise and that efficiently supports noise addition. In one implementation a Bloom filter is used to create the encoded profile. Additional noise is injected into the encoded profile to create an obfuscated user profile in the form of a privacy-preserving data structure. The privacy-preserving data structure or cookie can be attached to an online service request and sent over a network to an online service provider which can use it fulfill the services request, providing a somewhat personalized result while the user's privacy is maintained.

Abstract: Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules without initializing sensor procedures as a result of the request.

Abstract: A “Context-Aware Crowdsourced Task Optimizer” provides various processes to optimize task recommendations for workers in mobile crowdsourcing scenarios by automatically identifying and recommending bundles of tasks compatible with workers' contexts (e.g., worker history, present or expected locations, travel paths, working hours, skill sets, capabilities of worker's mobile computing devices, etc.). The Context-Aware Crowdsourced Task Optimizer bundles tasks to both maximize expected numbers of completed tasks and to dynamically price tasks to maximize the system's utility, which is a function of task values and task completion rates. Advantageously, the resulting task identification and recommendation process incentivizes individual workers to perform more tasks in a shorter time period, thereby helping tasks to complete faster, even with smaller budgets.

Abstract: Methods, systems, and computer storage media for detecting anomalies within nodes of a data center are provided. A self-learning system is employed to proactively and automatically detect the anomalies using one or more locally hosted agents for pulling information that describes states of a plurality of nodes (e.g., computing devices of a cloud-computing infrastructure), respectively, and using at least one early-warning mechanism for implementing a comparison technique. The comparison technique involves individually comparing the state information of the plurality of the nodes against one another and, based upon the comparison, grouping one or more nodes of the plurality of nodes into clusters that exhibit substantially similar state information. Upon identifying the clusters that include low number of nodes grouped therein, with respect to a remainder of the clusters of nodes, the members of the identified clusters are designated as anomalous machines.

Abstract: Magnetic stripe-based transaction enabled mobile communication device embodiments are presented which generally involve a mobile communication device which has been configured to perform transactions that heretofore were completed using a magnetic stripe found on magnetic-stripe cards. In one general embodiment, a mobile communication device generates magnetic stripe data which is used to perform a magnetic stripe-based transaction. To this end, the mobile communication device includes a magnetic stripe device and a computing device. The computing device stores the magnetic stripe data, and the magnetic stripe device is employed to transfer the stored magnetic stripe information so that it can be used to conduct transactions as if a traditional magnetic stripe card were being used.

Abstract: Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules without initializing sensor procedures as a result of the request.

Abstract: Technologies related to crawling computer-executable applications are described. A full crawl is executed over an application, where executing the full crawl includes causing the application to output a plurality of pages. The application retrieves content from the World Wide Web when generating the pages for output. Thereafter, a fast crawl is executed over the application, where executing the fast crawl takes less time when compared to the time needed to execute the full crawl.

Abstract: Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules. If the inferred value of the target context cannot be determined, the method further includes executing a first step of a sensing plan for acquiring an inferred value of the target context using a rule-based acquisition planner, as well as executing any of a number of subsequent steps of the sensing plan until the inferred value of the target context is obtained.

Abstract: The claimed subject matter provides systems and/or techniques that facilitate and/or effectuate efficient stream sharing for multi-user sensor data collection. The system includes mechanisms that locate within a query a specification that includes spatial regions over which data is required, based on the spatial regions the mechanism determines which sensors are situated within the region or ascertains which of the sensors in the region is actively streaming data and/or has persisted data in order to fulfill the query, constructs or utilizes a directed acyclic graph to obviate redundancy in a functional requirement included in the specification and imposed by the query, and formulates a result in fulfillment of the query that is delivered to an application.

Abstract: Methods, systems, and computer storage media for detecting anomalies within nodes of a data center are provided. A self-learning system is employed to proactively and automatically detect the anomalies using one or more locally hosted agents for pulling information that describes states of a plurality of nodes (e.g., computing devices of a cloud-computing infrastructure), respectively, and using at least one early-warning mechanism for implementing a comparison technique. The comparison technique involves individually comparing the state information of the plurality of the nodes against one another and, based upon the comparison, grouping one or more nodes of the plurality of nodes into clusters that exhibit substantially similar state information. Upon identifying the clusters that include low number of nodes grouped therein, with respect to a remainder of the clusters of nodes, the members of the identified clusters are designated as anomalous machines.

Abstract: Methods and systems for rule-based context acquisition are disclosed herein. The method includes accepting a request for target context from an application at a context acquisition system and identifying context rules relating to the target context using a rule-based inference cache. The method also includes determining an inferred value of the target context based on previously-acquired contexts and the context rules. If the inferred value of the target context cannot be determined, the method further includes executing a first step of a sensing plan for acquiring an inferred value of the target context using a rule-based acquisition planner, as well as executing any of a number of subsequent steps of the sensing plan until the inferred value of the target context is obtained.

Abstract: A “Portable Card Generator” is implemented within a portable device, such as a mobile phone, and provides various techniques for writing secure account information from user selected accounts to a “wildcard” having rewritable magnetic stripes, rewritable RFID tags, and/or rewritable smartcard circuitry. The account information is retrieved by the portable device from local or remote stores of user accounts. Once that account information is written, the wildcard is then available for immediate use for credit card or debit-type payments, loyalty card use, etc. Consequently, by providing a credit card sized object having a rewriteable magnetic stripe, RFID tag, and/or smartcard circuitry, in combination with account information for various credit cards, debit cards, consumer loyalty cards, insurance cards, ID cards or badges, etc., the user is no longer required to physically carry those cards in order to use the corresponding accounts within existing card-based infrastructures.

Abstract: Magnetic stripe-based transaction enabled mobile communication device embodiments are presented which generally involve a mobile communication device which has been configured to perform transactions that heretofore were completed using a magnetic stripe found on magnetic-stripe cards. In one general embodiment, a mobile communication device generates magnetic stripe data which is used to perform a magnetic stripe-based transaction. To this end, the mobile communication device includes a magnetic stripe device and a computing device. The computing device stores the magnetic stripe data, and the magnetic stripe device is employed to transfer the stored magnetic stripe information so that it can be used to conduct transactions as if a traditional magnetic stripe card were being used.

Abstract: Techniques are described herein for privately aggregating distributed time-series data. A requestor provides a query sequence to users. Each user evaluates the query sequence on the user's time-series data to determine an answer sequence. Each user transforms its answer sequence to another domain, adds noise, and encrypts it for further processing by the requestor. The requestor combines these encrypted sequences in accordance with a homomorphic encryption technique to provide an encrypted summation sequence. The requestor provides the encrypted summation sequence to at least some of the users, who may in turn provide respective decryption shares to the requestor. The requestor combines the decryption shares in an effort to decrypt the encrypted summation sequence. Decrypting the encrypted summation sequence provides a summation of the encrypted sequences from the users, which may be transformed back to the original domain to estimate a summation of the answer sequences of the users.

Abstract: Techniques are described herein for privately aggregating distributed time-series data. A requestor provides a query sequence to users. Each user evaluates the query sequence on the user's time-series data to determine an answer sequence. Each user transforms its answer sequence to another domain, adds noise, and encrypts it for further processing by the requestor. The requestor combines these encrypted sequences in accordance with a homomorphic encryption technique to provide an encrypted summation sequence. The requestor provides the encrypted summation sequence to at least some of the users, who may in turn provide respective decryption shares to the requestor. The requestor combines the decryption shares in an effort to decrypt the encrypted summation sequence. Decrypting the encrypted summation sequence provides a summation of the encrypted sequences from the users, which may be transformed back to the original domain to estimate a summation of the answer sequences of the users.

Abstract: The claimed subject matter provides systems and/or techniques that facilitate and/or effectuate efficient stream sharing for multi-user sensor data collection. The system includes mechanisms that locate within a query a specification that includes spatial regions over which data is required, based on the spatial regions the mechanism determines which sensors are situated within the region or ascertains which of the sensors in the region is actively streaming data and/or has persisted data in order to fulfill the query, constructs or utilizes a directed acyclic graph to obviate redundancy in a functional requirement included in the specification and imposed by the query, and formulates a result in fulfillment of the query that is delivered to an application.