Abstract: The present invention leverages analysis methods, such as expected value of information techniques, rate-based techniques, and random selection technique, to provide a fusion of low-level streams of input data (e.g., raw data) from multiple sources to facilitate in inferring human-centric notions of context while reducing computational resource burdens. In one instance of the present invention, the method utilizes real-time computations of expected value of information in a greedy, one-step look ahead approach to compute a next best set of observations to make at each step, producing “EVI based-perception.” By utilizing dynamically determined input data, the present invention provides utility-directed information gathering to enable a significant reduction in system resources. Thus, of the possible input combinations, the EVI-based system can automatically determine which sources are required for real-time computation relating to a particular context.

Abstract: Provided are systems and/or methods that facilitate sensing, detecting, logging, or treatment of a condition or need of a living body using a controlled parasite.

Abstract: A system and method for generating, managing and accessing a schema that facilitates maximizing utility of a managed communication is provided. The system provides a computer-based system for creating, accessing and/or managing a schema employed in utility-optimizing communication management. The system includes computer components for receiving communication related data and storing such communication related data, inferences concerning such data, probabilities and/or probability distributions associated with such data in an extensible, portable, data schema. The schema can facilitate making utility optimizing communication management decisions.

Abstract: Pre-computing a portion of forecasted workloads may enable load-balancing of data center workload, which may ultimately reduce capital and operational costs associated with data centers. Computing tasks performed by the data centers may be analyzed to identify computing tasks that are eligible for pre-computing, and may be performed prior to an actual data request from a user or entity. In some aspects, the pre-computing tasks may be performed during a low-volume workload period prior to a high-volume workload period to reduce peaks that typically occur in data center workloads that do not utilize pre-computation. Statistical modeling methods can be used to make predictions about the tasks that can be expected to maximally contribute to bottlenecks at data centers and to guide the speculative computing.

Abstract: Techniques and systems are provided that work to minimize the energy usage of computing devices by building and using models that predict the future work required of one or more components of a computing system, based on observations, and using such forecasts in a decision analysis that weighs the costs and benefits of transitioning components to a lower power and performance state. Predictive models can be generated by machine learning methods from libraries of data collected about the future performance requirements on components, given current and recent observations. The models may be used to predict in an ongoing manner the future performance requirements of a computing device from cues. In various aspects, models that predict performance requirements that take into consideration the latency preferences and tolerances of users are used in cost-benefit analyses that guide powering decisions.

Abstract: Embodiments for interacting with cloud computing providers are disclosed. In accordance with at least one embodiment, a resource broker receives a request for a computing task that is to be performed from a customer. The resource broker selects one of the cloud computing providers to perform at least a part of the computing task. In turn, the resource broker may obtain a gain from performance of the at least one part of the computing task by the cloud computing provider.

Abstract: Embodiments for generating and implementing collaborative plans that achieve goals for sets of individual agents based on a consideration of individual and group preferences are disclosed. In accordance with at least one embodiment, a collaborative mechanism includes receiving individual plan preferences of agents via one or more client devices and modeling agent costs based on the received individual plan preferences. One or more collaborative plans are then be generated based on the modeled agent costs and one or more agents may be grouped into each collaborative plan. The one or more generated collaborative plans are provided to the agents via the one or more client devices for implementation. Finally, payments are distributed among the agents to compensate at least one agent for participation in one of the generated collaborative plans.

Abstract: The present invention relates to a system and methodology to enable a plurality of information associated with electronic messages to be automatically prioritized by a message urgency system for transmittal to a user or system. The message urgency system can employ classifiers that can be explicitly and/or implicitly trained to prioritize or triage one or more received messages according to a learned importance to the user. An adaptable and configurable graphical user interface is provided in order to manage the prioritized information. The interface facilitates system personalization according to user desires of how messages are received and subsequently processed by the user. Display and input adjustments are provided in a plurality of selectable pages to enable the personalization of the system. Display options include status and summary views of various configuration and adjustment options that alter the characteristics of how messages are presented to the user.

Abstract: The present invention relates to a system and methodology to facilitate multiattribute adjustments and control associated with messages and other communications and informational items that are directed to a user via automated systems. An interface, specification language, and controls are provided for defining a plurality of variously configured groups that may attempt to communicate respective items. Controls include the specification of priorities and preferences as well as the modification of priorities and preferences that have been learned from training sets via machine learning methods. The system provides both a means for assessing parameters used in the control of messaging and communications and for the inspection and modification of parameters that have been learned autonomously.

Abstract: A sensing and context management architecture that can detect that a user is interacting with a given device and in an associated context, and in response thereto, manages device processes as the user moves from device to device, location to location, and/or context to context. The invention comprises a system that facilitates management of a user situation or context. A sensing component is provided that senses a context of a user by way of one or more sensors and/or a particular device with which the user is interacting in the context, for example, and a management component that manages the device and/or one or more services in the context according to rules or inferences user preferences, sensed observations, and user input data.

Abstract: A system that facilitates analyzing time-related data comprises an interface component that receives a packet of information that includes a plurality of predictions and timing information associated therewith. A time-analysis component communicatively coupled to the interface component compares the timing information associated with the plurality of predictions with a current time and makes a determination relating to output of at least one of the plurality of predictions based at least in part upon the comparison.

Abstract: A system that employs an explicitly and/or implicitly trained model in order to return entity-specific computer-based search results is provided. The innovation can provide for a customized search model that focuses search in connection with achieving information that is meaningful with respect to goals of an entity. The model can be used to modify a search query in accordance with a goal of the entity or to generate the search query thereby returning meaningful and/or targeted results to the user. The system can automatically gather entity-related data thereafter determining or inferring a goal as well as training the model. Moreover, the system can selectively configure (e.g., order, rank, filter) and render results to a user based upon the model.

Abstract: A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile.

Abstract: Methods and architectures for context-sensitive reminding and service facilitating are disclosed. The architectures monitor user context and activity, senses or infers relevant reminders, goals, such as those that come from a growing need of the user that should be fulfilled, and computes best reminders, and recommend plans on fulfilling need(s) in an optimum way. Statistical models of a user's knowledge and recall in different settings may be employed. Facilities, services, and merchants can be identified along a route that the user can take, and cost-benefit analysis is performed for determining which merchant(s) to select to fulfill the need(s). Routes may be created as opportunistic modifications of trips underway. Merchants can respond back with offers of sale to the user for all available needed items, and the user can respond with acceptance or denial of the offers. Merchants can also respond in a bidding fashion in order to gain user's patronage.

Abstract: A system and method for inferring informational goals and preferred level of details in answers in response to questions posed to computer-based information retrieval or question-answering systems is provided. The system includes a query subsystem that can receive an input query and extrinsic data associated with the query and which can output an answer to the query, and/or rephrased queries or sample queries. The query subsystem accesses an inference model to retrieve conditional probabilities that certain informational goals are present. One application of the system includes determining a user's likely informational goals and then accessing a knowledge data store to retrieve responsive information. The system includes a natural language processor that parses queries into observable linguistic features and embedded semantic components that can be employed to retrieve the conditional probabilities from the inference model.

Abstract: A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile.

Abstract: A route planning system comprises a receiver component that receives a request for directions between a beginning point and a destination point. An analysis component analyzes a traffic system representation that varies as context varies and outputs expected amounts of travel time between the beginning point and the destination point for multiple contexts based at least in part upon the analysis. A method is described herein that includes techniques for searching over routes and trip start times simultaneously so as to identity start times and routes associated with maximal expected value, or equivalently minimum expected cost, given preferences encoded about one or more of the leaving time, the travel time, and the arrival time.

Abstract: The claimed subject matter provides systems and/or methods that facilitate diversifying search results to improve searching and/or personalized searching. An interface component can receive a query. Additionally, a result diversification component can modify diversity of a set of search results obtained by a search engine in response to a query based at least in part upon one or more dimensions of diversity. The dimensions of diversity can include document topic, document type, document genre, domain of document, document age, location associated with the document, commercial characteristics of the document, user intent, and the like.

Abstract: The present invention is related to a system and method of considering time segments or intervals in a collaborative filtering model. The present invention extends collaborative filtering approaches by integrating considerations of temporality into the training and/or vote input associated with the usage of collaborative filtering models. The present invention also applies filtering to the output with temporal models, so as to view a most appropriate subset of recommended content, centering on content that may be available at a target time. The present invention applies time to a collaborative filtering model by allowing weight to be associated with selections within a current time segment, selections historically watched within the current time segment by the user and selections historically watched within the current time segment by a large group of users.

Abstract: A system for optimizing the value of communications between communicating parties is provided. The system includes a communication group manager that facilitates specifying policies, preferences and/or automated analysis of ideal communication channels, routing and/or scheduling in terms of communicating party groups that can be pre-populated clusters of communicating parties, assembled based on relationships (e.g., organizational), and/or assembled based on satisfying inclusion criteria (e.g., age, location, competence, communication history, meeting history). The communication group manager maps communicating parties into predefined and/or dynamically created groups that facilitate specifying and/or automatically computing ideal communication actions like selecting a channel, displaying lists of potential channels sorted by communicating party preferences, and (re)scheduling communications to different channels and/or times.