Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. A correlation table is constructed. Correlation values between each item and each context are then stored in then correlation table, wherein the correlations are used to recommend one or more of the items.

Abstract: Data relating to usage patterns of the user is stored, wherein the data includes an application portion having information as to items which were used and a context portion having information as to the context in which the items were used. The data is clustered into clusters of data points and centroid are computed, wherein the centroid includes an application portion and a context portion. Clusters similar to a current context of the user are selected by comparing a data point representing the current context of the user to the context portions of one or more of the centroids. For each of one or more items, a expectation value that the user wishes to use the corresponding item is computed, based on the application portions of the selected similar clusters, wherein the expectation values are used to recommend one or more of the items.

Abstract: Techniques for assessing the cost of allocation of execution and affecting the allocation of execution are disclosed. The cost of allocation of execution between a first computing device (e.g., mobile device) and one or more computing resource providers (e.g., Clouds) can be determined during runtime of the code. A computing system can operate independently of the first computing device and a computing resource provider and provide execution allocation cost assessment. Execution allocation cost can be assessed based on execution allocation data pertaining to the first computing device and computing resource providers. Power consumption of a mobile device can be used as a factor in determining how to allocate individual components of an application program between a mobile phone and a Cloud. In an Elastic computing environment, external computing resources can be used to extend the computing capabilities beyond that which can be provided by internal computing resources.

Abstract: An apparatus for controlling depth/distance of sound and method thereof are disclosed, by which an audio signal can be outputted to correspond to a depth of an image, i.e., a disparity in displaying a stereoscopic image. The present invention includes extracting at least one object from an image, measuring a depth change value in accordance with a motion of the object within the image, and changing a depth/distance level of the sound based on the depth change value of the object.

Abstract: A definition of a set of context variables to be considered is received, wherein the context variables represent categories of situations in which the computer system can be. A definition of a set of activities to be considered is also received, wherein the activities represent activities that can be performed using the computer system. For each context variable to be considered, a definition of a set of states to be considered is received, wherein the states represent situations in which the computer system can be. For each context variable to be considered, a specification of first probability distributions for each corresponding state is received. For each context variable to be considered, for each activity to be considered, a specification of second probability distributions to represent the likelihood of the activity being performed in the corresponding context is received. Usage data is generated using the first second probability distributions.

Abstract: Techniques for assessing the cost of allocation of execution and affecting the allocation of execution are disclosed. The cost of allocation of execution to or between a first computing device (e.g., a mobile device) and one or more computing resource providers (e.g., one or more Clouds) can be determined during runtime of the executable code. It will be appreciated that a computing system can operate independently of the first computing device and one or more computing resource providers and provide execution allocation cost assessment as a service to the first computing device and/or one or more computing resource providers. Execution allocation cost can be assessed (or determined) based on execution allocation data pertaining to the first computing device and/or one or more computing resource providers. By way of example, power consumption of a mobile device can be used as a factor in determining how to allocate individual components of an application program (e.g.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. A correlation table is constructed. Correlation values between each item and each context are then stored in then correlation table, wherein the correlations are used to recommend one or more of the items.

Abstract: In a first embodiment of the present invention, a method for automated creation of a mashup is provided, the method comprising: receiving data needs of a user; identifying sources of data to satisfy the data needs by comparing the data needs to available data sources; retrieving metadata relating to the identified sources of data from a source metadata store; identifying services to satisfy the data needs by comparing the retrieved metadata to available services; retrieving metadata related to the identified services from a service metadata store; and generating a plan for supplying data from the identified sources of data to the identified services based on the retrieved metadata from the source metadata source and the retrieved metadata from the service metadata source.

Abstract: An input situation can be represented by at least a first context variable. Data that includes interest values for multiple context variables can be provided and obtained. The obtained data can include a first data pertaining to the input situation and a second data pertaining to one or more other situations. It can be determined whether the first context variable is associated with a discrete range of values or a continuous range of values. At least a portion of data pertaining to the situations can be determined to be proximate data when the first context variable is associated with a continuous range of values. Based on the input situation and the proximate data, an interest value for the first input situation can be determined as a prediction of the interest in the input situation.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. A correlation table is constructed. Correlation values between each item and each context are then stored in then correlation table, wherein the correlations are used to recommend one or more of the items.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. The data is then clustered into input clusters of data points. It is determined if there are any input clusters that are similar to each other. Similar clusters are merged if there are any input clusters similar to each other. Any non-merged input clusters are divided into split clusters if the split clusters would not be similar to each other. The determining, merging, and dividing are then repeated using the merged, divided, and remaining unmerged and undivided clusters as input clusters.

Abstract: In one embodiment, a method for operating a local virtual world proxy is provided. A virtual world view is received corresponding to a virtual world client. Information about resources available to the virtual world client is obtained. Virtual representations of one or more resources available to a virtual world client are fetched. Then the virtual representations are injected into the virtual world view. The virtual world view is then forwarded to the virtual world client for display to a user of the virtual world client.

Abstract: In a first embodiment of the present invention, a method for automated creation of a mashup is provided, the method comprising: receiving data needs of a user; identifying sources of data to satisfy the data needs by comparing the data needs to available data sources; retrieving metadata relating to the identified sources of data from a source metadata store; identifying services to satisfy the data needs by comparing the retrieved metadata to available services; retrieving metadata related to the identified services from a service metadata store; and generating a plan for supplying data from the identified sources of data to the identified services based on the retrieved metadata from the source metadata source and the retrieved metadata from the service metadata source.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. The data is then clustered into clusters of data points. Then a centroid is determined for each of the clusters. A cluster similar to a current context of the user is selected by comparing a data point representing the current context of the user to one or more of the centroids. For each of one or more items, a threshold based on values for a plurality of the centroids with respect to the corresponding item, wherein a threshold is used to compare with centroid value of an item in a selected cluster to determine whether to recommend the item.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. The data is then clustered into clusters of data points. Then a centroid is determined for each of the clusters. A cluster similar to a current context of the user is selected by comparing a data point representing the current context of the user to one or more of the centroids. For each of one or more items, a threshold based on values for a plurality of the centroids with respect to the corresponding item, wherein a threshold is used to compare with centroid value of an item in a selected cluster to determine whether to recommend the item.

Abstract: In accordance with one aspect of the invention, web workers and local storages can be extended to a cloud-based environment. This allows web workers to be executed on any of a number of different cloud platforms located in a cloud, leveraging available resources to provide a quicker and more efficient processing environment for the various web workers. The present invention also provides these functionalities in a way that is transparent to not just the user, but also to the web page developer as well, eliminating the need for the web page developer to be aware of the cloud-based environment and design the web page for use therewith.

Abstract: Techniques for identifying potential communication uses of various systems are disclosed. Identifying potential communication uses of a computing system can improve the manner in which the computing system is used by allowing more intelligent decisions and better choices to be made regarding its communication use. By way of example, communication applications (or tasks or services) that are likely (or more likely) to be used by a person in a particular situation can be identified as potential communication use of a particular device. Such potential uses can, for example, be made more assessable (or more readily available) and/or effectively recommended (or automatically initiated), thereby allowing a person to more conveniently use the device. By way of example, identifying communication applications or tasks that are likely to be used by a person in a particular situation for various reasons (e.g., preferences and/or habits of a person in a particular situation) as potential communication use of a system (e.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. The data is then clustered into clusters of data points. Then a centroid is determined for each of the clusters. A cluster similar to a current context of the user is selected by comparing a data point representing the current context of the user to one or more of the centroids. For each of one or more items, a threshold based on values for a plurality of the centroids with respect to the corresponding item, wherein a threshold is used to compare with centroid value of an item in a selected cluster to determine whether to recommend the item.

Abstract: In one embodiment, data relating to usage patterns of the user is stored, wherein the data includes information as to items which were used and the context in which they were used. The data is then clustered into clusters of data points, wherein the number of data points per cluster is limited based on a preset value. Then a centroid is determined for each of the clusters. Clusters similar to the current context of the user are then selected by comparing a data point representing the current context of the user to one or more of the centroids. Then, for each of the one or more items, a probability that the user wishes to use the corresponding item is computed, based on the selected similar clusters, wherein the probabilities are used to recommend one or more of the items.

Abstract: Data relating to usage patterns of the user are stored. The data includes a context portion having information as to the context in which items were used and an interest rating portion indicative of an interest of the user in one or more objects of interest. The data is clustered into clusters of data points. For each of the clusters, a centroid is determined. The centroid includes a context portion and an interest rating portion. A current context of the user is received. Clusters are selected by comparing a data point representing the current context with the context portion of one or more centroids. Based on the selected clusters, an interest rating is computed. The computed interest rating indicates an interest of the user in one of the one or more objects of interest, given the current context.