摘要:
A method for determining user interests is provided, the method comprising: storing data items relating to usage patterns of the user, wherein the data items include an interest portion and a context portion; grouping the data items into context groups, each context group having data items with related context portions; for each context group, determining if the number of data items in the context group is greater than or equal to a first threshold; creating a first partition having context groups having a number of data items greater than or equal to the first threshold; averaging the ratings for interests in the data items in the context groups in the first partition, resulting in each context group in the first partition being a cluster; and deriving a user's interest by comparing a current context to a context group in the first partition.
摘要:
Techniques for determining an interest in an object of interest in a given situation are disclosed. Multiple situation-based interest rating components can be provided for various situations. Each situation-based interest rating component can include an interest value indicative of interest in an object of interest in one of the situations. An input situation can then be obtained. One of the situation-based interest rating components can be identified matching an input situation. The relevance of one or more of the other situation-based interest rating components to the identified matching component can then be determined. This can, for example, be done by computing one or more distances between only the respective situation-based portions of the matching situation-based interest rating component and one or more of the other components, or based on the interest value-based portion of each component, or both.
摘要:
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.
摘要:
A method for determining user interests is provided, the method comprising: storing data items relating to usage patterns of the user, wherein the data items include an interest portion and a context portion; grouping the data items into context groups, each context group having data items with related context portions; for each context group, determining if the number of data items in the context group is greater than or equal to a first threshold; creating a first partition having context groups having a number of data items greater than or equal to the first threshold; averaging the ratings for interests in the data items in the context groups in the first partition, resulting in each context group in the first partition being a cluster; and deriving a user's interest by comparing a current context to a context group in the first partition.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.g., computing and/or communication device) allows making the communications applications, tasks, or services more assessable and/or effectively recommending them for use in a particular situation.
摘要:
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.