Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: Method, apparatus, system, computer program product and computer readable medium are disclosed for recommending content to a plurality of users. Each of the users is associated with a user score. The method comprises determining a recommending score for an item of content at least partly based on a user's promotion of the item and the user score of the promoting user; recommending the item according to its recommending score; and adjusting the user score of the promoting user based on other users' feedback with respect to the item promoted by said user.

Abstract: Methods for rapidly determining earthquake parameters of an earthquake include inputting a seismogram of the earthquake, searching concurrently in pre-established historical seismogram database and theoretical seismogram database by use of an approximate nearest neighbor search method, to find a set of seismograms similar to the input seismogram according to a preset similarity condition, and determining from the set of similar seismograms one or more seismograms matched with the input seismogram, and determining the earthquake parameters from the matched seismograms. With the present invention, it is possible to search in millions of seismograms and determine parameters for an earthquake in a few second, and thus realize rapid and even real-time estimation of earthquake parameters.

Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: An approach is provided for a holistic framework to model user item rating with user generated tag information. A tagging manager determines one or more tags associated with one or more items, wherein the one or more tags are generated by one or more users. The tagging manager processes and/or facilitates a processing of the one or more tags to cause, at least in part, a generation of one or more semantic spaces. The one or more semantic spaces and/or one or more semantic concepts within the one or more semantic spaces represent one or more groupings of the one or more tags. The tagging manager determines one or more probability parameters that the one or more tags, the one or more users, the one or more items, or a combination thereof are associated with respective ones of the one or more semantic concepts in the semantic spaces.

Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: Methods for rapidly determining earthquake parameters of an earthquake include inputting a seismogram of the earthquake, searching concurrently in pre-established historical seismogram database and theoretical seismogram database by use of an approximate nearest neighbor search method, to find a set of seismograms similar to the input seismogram according to a preset similarity condition, and determining from the set of similar seismograms one or more seismograms matched with the input seismogram, and determining the earthquake parameters from the matched seismograms. With the present invention, it is possible to search in millions of seismograms and determine parameters for an earthquake in a few second, and thus realize rapid and even real-time estimation of earthquake parameters.

Abstract: Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.

Abstract: Product recommendation is disclosed, including retrieving user behavior data associated with a predetermined statistical period; sorting the user behavior data into one or more groups of data corresponding to one or more types of products based at least in part on associated product identifiers; determining a plurality of interest levels associated with the predetermined statistical period for at least one or more groups of data; determining a plurality of purchase peak probabilities using at least the plurality of interest levels, wherein a purchase peak probability is associated with a predicted likelihood of user interest in receiving recommendations associated with a type of product; ranking at least a portion of the plurality of purchase peak probabilities in response to receipt of an indication to present recommendation information; and presenting recommendation information based at least in part on the ranked at least portion of the plurality of purchase peak probabilities.