Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: Disclosed examples can relate to obtaining identifications of content (e.g., content recommendations) while keeping at least some interaction data locally private. For a given user and device, content items for which the user may have an affinity can be predicted based on the interactions of the user with other content items. Respective interaction data for respective content items can stay local to the user device by transforming the respective content items into content codes (e.g., determined based on a codebook generated by clustering perceptual values). The affinity for content codes can be transmitted to the server for use in determining identifications of content items to provide to the device.

Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: Methods, systems and computer program products are provided for summarizing user activity associated with media content by accessing a taste profile containing a representation of media content activity corresponding to at least one of a plurality of items, generating at least one statistic corresponding to the media content activity, and generating a taste profile attribute by using the at least one statistic.

Abstract: A catalog record is bridged to information stored in at least one inverted index by receiving an application user interface call associated with a predetermined filter request including a record identifier identifying a record in a relational database. A bitset is generated based on item identifiers in the record. The bitset is applied to at least one inverted index to obtain metadata associated with the item identifiers.

Abstract: Methods, systems and computer program products for clustering pages into headline clusters are provided by collecting web data, identifying pages from the web data, tokenizing unique words in each page, recognizing unique entities in each page, detecting media links in each page, and constructing a plurality of vector representations of each page. A first dimension of each vector representation includes the unique words tokenized in each page, a second dimension of each vector representation includes the unique entities recognized in each page, and a third dimension of each vector representation includes the media links detected in each page. The vector representations are, in turn, clustered.

Abstract: Methods, systems and computer program products are provided for providing content recommendation by obtaining metadata associated with a media object, extracting from the metadata a plurality of terms associated with the media object, and mapping at least a portion of the plurality of terms to buckets. A query vector having attributes corresponding to the buckets is used to perform a query on a database storing media object documents having attributes corresponding to the buckets.

Abstract: A data processing method, program, and apparatus for identifying a document within a block of text. A block of text is tokenized into a plurality of text tokens according to at least one rule parser. Each of the plurality of text tokens is sequentially compared to a plurality of document tokens to determine if the text token matches one of the plurality of document tokens. The plurality of document tokens correspond to a plurality of documents which have been tokenized according to the one or more rule parsers. Each matched text token is filtered according to predetermined filtering criteria to generate one or more candidate text tokens. It is then determined whether sequence of candidate text tokens that occur in sequential order within the block of text match sequence of document tokens. If so, then it is determined that the document has been identified within the block of text. The document can correspond to an artist, a song names, and misspellings and aliases thereof.

Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: A data processing method, program, and apparatus for identifying a document within a block of text. A block of text is tokenized into a plurality of text tokens according to at least one rule parser. Each of the plurality of text tokens is sequentially compared to a plurality of document tokens to determine if the text token matches one of the plurality of document tokens. The plurality of document tokens correspond to a plurality of documents which have been tokenized according to the one or more rule parsers. Each matched text token is filtered according to predetermined filtering criteria to generate one or more candidate text tokens. It is then determined whether sequence of candidate text tokens that occur in sequential order within the block of text match sequence of document tokens. If so, then it is determined that the document has been identified within the block of text. The document can correspond to an artist, a song names, and misspellings and aliases thereof.

Abstract: A data processing method, program, and apparatus for identifying a document within a block of text. A block of text is tokenized into a plurality of text tokens according to at least one rule parser. Each of the plurality of text tokens is sequentially compared to a plurality of document tokens to determine if the text token matches one of the plurality of document tokens. The plurality of document tokens correspond to a plurality of documents which have been tokenized according to the one or more rule parsers. Each matched text token is filtered according to predetermined filtering criteria to generate one or more candidate text tokens. It is then determined whether sequence of candidate text tokens that occur in sequential order within the block of text match sequence of document tokens. If so, then it is determined that the document has been identified within the block of text. The document can correspond to an artist, a song names, and misspellings and aliases thereof.

Abstract: Methods, systems and computer program products for clustering pages into headline dusters are provided by collecting web data, identifying pages from the web data, tokenizing unique words in each page, recognizing unique entities in each page, detecting media links in each page, and constructing a plurality of vector representations of each page. A first dimension of each vector representation includes the unique words tokenized in each page, a second dimension of each vector representation includes the unique entities recognized in each page, and a third dimension of each vector representation includes the media links detected in each page. The vector representations are, in turn, clustered.

Abstract: Methods, systems and computer program products are provided for predicting data. A name or title is obtained from a taste profile. There is an index into a data set based on the name or title, and a set of terms and corresponding term weights associated with the name or title are retrieved. A sparse vector is constructed based on the set of terms and term weights. The sparse vector is input to a training model including target data. The target data includes a subset of test data which has a correspondence to a predetermined target metric of data. A respective binary value and confidence level is output for each term, corresponding to an association between the term and the target metric.

Abstract: Methods, systems and computer program products are provided for providing content recommendation by obtaining metadata associated with a media object, extracting from the metadata a plurality of terms associated with the media object, and mapping at least a portion of the plurality of terms to buckets. A query vector having attributes corresponding to the buckets is used to perform a query on a database storing media object documents having attributes corresponding to the buckets.

Abstract: The present disclosure generally relates to the providing of media content, e.g. audio content in the form of music. More particularly, the present disclosure relates to systems, methods, computer server systems and electronic devices for playback of streamed media content. A visual array of one or several media options that correspond to one or more proposed media playlists can be provided at the user interface of the electronic devices. This makes it possible to facilitate the browsing, and thus the selection, of media content. The one or more proposed media playlists are based on previously played media and, accordingly, the proposed media playlists become personalized to fit the taste of the user of the electronic device.

Abstract: Methods, systems and computer program products are provided for providing content recommendation by obtaining metadata associated with a media object, extracting from the metadata a plurality of terms associated with the media object, and mapping at least a portion of the plurality of terms to buckets. A query vector having attributes corresponding to the buckets is used to perform a query on a database storing media object documents having attributes corresponding to the buckets.

Abstract: Methods, systems and computer program products are provided for predicting data. A name or title is obtained from a taste profile. There is an index into a data set based on the name or title, and a set of terms and corresponding term weights associated with the name or title are retrieved. A sparse vector is constructed based on the set of terms and term weights. The sparse vector is input to a training model including target data. The target data includes a subset of test data which has a correspondence to a predetermined target metric of data. A respective binary value and confidence level is output for each term, corresponding to an association between the term and the target metric.

Abstract: A data processing method, program, and apparatus for identifying a document within a block of text. A block of text is tokenized into a plurality of text tokens according to at least one rule parser. Each of the plurality of text tokens is sequentially compared to a plurality of document tokens to determine if the text token matches one of the plurality of document tokens. The plurality of document tokens correspond to a plurality of documents which have been tokenized according to the one or more rule parsers. Each matched text token is filtered according to predetermined filtering criteria to generate one or more candidate text tokens. It is then determined whether sequence of candidate text tokens that occur in sequential order within the block of text match sequence of document tokens. If so, then it is determined that the document has been identified within the block of text. The document can correspond to an artist, a song names, and misspellings and aliases thereof.