Abstract: Embodiments of this application provide a method for making recommendations to a user and an apparatus, a computing device, and a storage medium. The method includes obtaining user attribute information, reading attribute information, reading history information, and candidate items; performing intra-group information fusion on the reading attribute information according to preset groupings to obtain reading feature information; obtaining a reading history weight according to the reading history information; obtaining history feature information according to the reading history weight and the reading history information; obtaining user feature information according to the user attribute information, the reading feature information, and the history feature information; and selecting a recommendation item from the candidate items according to the user feature information.

Abstract: The present disclosure provides a data processing method performed by an electronic device. The method includes: obtaining first and second service behavior features, and a service scenario feature of an object from service history data associated with the object; generating first and second service embedding vectors and a scenario representation vector according to the first and second service behavior features and the service scenario feature; obtaining first and second weights of the first and second service embedding vectors according to the scenario representation vector and the first and second service embedding vectors; generating first and second service feature vectors according to the first and second service embedding vectors and the first and second weights of the first and second service embedding vectors, respectively; and obtaining an object embedding vector according to the first service feature vector and the second service feature vector.

Abstract: The invention relates to aqueous composition comprising water-soluble glycerin-based polyalkylene glycols as synthetic base oils as well as the use of the composition and the glycerin-based polyalkylene glycols as or in metalworking fluids, wherein the glycerin was consecutively alkoxylated in the following order: first with propylene oxide, followed by ethylene oxide and finally with propylene oxide.

Abstract: This application provides an article recommendation method and apparatus, a computer device, and a storage medium.

Abstract: A method and an apparatus for processing web content, a device, and a computer storage medium are provided. A long-term feature group and a short-term feature group are determined from historical browsing data of a user according to generation time points of elements in the historical browsing data. A long-term encoding vector corresponding to the long-term feature group is determined according to similarities between elements in the long-term feature group, a user embedding vector corresponding to the short-term feature group is determined according to the long-term encoding vector and similarities between elements in the short-term feature group, and at least one web content is determined as a recommendation candidate and provided to the user.

Abstract: The invention relates to aqueous composition comprising water-soluble glycerin-based polyalkylene glycols as synthetic base oils as well as the use of the composition and the glycerin-based polyalkylene glycols as or in metalworking fluids, wherein the glycerin was consecutively alkoxylated in the following order: first with propylene oxide, followed by ethylene oxide and finally with propylene oxide.

Abstract: A video recommendation method is provided, including: inputting a video to a first feature extraction network, performing feature extraction on at least one consecutive video frame in the video, and outputting a video feature of the video; inputting user data of a user to a second feature extraction network, performing feature extraction on the discrete user data, and outputting a user feature of the user; performing feature fusion based on the video feature and the user feature, and obtaining a recommendation probability of recommending the video to the user; and determining, according to the recommendation probability, whether to recommend the video to the user.

Abstract: The present disclosure provides a data processing method performed by an electronic device. The method includes: obtaining first and second service behavior features, and a service scenario feature of an object from service history data associated with the object; generating first and second service embedding vectors and a scenario representation vector according to the first and second service behavior features and the service scenario feature; obtaining first and second weights of the first and second service embedding vectors according to the scenario representation vector and the first and second service embedding vectors; generating first and second service feature vectors according to the first and second service embedding vectors and the first and second weights of the first and second service embedding vectors, respectively; and obtaining an object embedding vector according to the first service feature vector and the second service feature vector.

Abstract: A method and an apparatus for processing web content, a device, and a computer storage medium are provided. A long-term feature group and a short-term feature group are determined from historical browsing data of a user according to generation time points of elements in the historical browsing data. A long-term encoding vector corresponding to the long-term feature group is determined according to similarities between elements in the long-term feature group, a user embedding vector corresponding to the short-term feature group is determined according to the long-term encoding vector and similarities between elements in the short-term feature group, and at least one web content is determined as a recommendation candidate and provided to the user.

Abstract: Embodiments of this application provide a method for making recommendations to a user and an apparatus, a computing device, and a storage medium. The method includes obtaining user attribute information, reading attribute information, reading history information, and candidate items; performing intra-group information fusion on the reading attribute information according to preset groupings to obtain reading feature information; obtaining a reading history weight according to the reading history information; obtaining history feature information according to the reading history weight and the reading history information; obtaining user feature information according to the user attribute information, the reading feature information, and the history feature information; and selecting a recommendation item from the candidate items according to the user feature information.

Abstract: A video recommendation method is provided, including: inputting a video to a first feature extraction network, performing feature extraction on at least one consecutive video frame in the video, and outputting a video feature of the video; inputting user data of a user to a second feature extraction network, performing feature extraction on the discrete user data, and outputting a user feature of the user; performing feature fusion based on the video feature and the user feature, and obtaining a recommendation probability of recommending the video to the user; and determining, according to the recommendation probability, whether to recommend the video to the user.

Abstract: This application provides an article recommendation method and apparatus, a computer device, and a storage medium.

Abstract: A method for creating a semantically aggregated index in an indexer-agnostic index building system includes: extracting documents from a data source, each document including a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: A computer program product for an indexer-agnostic index building system includes a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed on a computer, causes the computer to perform operations for creating a semantically aggregated index. The operations include: extracting documents from a data source, wherein each document includes a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: A method for updating a scalable row-store, including: receiving an update to a key within a range of keys in a database table, wherein the database table is distributed across nodes in a cluster of computing devices; and replicating the update over a group of the nodes using a consensus-based replication algorithm, wherein the replication algorithm includes completing the update in response to receiving acknowledgement messages from a majority of the nodes in the group indicating that the majority has received notification of the update.

Abstract: Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.

Abstract: A method for creating a semantically aggregated index in an indexer-agnostic index building system includes: extracting documents from a data source, each document including a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: A method for updating a scalable row-store, including: receiving an update to a key within a range of keys in a database table, wherein the database table is distributed across nodes in a cluster of computing devices; and replicating the update over a group of the nodes using a consensus-based replication algorithm, wherein the replication algorithm includes completing the update in response to receiving acknowledgement messages from a majority of the nodes in the group indicating that the majority has received notification of the update.

Abstract: Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.