Abstract: A system for an interactive political platform includes a computing device configured to produce a user signature, identify a political alignment as a function of the user signature, wherein identifying a political agreement further comprises receiving an ethical set, identifying the political alignment as a function of the ethical set and the user signature using an alignment machine-learning model, determine a representative index as a function of the user political alignment, wherein determining the representative index further comprises receiving a bureaucratic indicator, and determining the representative index as a function of the bureaucratic indicator, and transmit a notification to a user as a function of the representative index.

Abstract: A database system enumerates one-column candidate referential integrities (1CRIs) from a plurality of input columns in one or more relations. The database system applies one or more disqualification tests to the 1CRIs to eliminate illegitimate 1CRIs resulting in a list of non-disqualified 1CRIs, wherein the disqualification tests are applied to an 1CRI being tested (hereinafter (A*,B*), A* representing a set of values of a referenced column or columns and B* representing a set of values of a referencing column or columns) until (A*,B*) is disqualified or until all of the disqualification tests have been executed and (A*,B*) has not been disqualified, in which case (A*,B*) is added to the list of non-disqualified 1CRIs, wherein each of the disqualification tests reduces the likelihood of incorrectly adding (A*,B*) to the list of non-disqualified 1CRIs.

Abstract: Systems and methods are disclosed for determining an engagement level of a user interacting with an electronic program, comprising receiving or determining a decision node tree, each node in the decision node tree corresponding to a user decision point in the electronic program, determining a number of levels in the decision node tree, determining a user traversed count comprising a number of levels the user has traversed in the decision node tree, and determining the engagement level of the user with the electronic program based upon the user traversed count and the number of levels in the decision node tree.

Abstract: The detection device (10) has the signal processing unit (154) and the estimation unit (155). The signal processing unit (154) updates the evaluation value of the vertex of the graph by belief propagation, on the basis of the matrix generated using the argument on the complex plane expressing the direction of the side of the graph in which at least some vertices are labeled. The estimation unit (155) estimates a label of a vertex of the graph on the basis of the evaluation value.

Abstract: A graph-based data privacy compliance solution is disclosed. In various embodiments, a privacy graph database based at least in part on an associated privacy graph model is used to store private information of a person, including by including in the privacy graph database a node representing a critical data element comprising the private information of the person.

Abstract: In an example embodiment, data in a multi-tenant database is organized as a graph representing the relationships among all documents and tenants. Specifically, each document is represented as a node in the graph and each tenant also is represented as a node. The relationships between the documents themselves, or between a document and a graph, are then represented as edges in the graph. A list of tenants whose data should be marked for deletion (e.g., former customers who no longer have a relationship with the entity maintaining the database) may be maintained. Periodically (e.g., once a week), this list of tenants and the relationship graph are fed as input into a graph search algorithm that generates smaller relationship graphs comprised only of documents associated with those accounts.

Abstract: A method for edge profiling within a data graph measures the impact that a particular type of edge has on a data graph. A list of all edges contained within a single connected component within the graph is generated in order to search for bridges across connected subcomponents. The process is implemented as two MapReduce jobs on separate compute clusters. The first job is the edge profile job, which is implemented as a Map-only job. The second job reads the output of the first, and builds multiple in-memory data structures representing each connected component within the data graph. After the graph is created, it is traversed to find bridges.

Abstract: The present disclosure relates to a method of generating, by a terminal, an integrated graph using a distributed graph including: receiving source node information from a user; identifying, by a graph types module, a location of a graph database related to a type of a source node based on the source node information; requesting, by a graph manager module, graph data to an application corresponding to the location of the graph database; receiving the graph data from the application; and integrating, by a graph integration module, a node and an edge based on the source node and the graph data to generate the integrated graph.

Abstract: Rules based semantic map sharding is proposed. A method of handling semantic objects for semantic map sharding makes used of rules to define which semantic objects are to be included in a shard. Hereto, semantic objects are defined in a geographical area to be contained in shard data. For the semantic objects, a set of rules is defined comprising a definition of which semantic objects are to be combined into a shard data entry of the shard data and which semantic objects are to be stored in separate shard data entries.

Abstract: Aspects of the current subject matter are directed to a user-facing approach for migration of unstructured data. A graphical user interface is provided to enable a user to execute a migration process of attachments between content repositories, where the execution is end to end with simple commands and/or user actions through interaction with the graphical user interface. The commands and/or user actions are translated into a background execution of the steps of the migration process in the proper order with proper parameters. Aspects of the current subject matter provide for the migration process to be transparent to the end user. Logs or reports relating to the migration process may be available and accessible to the user.

Abstract: In one embodiment, a method includes, by one or more computing devices, receiving, from a client system of a first user of an online social network, a text post inputted by the first user, parsing the text post to identify a query associated with the text post, sending, to the client system, instructions for presenting a confirmation prompt requesting confirmation of the identified query from the first user, receiving, from the client system, a confirmation of the identified query from the first user, generating, in response to receiving the confirmation, a recommendation list responsive to the query, wherein the recommendation list comprises references to one or more objects referenced in one or more prior comments associated with one or more prior posts of the online social network associated with the query, and sending, to the client system, instructions for presenting the recommendation list to the first user.

Abstract: In an example embodiment, a deep learning model is used to learn embedding representations of a heterogeneous information network, where the embedding represents entity-specific properties and network environment properties. Position-aware embeddings specific to the heterogeneous information network may be used as input features of the deep learning model. Furthermore, meta-path embedding specific to the heterogeneous information network may also be used as input features of the deep learning model. Modified embedding propagation methods are further designed to explore better ways to capture network meta-path properties.

Abstract: Techniques described herein allow a user of an RDBMS to specify a graph algorithm function (GAF) declaration, which defines a graph algorithm that takes a graph object as input and returns a logical graph object as output. A database dictionary stores the GAF declaration, which allows addition of GAFs without changing the RDBMS kernel. GAFs are used within graph queries to compute output properties of property graph objects. Output properties are accessible in the enclosing graph pattern matching query, and are live for the duration of the query cursor execution. According to various embodiments, the declaration of a GAF includes a DESCRIBE function, used for semantic analysis of the GAF, and an EXECUTE function, which defines the operations performed by the GAF. Furthermore, composition of GAFs in a graph query is done by supplying, as the input graph argument of an outer GAF, the result of an inner GAF.

Abstract: Embodiments are for generating a digital signature of a query execution plan using similarity hashing. A technique includes generating a node digital signature for nodes in a query and generating an edge digital signature for edges in the query, the edges connecting the nodes. The technique includes selecting at least one previously executed query based on the node digital signature and the edge digital signature for the query and causing the query to be processed according to an assignment associated with the at least one previously executed query.

Abstract: A social networking application provides for automated link and/or content recommendation to users of a social media platform by automated social graph refinement that augments a baseline social graph with predicted links and inferred labels by iteratively (a) propagating attribute labels through optimizing attribute label similarity between user nodes constrained by closeness of links between the users, and (b) predicting links between users through optimizing link closeness constrained by label similarity. Each label inference iteration is based on predicted labels generated in and immediately prior link prediction iteration, and each link prediction iteration is based on inferred labels generated in and immediately prior label inference iteration.

Abstract: Systems, apparatuses, and methods are provided herein for tracking data lineage. A method for tracking data lineage comprises detecting, with a data lineage recorder module, an execution of a task of a workflow by a workflow engine on a device, the workflow comprises a plurality of ordered tasks, detecting, with a data lineage proxy, a request sent from the device, selecting, with the data lineage recorder module, request lineage data items associated with the task from a content of the request, associating, in a data lineage database, the request lineage data items with the task, and generating a data lineage graph comprising representations of the plurality of ordered tasks of the workflow including the task and the request lineage data items associated with the task.

Abstract: A discussion support device acquires, via a communication network, a plurality of comments relating to a main topic of a discussion, extracts a plurality of ideas, a plurality of favorable points, a plurality of unfavorable points, and a plurality of issues from the acquired plurality of comments, identifies a topology between the extracted plurality of ideas, plurality of favorable points, plurality of unfavorable points, and plurality of issues, and creates a facilitation structure to realize the identified topology.

Abstract: A computing system obtains a first article about a first topic, where the first article references a plurality of entities including a person. The computing system identifies the person as a dominant entity of the first article. The computing system determines whether the first article expresses negative sentiment based upon content of the first article. In accordance with a determination that the first article does not express negative sentiment, the computing system retrieves a uniform resource locator (URL) of a webpage about a second topic that is of interest to the first person. Upon receiving a request for the first article from a computing device, the computing system causes the first article and a link to be concurrently displayed on a display, where the URL of the webpage is embedded in the link.

Abstract: A system for loading graph data from an external store in response to a graph query is disclosed. In some embodiment, given a graph database where all vertices are stored in memory and some but not all edges are stored in the external store, the system performs one of two methods. In the first method, the system iteratively expands a set of vertices that is initially specified in the graph query and collects all edges connected to the set of vertices, including edges stored in the external store, that satisfy a vertex constraint also specified in the query. In the second method, the system finds a set of vertices that satisfy the vertex constraint and collects all edges connected to the set of vertices, including edges stored in an external store.

Abstract: A unified graph query system provides an abstraction layer that increases the interoperability of different graph technologies by exposing graphs stored in graph databases using a unified query language. The abstraction layer generates graph models for each of the available graph databases and extracts a graph component and other source data used to identify the source of the data requested by a query. The unified graph query system executes the query across the multiple graphs included in different graph databases by using the graph models to locate the graph component in each of the multiple graphs and extract the feature data associated with the graph component. The feature data is used to generate features that are used by a machine learning service to train machine learning models and is also used to make predictions in real time.

Abstract: The present disclosure provides techniques for extracting structural information using machine learning. One example method includes receiving electronic data indicating one or more pages, constructing, for each page of the one or more pages, a tree based on the page, wherein each level of the tree includes one or more nodes corresponding to elements in a level of elements in the page, encoding, for each page of the one or more pages, a value of each node of the tree for the page into a vector using a first machine learning model, sampling a plurality of pairs of vectors from the one or more trees for the one or more pages, wherein a given pair of vectors corresponds to values of nodes in a same tree, training a second machine learning model using the plurality of pairs, and combining each vector with weights of the second machine learning model.

Abstract: Methods for cascade elimination of candidates in spatial relation operations are performed by systems, devices, and apparatuses. Spatial relation operations include counts of geometric objects against geographies/geometries, and data points associated with vertices of shapes representing the geographies/geometries are reduced to form smaller sets of data points that represent the initial shapes. Elimination of geometric objects for operations is performed using inner- and outer-reductions in cascade. Data points are reduced until a representation of the original shape with a specified area or number of data points is generated. Multi-polygon geometries are joined by union based on preservation of area and data points of the polygons therein prior to reducing data points. Cascade reductions are also performed at specified times during spatial operations based on costs associated therewith.

Abstract: Systems and methods to monitor veracity of a collection of one or more profiles associated with a user.

Abstract: Methods, systems, and computer program products for accelerating inference of transformer-based models are provided herein. A computer-implemented method includes obtaining a machine learning model comprising a plurality of transformer blocks, a task, and a natural language dataset; generating a compressed version of the machine learning model based on the task and the natural language dataset, wherein the generating comprises: obtaining at least one set of tokens, wherein each token in the set corresponds to one of the items in the natural language dataset, identifying and removing one or more redundant output activations of different ones of the plurality of transformer blocks for the at least one set of tokens, and adding one or more input activations corresponding to the one or more removed output activations into the machine learning model at subsequent ones of the plurality of the transformer blocks; and outputting the compressed version of the machine learning model to at least one user.

Abstract: A platform-agnostic input system can render a multiuser input board user interface element at one or more frontends to collect input from multiple users simultaneously. The platform-agnostic input system can maintain an object graph based on positions of objects added to the multiuser input board. The platform-agnostic input system can select branches of the object graph and determine which among a set of platforms in a multiplatform computing system to associate with the data associated with each node of that branch of the object graph.

Abstract: The present disclosure includes an object to acquire information indicating a tendency on a visit spot for each vehicle sort. The present disclosure provides an information processing apparatus including a controller configured to execute: acquiring first information about a plurality of vehicles, the first information including vehicle information about a vehicle, the first information not being capable of identifying an individual user or an individual vehicle but reflecting at least part of attributes or preferences of a user associated with the vehicle, and spot information about a visit spot of the vehicle; and acquiring tendency information indicating a tendency on the visit spot of the vehicle for each vehicle classification based on the vehicle information, from the first information about the plurality of vehicles.

Abstract: Various embodiments of the present disclosure relate to a computer-implemented method, a system, and a storage medium, where a graph stored in a computing system is logically divided into subgraphs, the subgraphs are stored on different interconnected (or coupled) devices in the computing system, and nodes of the subgraphs include hub nodes connected to adjacent subgraphs. Each device stores attributes and node structure information of the hub nodes of the subgraphs into other devices, and software or hardware prefetch engine on the device prefetches attributes and node structure information associated with a sampled node. A prefetcher on a device interfacing with the interconnected (or coupled) devices may further prefetch attributes and node structure information of nodes of the subgraphs on other devices. A traffic monitor is provided on an interface device to monitor traffic. When the traffic is small, the interface device prefetches node attributes and node structure information.

Abstract: Methods, computer readable media, and devices for securely managing interactions between distributed components are provided. One method may include generating a first interaction identifier based on a first component identifier and data to be shared with a second component, storing the first interaction identifier in an interaction data store of the first component, sending a request to the second component including the first component identifier, the first interaction identifier, and the data to be shared with the second component, creating a graph node in an interaction relationship data store based on the first interaction identifier, receiving a response from the second component including a second component identifier, a second interaction identifier, and response data, and adding a relationship edge in the interaction relationship data store connecting the graph node based on the first interaction identifier with a graph node based on the second interaction identifier.

Abstract: A method, apparatus, system, and computer program code for retrieving data records. A set of static configuration objects is provided, including: a set of resources that describe available data items, and a set of views that express a serialized transformation of resources objects into a response. In response to receiving a data request, a computer system generates a data fetch execution plan from the set of resources and the set of views. The data fetch execution plan is generated using an executor adapted to a particular data store and set of performance requirements. The computer system retrieves the data records according to the data fetch execution plan.

Abstract: A method for policy-based analytics includes retrieving, from a graph database, first data representing a first entity in a computing environment, a second entity in the computing environment, and an event associated with the first entity and the second entity; predicting, according to a risk indicator model, a risk associated with the first entity based at least in part on the event; and updating the graph database to include second data representing the risk and a risk indicator. The first and second entities are stored as properties of a first vertex and a second vertex, respectively, and the event is stored as a property of an edge between the first vertex and the second vertex. The risk indicator is stored as a property of a third vertex. The risk is stored as a property of an edge between the first vertex and the third vertex.

Abstract: Provided are systems and methods for personalizing website content configured for delivery to a user. An exemplary system includes a graph database for storage of data (i) representative of the user's interaction with existing content presented on the website and (ii) indicative of content entities of interest to the user, the data being stored as nodes. Also included are one or more personalization engines configured to analyze relations between one or more pairs of the nodes, each analyzed relation creating a respective link, and a structure of each of the links being a function of the user's interaction with the existing content. The one or more processors are configured to personalize new content for presentation to the user and a portion of the new content is (i) derived from one of the respective links and (ii) delivered to the user in near-real time when a type of the first link is within a first category.

Abstract: Managing connected data, such as a graph data store, includes a computing device with persistent memory and volatile memory. The computing device stores a graph data store with a plurality of nodes and edges in persistent memory. Each of the edges defines the relationship between at least two of the nodes. The nodes and edges may contain tags and properties containing additional information. In response to a search request query, the computing device generates an iterator object stored in volatile memory with a reference to one or more nodes and/or edges in the graph data store. The split between volatile and persistent memory allocation could be used for other objects, such as allocators and transactions. Other embodiments are described and claimed.

Abstract: Machine learning based techniques are described for identifying sanctionable persons via monitoring a plurality of electronic content sources. This may allow for more rapid identification of prohibited or restricted transactions. A trained sentiment analysis classifier may classify a particular electronic content item as containing sanctionable conduct. An electronic textual analysis of the electronic content item may be performed to identify one or more individual names within the particular electronic content item. An indication as to whether the one or more individual names have been identified as individuals who may be subject to one or more sanction requirements that prohibit one or more online actions may be electronically stored in a data table. Various operations may be performed to block or otherwise restrict online accounts associated with the individual from performing online activities.

Abstract: Techniques are described for reducing the number of parameters of a deep neural network model. According to one or more embodiments, a device can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a structure extraction component that determines a number of input nodes associated with a fully connected layer of a deep neural network model. The computer executable components can further comprise a transformation component that replaces the fully connected layer with a number of sparsely connected sublayers, wherein the sparsely connected sublayers have fewer connections than the fully connecter layer, and wherein the number of sparsely connected sublayers is determined based on a defined decrease to the number of input nodes.

Abstract: A process including obtaining a set of natural-language text documents that discuss a topic, the set of documents containing different states of knowledge about the topic at different times. The process includes selecting an ontology from among a plurality of ontologies that correspond to different domains of knowledge, the selection being based on the ontology corresponding to a domain of knowledge including the topic. The process includes identifying concepts discussed in the documents using the ontology and detecting changes in at least some of the concepts over time based on differences between discussion of the concepts in documents authored at different times. The process includes updating natural language instructions on the topic based on the detected changes in the concepts and storing the updated natural language instructions in memory.

Abstract: An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies item nodes and attribute nodes related to the search query. The online concierge system identifies item nodes and attribute nodes that are likely to result in a conversion. Information about the identified nodes is presented to the customer. The customer may select an item node to purchase the item, or an attribute node to execute a new search query based on terms associated with the attribute node.

Abstract: An apparatus links an entity in a first knowledge-graph with a word in a text. The apparatus, based on a number of first-edges coupled to each of first-nodes serving as a transition-source and a number of second-edges coupled to each of second-nodes serving as a transition-destination in the first knowledge-graph, identifies a third-edge to be deleted from edges coupled to a third-node among the second-nodes which has a preset input-order indicating a number of edges that transition to the third-node, and generates a second knowledge-graph by deleting the third-edge from the first knowledge-graph. The apparatus couples first and second nodes which have been coupled to each other by the third-edge in the first knowledge-graph, via a fourth-node to which the first and second nodes are coupled by edges in the second knowledge-graph, and provides the word in the text and the entity linked with the word to a user.

Abstract: The present disclosure describes techniques for using instances of a connector to communicate with multiple target systems without a manual pre-configuration step for each of the multiple target systems. The connector may be an extensible program-code-template for creating objects to perform one or more operations. For example, each instance of the connector may obtain information regarding a corresponding target system, determine an interface to the corresponding target system based on the information, and translate requests for the corresponding target system according to the interface.

Abstract: Techniques herein minimally communicate between computers to repartition a graph. In embodiments, each computer receives a partition of edges and vertices of the graph. For each of its edges or vertices, each computer stores an intermediate representation into an edge table (ET) or vertex table. Different edges of a vertex may be loaded by different computers, which may cause a conflict. Each computer announces that a vertex resides on the computer to a respective tracking computer. Each tracking computer makes assignments of vertices to computers and publicizes those assignments. Each computer that loaded conflicted vertices transfers those vertices to computers of the respective assignments. Each computer stores a materialized representation of a partition based on: the ET and vertex table of the computer, and the vertices and edges that were transferred to the computer. Edges stored in the materialized representation are stored differently than edges stored in the ET.

Abstract: A computer-implemented method of retrieving and displaying data from an entity network database (130) comprising a plurality of entities and a plurality of relationships between the entities is provided. The method comprises receiving a selection of a plurality of anchor entities of the entity network database; retrieving a plurality of connector entities of the entity network database, each connector entity disposed on a path in the entity network database extending between at least two of the anchor entities; determining a relevance score for each of the connector entities, the relevance score reflecting the relevance of each connector entity to the anchor entities; and displaying the connector entities within a shape defined by the anchor entities, wherein the distance of each connector entity from the anchor entities is based on the relevance score of the connector entity.

Abstract: Methods, non-transitory machine readable media, and computing devices that provide more efficient hierarchical propagation in tree structures are disclosed. With this technology, a first delta record for a first interior node is created optionally in an atomic transaction along with updating a first tally record for a leaf node based on a first value. The transaction is in response to an action associated with the leaf node and the first interior node is a parent of the leaf node in a hierarchical tree. A timer associated with the first delta record is then set. A second value is updated in a second tally record for the first interior node based on the first value, when the timer has expired. Accordingly, this technology advantageously maintains recursive properties or values throughout a hierarchical tree continually, with reduced cost, even in a distributed network and in hierarchical trees with large numbers of nodes.

Abstract: In one embodiment, a method includes, by a client system of a user of an online social network, sending, to one or more computing devices of the online social network, a text post inputted by the user. The text post is associated with a query. The method includes receiving, from the one or more computing devices in response to the text post, an initial recommendation list. The initial recommendation list includes references to one or more objects referenced in comments associated with one or more prior posts associated with the query. The method includes sending, to the one or more computing devices, a request for updates to the initial recommendation list. Moreover, the method includes receiving, from the one or more computing devices in response to the request, an updated recommendation list comprising references to one or more objects referenced in comments associated with the text post.

Abstract: In general, embodiments of the invention relate to a method and computing system for scheduling tasks (functions or routines) dynamically from Input/Output (I/O) operations that may be received from a client. The scheduling or ordering of the tasks play an important role in the overall latency of the execution of IO operations, as each task may consume significant amount of computing resources.

Abstract: Systems and techniques are provided for mutable data ingestion and storage. Data for a database may be received at a computing device. New data from the data for the database may be stored as a mutable data chunk. The data for the database may be determined to include updated data for a previously stored mutable data chunk. The updated data may be applied to the previously stored mutable data chunk to update the previously stored mutable chunk. A second previously stored mutable data chunk may be determined to have been initially stored a specified amount of time ago. In response to determining that the second previously stored mutable data chunk was initially stored the specified amount of time ago, the second previously stored mutable data chunk may be caused to become an immutable data chunk.

Abstract: One embodiment provides a method and system for joint payment. During operation, a joint-payment server receives a joint-payment request comprising an identifier of a user initiating a joint payment and an identifier of a user to-be-included in the joint payment; determines, based the identifiers of the user initiating the joint payment and the to-be-included user, whether a binding relationship has been established between the user initiating the joint payment and the to-be-included user; in response to determining that the binding relationship has been established, generates graphic codes respectively corresponding to the user initiating the joint payment and the to-be-included user; and sends the graphic codes to a terminal device associated with the user initiating the joint payment, thereby facilitating the terminal device to display the graphic codes to complete the joint payment.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: An information management apparatus includes a processor configured to associate components including questions and answers to the questions using parent-child relationships and control a display of the components as a tree structure, receive a selection of a subset of components in the tree structure according to a user operation and also connect the selected subset of components to the tree structure, and change the parent-child relationships of the components according to the connection of the components.

Abstract: Methods and systems are provided for determining the category of a software application utilizing machine learning (ML) and knowledge graph techniques, and for controlling access to the application by a user based on the category and configured time restrictions for the user. The system includes a feature set extractor and a category predictor with a trained ML model. The trained ML model generates the category of the application based on a feature(s) of the application. The generated category is indicated in a data structure. An access request handler receives a request related to access to the application from a user device. A category determiner determines the category of the application from the data structure. A time usage manager determines an available time usage for the category and the specified user. The access arbiter responds to the request from the user device with the available time usage.

Abstract: Systems and methods for updating values of roll-up summary fields (RSFs) associated with a data model are described. A server computing system receives data associated with roll-up summary fields (RSF) of objects of a data model. The data is in in a serialized format. The computer system deserializes the data to determine values of the RSFs at nodes of a graph associated with the data model. The computer system updates a value of a RSF at a first node of the graph. The computer system updates a value of one or more RSFs at one or more remaining nodes of the graph based on said updating the value of the RSF at the first node. The computer system serializes the values of the RSFs at all of the nodes of the graph to generate serialized data subsequent to said updating the value of the one or more RSFs at the one or more remaining nodes of the graph.

Abstract: A method, apparatus and server for recommending an application are provided. The method may include determining at least one target friend among a plurality of friends of a target user, obtaining social interaction characteristics between the target user and the at least one target friend, based on a pre-trained friend impact prediction model of a target application and the social interaction characteristics between the target user and the at least one target friend, determining a first impact of the at least one target friend on registration of the target user in the target application, determining a recommendation score corresponding to the target user and the target application according to the first impact of the at least one target friend on registration of the target user in the target application, and performing application recommendation according to the recommendation score.