CN110515968B - Method and apparatus for outputting information - Google Patents
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- CN110515968B CN110515968B CN201910812692.2A CN201910812692A CN110515968B CN 110515968 B CN110515968 B CN 110515968B CN 201910812692 A CN201910812692 A CN 201910812692A CN 110515968 B CN110515968 B CN 110515968B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/288—Entity relationship models
Abstract
The embodiment of the application discloses a method and a device for outputting information. One embodiment of the method comprises: determining a target entity based on the input information; searching a target node corresponding to a target entity in a pre-generated entity relationship graph, wherein the nodes in the entity relationship graph store the entities, and edges between the nodes in the entity relationship graph store the relationships between the entities; in response to finding the target node corresponding to the target entity, searching the related node of the target node in the entity relationship map; and outputting information based on the related nodes of the target node. This embodiment improves the correlation between the output entities.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a method and a device for outputting information.
Background
Under the internet flood with big data being popularized, more and more scenes hope to carry out mining on related data through space-time big data. Such as making a collision with the relevant person based on time, place, and action as clues. And the collision result can be applied to a plurality of fields to solve the problem of relevant services. For example, fixed-point advertisement delivery is carried out on users passing through a business circle and a shop, and people are expected to be collided through geographical positions; and hopefully, acquaintances of the users are defined through communication and internet surfing behaviors of the mobile phone numbers so as to recall the lost connection personnel. The purpose of the collision of the related people in the internet scene is to highlight the organization of the entity information of people, events, places and objects, and then to discover a specific group based on the co-occurrence characteristics of time, place and action.
Disclosure of Invention
The embodiment of the application provides a method and a device for outputting information.
In a first aspect, an embodiment of the present application provides a method for outputting information, including: determining a target entity based on the input information; searching a target node corresponding to a target entity in a pre-generated entity relationship graph, wherein the nodes in the entity relationship graph store the entities, and edges between the nodes in the entity relationship graph store the relationships between the entities; in response to finding the target node corresponding to the target entity, searching the related node of the target node in the entity relationship map; and outputting information based on the related nodes of the target node.
In some embodiments, finding a target node corresponding to a target entity in a pre-generated entity relationship graph includes: if the target entity is a place, determining a sub-geographic area where the target entity is located; searching a node which falls into a sub-geographic area where a target entity is located in the entity relation map to serve as a target node; and searching the related nodes of the target nodes in the entity relationship graph, wherein the searching comprises the following steps: and performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node as a related node of the target node, wherein the entity stored by the in-degree node of the target node is a person.
In some embodiments, edges between nodes in the entity relationship graph also store attributes of the relationships; and searching a target node corresponding to the target entity in the pre-generated entity relationship graph, wherein the searching comprises the following steps: if the target entity is a place set, determining a sub-geographic area set where the target entity is located; searching a node which falls into a sub-geographic area set where a target entity is located in an entity relation graph to serve as a target node; and searching the related nodes of the target nodes in the entity relationship graph, wherein the searching comprises the following steps: performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node; and screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attribute of the relationship.
In some embodiments, finding a target node corresponding to a target entity in a pre-generated entity relationship graph includes: if the target entity is a person, searching a node for storing the target entity in the entity relationship graph as a target node; and searching the related nodes of the target nodes in the entity relationship graph, wherein the searching comprises the following steps: performing out-degree traversal of the graph based on the target node, and determining an out-degree node of the target node, wherein an entity stored by the out-degree node of the target node is a place; determining a sub-geographic area where a degree-out node of a target node is located; searching out the nodes of the sub-geographic area where the out-degree node falling into the target node is located in the entity relationship map; performing in-degree traversal of the graph based on the nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, and determining in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, wherein entities stored by the in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located are characters; and screening out related nodes of the target node from the in-degree nodes of the nodes in the sub-geographic area where the out-degree node of the target node is located based on the attribute of the relationship.
In some embodiments, the generating of the entity relationship graph comprises: acquiring an entity relationship data set, wherein entity relationship data in the entity relationship data set records entities and relationships among the entities; for entity relationship data in the entity relationship data set, nodes are generated based on entities in the entity relationship data, edges between the nodes are generated based on relationships between the entities in the entity relationship data, and an entity relationship map is obtained.
In some embodiments, the entity relationship data in the entity relationship data set further records attributes of the relationship; and the step of generating the entity relationship map further comprises the following steps: for entity relationship data in the entity relationship data set, attributes of the edges are generated based on attributes of the relationships in the entity relationship data.
In some embodiments, the generating of the entity relationship graph further comprises: the method includes the steps of removing duplication of nodes in the entity relationship graph and filtering repeated edges in the entity relationship graph.
In some embodiments, the generating of the entity relationship graph further comprises: and aggregating the associated nodes in the entity relationship graph and aggregating the associated edges in the entity relationship graph.
In some embodiments, aggregating the associated nodes in the entity relationship graph comprises: if the nodes of the storage places exist in the entity relationship map, dividing the preset geographical area into a sub geographical area set, wherein the nodes of the storage places in the entity relationship map all fall into the preset geographical area, and the sub geographical areas in the sub geographical area set are not overlapped with each other; and for the sub-geographic areas in the sub-geographic area set, aggregating the nodes falling into the sub-geographic areas in the entity relationship graph.
In some embodiments, aggregating the associated edges in the entity relationship graph comprises: if the entity relationship map has edges for storing the time attributes, dividing the preset time period into a sub-time period set, wherein the edges for storing the time attributes in the entity relationship map all fall into the preset time period, and the sub-time periods in the sub-time period set are not overlapped with each other; and for the sub-time periods in the sub-time period set, aggregating edges falling into the sub-time periods in the entity relationship map.
In a second aspect, an embodiment of the present application provides an apparatus for outputting information, including: a target entity determination unit configured to determine a target entity based on the input information; the target node searching unit is configured to search a target node corresponding to a target entity in a pre-generated entity relationship graph, wherein the nodes in the entity relationship graph store the entities, and the edges between the nodes in the entity relationship graph store the relationships between the entities; a related node searching unit configured to search a related node of the target node in the entity relationship map in response to finding the target node corresponding to the target entity; a relevant node output unit configured to output information based on a relevant node of the target node.
In some embodiments, the target node finding unit is further configured to: if the target entity is a place, determining a sub-geographic area where the target entity is located; searching a node which falls into a sub-geographic area where a target entity is located in the entity relation map to serve as a target node; and the correlation node finding unit is further configured to: and performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node as a related node of the target node, wherein the entity stored by the in-degree node of the target node is a person.
In some embodiments, edges between nodes in the entity relationship graph also store attributes of the relationships; and the target node finding unit is further configured to: if the target entity is a place set, determining a sub-geographic area set where the target entity is located; searching a node which falls into a sub-geographic area set where a target entity is located in an entity relation graph to serve as a target node; and the correlation node finding unit is further configured to: performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node; and screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attribute of the relationship.
In some embodiments, the target node finding unit is further configured to: if the target entity is a person, searching a node for storing the target entity in the entity relationship graph as a target node; and the correlation node finding unit is further configured to: performing out-degree traversal of the graph based on the target node, and determining an out-degree node of the target node, wherein an entity stored by the out-degree node of the target node is a place; determining a sub-geographic area where a degree-out node of a target node is located; searching out the nodes of the sub-geographic area where the out-degree node falling into the target node is located in the entity relationship map; performing in-degree traversal of the graph based on the nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, and determining in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, wherein entities stored by the in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located are characters; and screening out related nodes of the target node from the in-degree nodes of the nodes in the sub-geographic area where the out-degree node of the target node is located based on the attribute of the relationship.
In some embodiments, the generating of the entity relationship graph comprises: acquiring an entity relationship data set, wherein entity relationship data in the entity relationship data set records entities and relationships among the entities; for entity relationship data in the entity relationship data set, nodes are generated based on entities in the entity relationship data, edges between the nodes are generated based on relationships between the entities in the entity relationship data, and an entity relationship map is obtained.
In some embodiments, the entity relationship data in the entity relationship data set further records attributes of the relationship; and the step of generating the entity relationship map further comprises the following steps: for entity relationship data in the entity relationship data set, attributes of the edges are generated based on attributes of the relationships in the entity relationship data.
In some embodiments, the generating of the entity relationship graph further comprises: the method includes the steps of removing duplication of nodes in the entity relationship graph and filtering repeated edges in the entity relationship graph.
In some embodiments, the generating of the entity relationship graph further comprises: and aggregating the associated nodes in the entity relationship graph and aggregating the associated edges in the entity relationship graph.
In some embodiments, aggregating the associated nodes in the entity relationship graph comprises: if the nodes of the storage places exist in the entity relationship map, dividing the preset geographical area into a sub geographical area set, wherein the nodes of the storage places in the entity relationship map all fall into the preset geographical area, and the sub geographical areas in the sub geographical area set are not overlapped with each other; and for the sub-geographic areas in the sub-geographic area set, aggregating the nodes falling into the sub-geographic areas in the entity relationship graph.
In some embodiments, aggregating the associated edges in the entity relationship graph comprises: if the entity relationship map has edges for storing the time attributes, dividing the preset time period into a sub-time period set, wherein the edges for storing the time attributes in the entity relationship map all fall into the preset time period, and the sub-time periods in the sub-time period set are not overlapped with each other; and for the sub-time periods in the sub-time period set, aggregating edges falling into the sub-time periods in the entity relationship map.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described in any implementation of the first aspect.
In a fourth aspect, the present application provides a computer-readable medium, on which a computer program is stored, which, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
According to the method and the device for outputting the information, the target entity is determined based on the input information; then searching a target node corresponding to the target entity in a pre-generated entity relation graph; then, in response to finding the target node corresponding to the target entity, searching the related node of the target node in the entity relationship map; and finally, outputting information based on the related nodes of the target node. The nodes in the entity relationship map store entities, the edges between the nodes in the entity relationship map store the relationships between the entities, and related nodes are searched based on the entity relationship map to output entity information, so that the relevance between the output entities is improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture to which the present application may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for outputting information, in accordance with the present application;
FIG. 3 is a flow diagram of yet another embodiment of a method for outputting information according to the present application;
FIG. 4 is a flow diagram of one embodiment of a method for generating an entity relationship graph according to the present application;
FIG. 5 is a schematic diagram of an entity relationship map;
FIG. 6 is a schematic block diagram illustrating one embodiment of an apparatus for outputting information according to the present application;
FIG. 7 is a block diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the present method for outputting information or apparatus for outputting information may be applied.
As shown in fig. 1, a system architecture 100 may include a terminal device 101, a network 102, and a server 103. Network 102 is the medium used to provide communication links between terminal devices 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal device 101 to interact with server 103 over network 102 to receive or send messages and the like.
The terminal apparatus 101 may be hardware or software. When the terminal apparatus 101 is hardware, it may be various electronic apparatuses. Including but not limited to smart phones, tablet computers, e-book readers, laptop portable computers, desktop computers, and the like. When the terminal apparatus 101 is software, it can be installed in the above-described electronic apparatus. It may be implemented as multiple pieces of software or software modules, or as a single piece of software or software module. And is not particularly limited herein.
The server 103 may provide various services. For example, the server 103 may perform processing such as analysis on data such as input information received from the terminal apparatus 101, and feed back a processing result (e.g., an entity stored in a relevant node of the target node) to the terminal apparatus 101.
The server 103 may be hardware or software. When the server 103 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 103 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for outputting information provided in the embodiment of the present application is generally performed by the server 103, and accordingly, the apparatus for outputting information is generally disposed in the server 103.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for outputting information in accordance with the present application is shown. The method for outputting information comprises the following steps:
In the present embodiment, an execution subject (e.g., the server 103 shown in fig. 1) of the method for outputting information may acquire input information from a terminal device (e.g., the terminal device 101 shown in fig. 1) communicatively connected thereto, and determine a target entity based on the input information. Where an entity may include a variety of categories including, but not limited to, location, people, behavior, and so forth. The input information may be information related to the entity input by the user. The target entity may be an entity corresponding to the related information input by the user. For example, if the input information is geographic coordinates, the target entity may be a corresponding location; if the input information is the name of a person, then the target entity may be the corresponding person.
In this embodiment, the executing entity may search for a target node corresponding to a target entity in a pre-generated entity relationship graph. If the target node corresponding to the target entity is found, executing step 203; if the target node corresponding to the target entity cannot be found, the process is ended.
In practice, the entity relationship graph may include nodes and edges between the nodes. Nodes in the entity relationship graph may store entities. Edges between nodes in the entity relationship graph may store relationships between entities. The target node may include a node that stores the target entity, and may also include nodes near the node that stores the target entity. For example, if the target entity is a person, the target node is typically the node that stores the target entity; if the target entity is a site, the target node typically includes both the node storing the target entity and nodes near the node storing the target entity.
Furthermore, different nodes typically store different entities. If an edge is connected between two nodes, the relationship between the two nodes is shown. Also, two nodes connected with edges typically belong to different classes. For example, if an edge is connected between a node storing a person and a node storing a place, it is indicated that the person and the place have a positioning relationship; if an edge is connected between the node for storing the character and the node for storing the behavior, the occurrence relationship between the character and the behavior is shown.
In this embodiment, when the target node corresponding to the target entity is found, the execution main body may find the relevant node of the target node in the entity relationship map. The relevant node of the target node can be a node of an edge which is directly connected or indirectly connected with the target node. Thus, the entities stored by the target node's associated nodes are entities that have certain co-occurrence characteristics.
And step 204, outputting information based on the related nodes of the target node.
In this embodiment, the execution agent may output information based on a node related to the target node. For example, the execution agent may output information of at least a part of the relevant nodes of the target node.
According to the method for outputting the information, the target entity is determined based on the input information; then searching a target node corresponding to the target entity in a pre-generated entity relation graph; then, in response to finding the target node corresponding to the target entity, searching the related node of the target node in the entity relationship map; and finally, outputting information based on the related nodes of the target node. The nodes in the entity relationship map store entities, the edges between the nodes in the entity relationship map store the relationships between the entities, and related nodes are searched based on the entity relationship map to output entity information, so that the relevance between the output entities is improved.
With further reference to fig. 3, a flow 300 of yet another embodiment of a method for outputting information in accordance with the present application is shown. The method for outputting information comprises the following steps:
In this embodiment, the specific operation of step 301 has been described in detail in step 201 in the embodiment shown in fig. 2, and is not described herein again.
In this embodiment, if the target entity is a place, an executing subject (e.g., the server 103 shown in fig. 1) of the method for outputting information may determine a sub-geographic area where the target entity is located. Generally, the execution subject may divide the preset geographic area into a set of sub-geographic areas in advance. The preset geographic area may be a geographic area of any range, may be a country, may also be a province, may also be a city, and is not specifically limited herein. The sub-geographic areas in the set of sub-geographic areas do not overlap with each other. The number of locations present in each sub-geographic area is not limited, and there may be no location or a plurality of locations present in each sub-geographic area. And, the distance between the places in the same sub-geographic area is close. For example, the execution subject may divide the preset geographic area into a plurality of grids by way of grid division. Wherein a grid is a sub-geographic area.
In this embodiment, the executing entity may search, in the entity relationship graph, a node that falls in a sub-geographic area where the target entity is located, as the target node. Here, the target node includes both a node storing the target entity and a node near the node storing the target entity.
And 304, performing graph in-degree traversal based on the target node, and determining the in-degree node of the target node as a related node of the target node.
In this embodiment, the executing entity may perform an in-degree traversal of the graph based on the target node to determine an in-degree node of the target node as a relevant node of the target node. Wherein, the entity stored by the in-degree node of the target node can be a person. Thus, the entities stored by the relevant nodes of the target node are groups that are simultaneously present at a particular site.
In practice, edges in the entity relationship graph are directional. For example, if edges are connected between a node storing a person and a node storing a place, the edges between the nodes point from the person to the place. Wherein the node storing the figure is an in-degree node of the storage place. The node of the storage location is an out-degree node of the node storing the person. If edges are connected between the nodes storing the characters and the nodes storing the behaviors, the edges between the nodes point to the behaviors from the characters. Wherein the node storing the figure is an in-degree node of the node storing the behavior. The node storing the behavior is an out-degree node of the node storing the character.
Step 302', if the target entity is a location set, determining a sub-geographic area set where the target entity is located.
In this embodiment, if the target entity is a location set, the sub-geographic area set where the target entity is located is determined. In general, a location set may include a plurality of locations that a person passes through on a motion trajectory.
Step 303', searching the node in the entity relationship graph, which falls into the set of sub-geographic regions where the target entity is located, as the target node.
In this embodiment, the executing entity may search, in the entity relationship graph, a node that falls into a set of sub-geographic areas where the target entity is located, as the target node. That is, for each place in the set of places, the executing entity may look up the nodes in the entity relationship graph that fall within the sub-geographic region in which the place is located.
And step 304', performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node.
In this embodiment, the executing agent may perform an in-degree traversal of the graph based on the target node to determine an in-degree node of the target node. That is, for a node that falls within a sub-geographic area where each place in the set of places is located, the executing entity may determine an in-degree node of the node that falls within the sub-geographic area where the place is located. Wherein, the entity stored by the in-degree node of the target node can be a person.
And 305', screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attributes of the relationship.
In this embodiment, the execution body may screen out a relevant node of the target node from the in-degree nodes of the target node based on the attribute of the relationship. Generally, the execution body may screen out nodes with the same or similar attributes of the relationship from the in-degree nodes of the target node, as related nodes of the target node.
In practice, edges between nodes in the entity relationship graph may also store attributes of the relationships. Wherein the attribute of the relationship may be a characteristic of the two nodes connected with the edge, including but not limited to the occurrence time of the relationship between the two nodes connected with the edge. For example, if edges are connected between the nodes storing people and the nodes storing places, and the edges between the nodes can also store time, the time represents the time when the positioning relationship between people and places occurs; if edges are connected between the nodes storing the characters and the nodes storing the behaviors, and the edges between the nodes can also store time, the time represents the time when the occurrence relationship between the characters and the behaviors occurs. Here, the execution body generally screens out nodes in which a positioning relationship occurs within a certain period of time (e.g., within a day) from the in-degree nodes of the target node. Thus, the entities stored by the relevant nodes of the target node are groups with the co-occurrence of the motion tracks in a certain period of time.
Step 302', if the target entity is a person, a node storing the target entity is searched in the entity relationship graph as a target node.
In this embodiment, if the target entity is a person, the executing entity may search a node storing the target entity in the entity relationship graph as the target node. Here, the target node is a node storing the target entity.
And step 303', performing out-degree traversal of the graph based on the target node, and determining out-degree nodes of the target node.
In this embodiment, the executing agent may perform out-degree traversal of the graph based on the target node to determine an out-degree node of the target node. Wherein, the entity stored by the out-degree node of the target node can be a place.
Step 304', a sub-geographic area where the out-degree node of the target node is located is determined.
In this embodiment, the execution subject may determine a sub-geographic area where the outbound node of the target node is located.
Step 305', find out the nodes of the sub-geographic area where the out-degree node falling into the target node is located in the entity relationship graph.
In this embodiment, the executing entity may find the node in the entity relationship graph, where the outbound node falling into the target node is located in the sub-geographic area.
And step 306', an in-degree traversal of the graph is performed based on the nodes of the sub-geographic area where the out-degree node of the target node is located, and the in-degree node of the sub-geographic area where the out-degree node of the target node is located is determined.
In this embodiment, the executing body may perform an in-degree traversal of the graph based on the node in the sub-geographic area where the out-degree node that falls into the target node is located, so as to determine the in-degree node of the node in the sub-geographic area where the out-degree node that falls into the target node is located. The entity stored by the degree-in node of the node in the sub-geographic area where the degree-out node of the target node is located can be a person.
And 307' based on the attribute of the relation, screening out relevant nodes of the target node from the input nodes of the nodes in the sub-geographic area where the output node of the target node is located.
In this embodiment, the execution body may screen out a relevant node of the target node from the in-degree nodes of the nodes in the sub-geographic area where the out-degree node of the target node is located, based on the attribute of the relationship. Generally, the execution subject may screen out nodes having the same or similar relationship attributes from the in-degree nodes of the nodes in the sub-geographic area where the out-degree node of the target node is located, as the relevant nodes of the target node. Here, the execution body generally screens out nodes having a positioning relationship within a certain period of time (for example, within a day) from the in-degree nodes of the nodes falling into the sub-geographic area where the out-degree node of the target node is located. Thus, the entities stored by the relevant nodes of the target node are the same group of lines within a certain period of time.
And 308, outputting information based on the related nodes of the target node.
In this embodiment, the specific operation of step 308 has been described in detail in step 204 in the embodiment shown in fig. 2, and is not described herein again.
As can be seen from fig. 3, compared with the corresponding embodiment of fig. 2, the flow 300 of the method for outputting information in the present embodiment highlights the step of finding the relevant node of the target node in the entity relationship graph. Therefore, the scheme described in the embodiment can output not only the group appearing at the specific place at the same time, but also the group with the co-occurrence motion trail and the group with the same line. Thereby enriching the types of the output groups.
With further reference to FIG. 4, a flow 400 of one embodiment of a method for generating an entity relationship graph in accordance with the present application is illustrated. The method for generating the entity relationship map comprises the following steps:
In this embodiment, an executive (e.g., server 103 shown in fig. 1) of a method for generating an entity relationship graph may obtain an entity relationship data set. The entity relationship data in the entity relationship data set can record the entities and the relationships among the entities. Entity relationship data, which may also be called spatiotemporal data, is a co-occurrence record of people and locations, people and behaviors. It should be understood that there are typically at least two entities in the same entity relationship data.
In this embodiment, for entity relationship data in the entity relationship data set, the execution subject may generate nodes based on the entities in the entity relationship data, and generate edges between the nodes based on the relationships between the entities in the entity relationship data, so as to obtain the entity relationship graph. Specifically, for each entity relationship data, the executing entity may first extract at least two entities from the entity relationship data and a relationship between the at least two entities; then establishing a node storing each of the at least two entities; finally, connecting the established at least two nodes to generate an edge between the at least two nodes.
In some optional implementations of the present embodiment, the edges in the entity relationship graph are directional. For example, if edges are connected between a node storing a person and a node storing a place, the edges between the nodes point from the person to the place. Wherein the node storing the figure is an in-degree node of the storage place. The node of the storage location is an out-degree node of the node storing the person. If edges are connected between the nodes storing the characters and the nodes storing the behaviors, the edges between the nodes point to the behaviors from the characters. Wherein the node storing the figure is an in-degree node of the node storing the behavior. The node storing the behavior is an out-degree node of the node storing the character.
In some optional implementations of this embodiment, the entity relationship data in the entity relationship data set may further record attributes of the relationship. In this way, for entity relationship data in an entity relationship data set, the execution principal may generate attributes of edges based on attributes of relationships in the entity relationship data. Wherein the attribute of the relationship may be a characteristic of the two nodes connected with the edge, including but not limited to the occurrence time of the relationship between the two nodes connected with the edge. For example, if edges are connected between the nodes storing people and the nodes storing places, and the edges between the nodes can also store time, the time represents the time when the positioning relationship between people and places occurs; if edges are connected between the nodes storing the characters and the nodes storing the behaviors, and the edges between the nodes can also store time, the time represents the time when the occurrence relationship between the characters and the behaviors occurs.
In some optional implementations of this embodiment, the execution subject may further perform deduplication on nodes in the entity relationship graph, and filter repeated edges in the entity relationship graph. Thus, if the same entity appears multiple times in the entity relationship data set, only one node storing the entity is established in the entity relationship graph. Similarly, if a relationship between two entities in an entity relationship data set occurs multiple times, then only one edge is connected between the two nodes in the entity relationship graph.
In some optional implementation manners of this embodiment, the execution main body may further aggregate association nodes in the entity relationship graph, and aggregate association edges in the entity relationship graph. The entity relationship data set is very large in scale due to the dynamic and ubiquitous nature of the entity relationship data set. Taking location positioning data of products of large-scale internet companies as an example, after an entity relationship map is constructed by collecting original entity relationship data, the point and edge specifications can reach billions. This causes a situation where there are many edges in a node in the entity relationship graph. Here, data needs to be compressed, and points and edges are aggregated when the data is reflected on the entity relationship graph. For point aggregation, it mainly appears to aggregate nodes with similar, and common characteristics into one large node. For edge aggregation, aggregation over a span of time is mainly reflected.
In some optional implementation manners of this embodiment, if there is a node of a storage location in the entity relationship graph, the execution main body may divide a preset geographic area into a set of sub-geographic areas; and for the sub-geographic areas in the sub-geographic area set, aggregating the nodes falling into the sub-geographic areas in the entity relationship graph. The nodes of the storage places in the entity relationship graph all fall into a preset geographical area, and the sub geographical areas in the sub geographical area set are not overlapped with each other. Taking a place as an example, place data is often discrete points, and if the area of a preset geographic area is 960 ten thousand square kilometers, 9.6 trillion nodes exist in an entity relationship graph, which requires a large amount of storage. By using a 100 × 100 coordinate grid as a node, the number of nodes in the entity relationship graph is reduced to 9.6 hundred million.
In some optional implementation manners of this embodiment, if an edge storing a time attribute exists in the entity relationship graph, the execution main body may divide a preset time period into a sub-time period set; and for the sub-time periods in the sub-time period set, aggregating edges falling into the sub-time periods in the entity relationship map. The edges of the entity relationship graph storing the time attributes all fall into a preset time period, and the sub-time periods in the sub-time period set are not overlapped with each other. For example, the executive may record the positioning behavior of a character in a grid as an edge during a day. The time attribute of the edge is the date. In addition, the execution body may record the detailed positioning frequency as an attribute. If the frequency attribute is "frequency { '12': 6, '16': 10 }", it indicates that 6 dotting records exist at 12 points and 10 dotting records exist at 16 points. Thus 16 positioning records are aggregated into 1. It is of course also possible to record the exact positioning coordinates at each time instant in a similar manner on the edge attributes.
For ease of understanding, FIG. 5 shows a schematic diagram of an entity relationship graph. As shown in fig. 5, there are 6 nodes and 5 edges in the entity relationship graph. Wherein, the 6 nodes comprise 4 nodes for storing people and 2 nodes for storing places. The 4 nodes storing characters are a node storing character 1, a node storing character 2, a node storing character 3, and a node storing character 4, respectively. The nodes of the 2 storage locations are the node of storage location a and the node of storage location B, respectively. The node storing the person 1, the node storing the person 2, and the node storing the person 3 are connected to the node of the storage location B, respectively, and it is explained that the person 1, the person 2, and the person 3 arrive at the storage location B. The node storing the person 1 and the node storing the person 4 are connected to the node of the storage location a, respectively, and the person 1 and the person 4 are explained to arrive at the storage location a.
With further reference to fig. 6, as an implementation of the methods shown in the above-mentioned figures, the present application provides an embodiment of an apparatus for outputting information, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.
As shown in fig. 6, the apparatus 600 for outputting information of the present embodiment may include: a target entity determining unit 601, a target node finding unit 602, a related node finding unit 603, and a related node outputting unit 604. Wherein the target entity determining unit 601 is configured to determine a target entity based on the input information; a target node searching unit 602 configured to search a target node corresponding to a target entity in a pre-generated entity relationship graph, where nodes in the entity relationship graph store entities and edges between the nodes in the entity relationship graph store relationships between the entities; a related node searching unit 603 configured to search, in response to finding a target node corresponding to the target entity, a related node of the target node in the entity relationship map; a relevant node output unit 604 configured to output information based on the relevant node of the target node.
In the present embodiment, in the apparatus 600 for outputting information: the specific processes of the target entity determining unit 601, the target node searching unit 602, the related node searching unit 603, and the related node outputting unit 604 and the technical effects thereof can refer to the related descriptions of step 201 and step 204 in the corresponding embodiment of fig. 2, which are not described herein again.
In some optional implementations of this embodiment, the target node finding unit 602 is further configured to: if the target entity is a place, determining a sub-geographic area where the target entity is located; searching a node which falls into a sub-geographic area where a target entity is located in the entity relation map to serve as a target node; and the correlation node finding unit 603 is further configured to: and performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node as a related node of the target node, wherein the entity stored by the in-degree node of the target node is a person.
In some optional implementations of this embodiment, edges between nodes in the entity relationship graph further store attributes of the relationships; and the target node finding unit 602 is further configured to: if the target entity is a place set, determining a sub-geographic area set where the target entity is located; searching a node which falls into a sub-geographic area set where a target entity is located in an entity relation graph to serve as a target node; and the correlation node finding unit 603 is further configured to: performing in-degree traversal of the graph based on the target node, and determining the in-degree node of the target node; and screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attribute of the relationship.
In some optional implementations of this embodiment, the target node finding unit 602 is further configured to: if the target entity is a person, searching a node for storing the target entity in the entity relationship graph as a target node; and the correlation node finding unit 603 is further configured to: performing out-degree traversal of the graph based on the target node, and determining an out-degree node of the target node, wherein an entity stored by the out-degree node of the target node is a place; determining a sub-geographic area where a degree-out node of a target node is located; searching out the nodes of the sub-geographic area where the out-degree node falling into the target node is located in the entity relationship map; performing in-degree traversal of the graph based on the nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, and determining in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, wherein entities stored by the in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located are characters; and screening out related nodes of the target node from the in-degree nodes of the nodes in the sub-geographic area where the out-degree node of the target node is located based on the attribute of the relationship.
In some optional implementations of this embodiment, the generating of the entity relationship graph includes: acquiring an entity relationship data set, wherein entity relationship data in the entity relationship data set records entities and relationships among the entities; for entity relationship data in the entity relationship data set, nodes are generated based on entities in the entity relationship data, edges between the nodes are generated based on relationships between the entities in the entity relationship data, and an entity relationship map is obtained.
In some optional implementations of this embodiment, the entity relationship data in the entity relationship data set further records attributes of the relationship; and the step of generating the entity relationship map further comprises the following steps: for entity relationship data in the entity relationship data set, attributes of the edges are generated based on attributes of the relationships in the entity relationship data.
In some optional implementations of this embodiment, the generating of the entity relationship graph further includes: the method includes the steps of removing duplication of nodes in the entity relationship graph and filtering repeated edges in the entity relationship graph.
In some optional implementations of this embodiment, the generating of the entity relationship graph further includes: and aggregating the associated nodes in the entity relationship graph and aggregating the associated edges in the entity relationship graph.
In some optional implementations of this embodiment, aggregating the associated nodes in the entity relationship graph includes: if the nodes of the storage places exist in the entity relationship map, dividing the preset geographical area into a sub geographical area set, wherein the nodes of the storage places in the entity relationship map all fall into the preset geographical area, and the sub geographical areas in the sub geographical area set are not overlapped with each other; and for the sub-geographic areas in the sub-geographic area set, aggregating the nodes falling into the sub-geographic areas in the entity relationship graph.
In some optional implementations of this embodiment, aggregating the associated edges in the entity relationship graph includes: if the entity relationship map has edges for storing the time attributes, dividing the preset time period into a sub-time period set, wherein the edges for storing the time attributes in the entity relationship map all fall into the preset time period, and the sub-time periods in the sub-time period set are not overlapped with each other; and for the sub-time periods in the sub-time period set, aggregating edges falling into the sub-time periods in the entity relationship map.
Referring now to FIG. 7, a block diagram of a computer system 700 suitable for use in implementing an electronic device (e.g., server 103 shown in FIG. 1) of an embodiment of the present application is shown. The electronic device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program, when executed by a Central Processing Unit (CPU)701, performs the above-described functions defined in the method of the present application.
It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or electronic device. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes a target entity determining unit, a target node finding unit, a related node finding unit, and a related node outputting unit. Where the names of these units do not constitute a limitation on the unit itself in this case, for example, the target entity determining unit may also be described as a "unit that determines a target entity based on input information".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: determining a target entity based on the input information; searching a target node corresponding to a target entity in a pre-generated entity relationship graph, wherein the nodes in the entity relationship graph store the entities, and edges between the nodes in the entity relationship graph store the relationships between the entities; in response to finding the target node corresponding to the target entity, searching the related node of the target node in the entity relationship map; and outputting information based on the related nodes of the target node.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (12)
1. A method for outputting information, comprising:
determining a target entity based on the input information;
searching a target node corresponding to the target entity in a pre-generated entity relationship graph, wherein the nodes in the entity relationship graph store the entities, and edges between the nodes in the entity relationship graph store the relationships and the attributes of the relationships between the entities;
in response to finding a target node corresponding to the target entity, finding a relevant node of the target node in the entity relationship graph;
outputting information based on the relevant nodes of the target node;
the searching for the target node corresponding to the target entity in the pre-generated entity relationship graph comprises:
if the target entity is a location set, determining a sub-geographic area set where the target entity is located;
searching a node which falls into a sub-geographic area set where the target entity is located in the entity relationship graph to serve as the target node; and
the searching for the relevant node of the target node in the entity relationship graph comprises:
performing graph in-degree traversal based on the target node, and determining the in-degree node of the target node;
and screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attribute of the relationship.
2. The method of claim 1, wherein the searching for the target node corresponding to the target entity in the pre-generated entity relationship graph comprises:
if the target entity is a place, determining a sub-geographic area where the target entity is located;
searching a node which falls into a sub-geographic area where the target entity is located in the entity relationship graph to serve as the target node; and
the searching for the relevant node of the target node in the entity relationship graph comprises:
and performing graph in-degree traversal based on the target node, and determining the in-degree node of the target node as a related node of the target node, wherein an entity stored in the in-degree node of the target node is a person.
3. The method of claim 1, wherein the searching for the target node corresponding to the target entity in the pre-generated entity relationship graph comprises:
if the target entity is a person, searching a node for storing the target entity in the entity relationship graph as the target node; and
the searching for the relevant node of the target node in the entity relationship graph comprises:
performing graph output traversal based on the target node, and determining an output node of the target node, wherein an entity stored by the output node of the target node is a place;
determining a sub-geographic area where a degree-out node of the target node is located;
searching out the nodes of the sub-geographic area where the out-degree node falling into the target node is located in the entity relationship graph;
performing in-degree traversal of the graph based on the nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, and determining the in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located, wherein entities stored in the in-degree nodes of the sub-geographic area where the out-degree nodes falling into the target nodes are located are characters;
and screening out relevant nodes of the target nodes from the input nodes of the nodes in the sub-geographic area where the output nodes of the target nodes are located based on the attributes of the relationship.
4. The method of any one of claims 1-3, wherein the generating of the entity relationship graph comprises:
acquiring an entity relationship data set, wherein entity relationship data in the entity relationship data set records entities and relationships among the entities;
and for the entity relationship data in the entity relationship data set, generating nodes based on the entities in the entity relationship data, and generating edges between the nodes based on the relationship between the entities in the entity relationship data to obtain the entity relationship map.
5. The method of claim 4, wherein the entity relationship data in the entity relationship data set further records attributes of relationships; and
the step of generating the entity relationship map further comprises:
for entity relationship data in the entity relationship data set, generating attributes of edges based on attributes of relationships in the entity relationship data.
6. The method of claim 5, wherein the generating of the entity relationship graph further comprises:
and carrying out duplication removal on the nodes in the entity relationship graph, and filtering repeated edges in the entity relationship graph.
7. The method of claim 5, wherein the generating of the entity relationship graph further comprises:
and aggregating the associated nodes in the entity relationship graph and aggregating the associated edges in the entity relationship graph.
8. The method of claim 7, wherein the aggregating associated nodes in the entity relationship graph comprises:
if the entity relationship map has nodes of storage places, dividing a preset geographical area into a sub geographical area set, wherein the nodes of the storage places in the entity relationship map all fall into the preset geographical area, and the sub geographical areas in the sub geographical area set are not overlapped with each other;
and for the sub-geographic areas in the sub-geographic area set, aggregating the nodes falling into the sub-geographic areas in the entity relationship graph.
9. The method of claim 7, wherein the aggregating associated edges in the entity relationship graph comprises:
if the entity relationship map has edges for storing the time attributes, dividing a preset time period into a sub-time period set, wherein the edges for storing the time attributes in the entity relationship map all fall into the preset time period, and the sub-time periods in the sub-time period set are not overlapped with each other;
and for the sub-time periods in the sub-time period set, aggregating the edges falling into the sub-time periods in the entity relationship map.
10. An apparatus for outputting information, comprising:
a target entity determination unit configured to determine a target entity based on the input information;
a target node searching unit configured to search a target node corresponding to the target entity in a pre-generated entity relationship graph, wherein nodes in the entity relationship graph store entities, and edges between the nodes in the entity relationship graph store relationships and attributes of the relationships between the entities;
a related node searching unit configured to search a related node of the target node in the entity relationship map in response to finding the target node corresponding to the target entity;
a relevant node output unit configured to output information based on a relevant node of the target node;
wherein the target node lookup unit is further configured to:
if the target entity is a location set, determining a sub-geographic area set where the target entity is located;
searching a node which falls into a sub-geographic area set where the target entity is located in the entity relationship graph to serve as the target node; and
the correlation node lookup unit is further configured to:
performing graph in-degree traversal based on the target node, and determining the in-degree node of the target node;
and screening out relevant nodes of the target node from the in-degree nodes of the target node based on the attribute of the relationship.
11. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-9.
12. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, carries out the method according to any one of claims 1-9.
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| CN111522887B (en) * | 2020-04-03 | 2023-09-12 | 北京百度网讯科技有限公司 | Method and device for outputting information |
| CN111506737B (en) * | 2020-04-08 | 2023-12-19 | 北京百度网讯科技有限公司 | Graph data processing method, searching method, device and electronic equipment |
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