Methods and apparatus for presenting information

Abstract

To provide a method and device for receiving a query for an event graph and presenting information.SOLUTION: A method includes: receiving a query for an event graph, the query indicating at least a target event to be searched (Step 810); presenting, as a result of the query, a target event graph comprising a plurality of nodes and at least one directed edge connecting the plurality of nodes, the plurality of nodes representing the target event and one or more events associated with the target event respectively, and the at least one directed edge representing an event relationship between events represented by connected nodes respectively (Step 820); and presenting, for at least one node in the plurality of nodes, time information of at least one event represented by the at least one node, respectively (Step 830).SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] Exemplary embodiments of the present disclosure generally relate to the field of computers, and particularly to methods and apparatuses for presenting information.

Background Art

[0002] With the development of network technology and multimedia technology, the amount of news has been increasing exponentially every day, and there is a large amount of repetitive news. Generally, news events do not occur alone. A user may want to understand the background of the event, further understand the direction of the event through historical events, and predict the possible impacts of the current event. For a user, the process of searching for and filtering event-related information is very cumbersome. Therefore, a solution that can automatically sort, narrow down, and provide insights on various news is desired.

Summary of the Invention

[0003] In a first aspect of the present disclosure, an information presentation method is provided. The method includes receiving a query for an event graph, where the query instructs at least a target event to be searched; presenting, as a result of the query, a target event graph including a plurality of nodes and at least one directed edge connecting the plurality of nodes, where the plurality of nodes respectively represent the target event and one or more events related to the target event, and the at least one directed edge represents an event relationship between the events represented by the connected nodes; presenting time information of at least one event represented by at least one of the plurality of nodes with respect to at least one of the plurality of nodes.

[0004] A second aspect of the present disclosure provides an electronic device comprising at least one processing circuit, the at least one processing circuit is configured to receive a query for an event graph, the query specifies at least one target event to be searched for, and present as a result of the query a target event graph comprising a plurality of nodes and at least one directed edge connecting the plurality of nodes, each of which nodes represents a target event and one or more events associated with the target event, each of which directed edge represents an event relationship between events represented by the connected nodes, and for at least one node among the plurality of nodes, present temporal information for at least one event represented by the at least one node.

[0005] In some embodiments of the second aspect, at least one processing circuit is further configured to receive a selection for a first node among a plurality of nodes, the first node displays a first event, and in response to the selection of the first node, presents an occurrence time distribution for the first event, the occurrence time distribution indicating the frequency of occurrence of the first event within a historical time period.

[0006] In some embodiments of the second aspect, at least one processing circuit is further configured to receive a selection for a first time within a historical time period, and in response to the selection of the first time, present one or more media contents, and the occurrence of a first event in the first time is determined from one or more media contents.

[0007] In some embodiments of the second aspect, at least one processing circuit is further configured to receive a selection for a first directed edge in at least one directed edge, the first directed edge representing a first event relationship, and in response to the selection of the first directed edge, presenting one or more media contents, the first event relationship being determined from one or more media contents.

[0008] In some embodiments of the second aspect, at least one processing circuit further presents, with respect to a second node among a plurality of nodes, a second time in which a second event indicated by the second node occurs, and with respect to a third node among a plurality of nodes, a third time in which a third event indicated by the third node occurs, where the second event has a second event relationship with the third event, and the temporal order between the second time and the third time is configured to satisfy the second event relationship.

[0009] In some embodiments of the second aspect, the query further specifies the time range to be searched, and the time included in the time information is within the time range.

[0010] In some embodiments of the second aspect, the target event graph is determined based on the reference event graph, and each node in the reference event graph is associated with the occurrence time of the event represented by that node.

[0011] In some embodiments of the second aspect, at least one processing circuit is configured to construct a reference event graph as follows: generate an individual event graph corresponding to media content, the individual event graph including at least a fourth node indicating a fourth event, a fifth node indicating a fifth event, and a third directed edge indicating a third event relationship between the fourth and fifth events, the fourth event, the fifth event, and the third event relationship being determined from the media content, the fourth time when the fourth event occurs and the fifth time when the fifth event occurs based on the media content, the first similarity between the fourth event and the sixth event indicated by the sixth node in the reference event graph, and the second similarity between the fifth event and the seventh event indicated by the seventh node in the reference event graph, and the reference event graph being updated using the fourth and fifth times based on the first similarity, second similarity, first threshold, and second threshold which is smaller than the first threshold.

[0012] In some embodiments of the second aspect, at least one processing circuit is further configured to add a directed edge indicating a third event relationship between the sixth and seventh nodes in response to the first similarity exceeding a first threshold and the second similarity exceeding a first threshold, to store the fourth time in relation to the sixth node in the reference event graph, and to store the fifth time in relation to the seventh node in the reference event graph.

[0013] In some embodiments of the second aspect, at least one processing circuit is further configured to add an eighth node representing a fifth event in the reference event graph in response to the first similarity exceeding a first threshold and the second similarity being less than a second threshold, to add a directed edge representing a third event relationship between the sixth and eighth nodes, to store a fourth time in relation to the sixth node in the reference event graph, and to store a fifth time in relation to the eighth node in the reference event graph.

[0014] In some embodiments of the second aspect, at least one processing circuit is configured to add individual event graphs to the reference event graph in response to the first and second similarity scores being between the first and second thresholds, to add indications that the fourth and sixth events are similar and that the fifth and seventh events are similar in the reference event graph, to store the fourth time in relation to the fourth node in the reference event graph, and to store the fifth time in relation to the fifth node in the reference event graph.

[0015] A third aspect of the present disclosure provides an electronic device comprising at least one processing unit and at least one memory, the at least one memory being coupled to the at least one processing unit and configured to store instructions to be executed by the at least one processing unit. When instructions are executed by the at least one processing unit, the device performs the method of the first aspect.

[0016] A fourth aspect of this disclosure provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium, and the computer program is executed by a processor to realize the method of the first aspect.

[0017] Furthermore, the contents described in the summary section of the present invention do not limit the key or important features of the embodiments of this disclosure, nor do they limit the scope of this disclosure. It should be understood that other features of this disclosure can be more readily understood from the following description. [Brief explanation of the drawing]

[0018] The above and other features, advantages and aspects of each embodiment of this disclosure will become clearer by referring to the following detailed description in conjunction with the attached drawings. In the attached drawings, the same or similar reference numerals indicate the same or similar elements.

[0019] [Figure 1] This is a schematic diagram illustrating an exemplary environment in which the embodiments of this disclosure may be realized. [Figure 2] This is a flowchart illustrating the process of constructing a reference matter graph according to some embodiments of this disclosure. [Figure 3] This is a schematic diagram illustrating how time elements are associated with individual event graphs according to some embodiments of the present disclosure. [Figure 4A] This figure shows examples of reference matter graph updates according to some embodiments of the present disclosure. [Figure 4B] This figure shows examples of reference matter graph updates according to some embodiments of the present disclosure. [Figure 4C] This figure shows examples of reference matter graph updates according to some embodiments of the present disclosure. [Figure 5] This is a schematic diagram showing a user interface in which search criteria are specified by the user according to some embodiments of the present disclosure. [Figure 6] This is a schematic diagram illustrating how to eliminate unreasonable event chains in some embodiments of the present disclosure. [Figure 7A]A diagram illustrating an example of visual presentation of query results according to some embodiments of the present disclosure. [Figure 7B] A diagram illustrating an example of visual presentation of query results according to some embodiments of the present disclosure. [Figure 7C] A diagram illustrating an example of visual presentation of query results according to some embodiments of the present disclosure. [Figure 7D] A diagram illustrating an example of visual presentation of query results according to some embodiments of the present disclosure. [Figure 8] A flowchart showing the process of information presentation according to some embodiments of the present disclosure. [Figure 9] A block diagram showing an electronic device of multiple embodiments for implementing the present disclosure.

Embodiments for Implementing the Invention

[0020] Hereinafter, embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the accompanying drawings, the present disclosure can be implemented in various forms and is not limited to the embodiments here. It should be understood that these embodiments are used to understand the present disclosure more thoroughly and completely. It should be understood that the accompanying drawings and embodiments of the present disclosure are only used for illustrative purposes and are not intended to limit the protection scope of the present disclosure.

[0021] Note that it should be noted that the titles of all sections / subsections provided in this specification are not restrictive. Various embodiments are described throughout this specification, and any embodiment can be included in any section / subsection. Furthermore, the embodiments described in any section / subsection can be combined with any other embodiments described in the same section / subsection and / or different sections / subsections in any form.

[0022] In describing the embodiments of this disclosure, the terms “including” and similar terms should be understood as broadly including, i.e., “including, but not limited to.” The term “based on” means “based at least in part.” “One embodiment” or “the embodiment” means “at least one embodiment.” “Several embodiments” means “at least several embodiments.” The following may include explicit and implicit definitions.

[0023] As used herein, the term “circuit” means hardware circuitry and / or a combination of hardware circuitry and software. For example, a circuit may be a combination of analog and / or digital hardware circuitry and software / firmware. Another example is a circuit which may be any part of a hardware processor including software, which includes (multiple) digital signal processors, software and (multiple) memories, which work together to operate the device and perform various functions. Another example is a circuit which may be hardware circuitry and / or a processor, such as a microprocessor or a part of a microprocessor, which requires software / firmware for operation, but may not have software if operation is not required. As used herein, the term “circuit” may include hardware circuitry or processors only, or parts of hardware circuitry or processors and / or their associated software and / or firmware implementations.

[0024] As used herein, the term “event” refers to a phenomenon or change of state consisting of one or more actions involving one or more event entities at a specific time and space.

[0025] Exemplary Environment and Basic Principles Figure 1 is a schematic diagram of an exemplary environment 100 in which embodiments of the present disclosure may be realized. In environment 100, an electronic device 150 receives a query 110 from a user for an event graph. The query 110 specifies at least one event to be searched for, also called a target event or event of interest. The electronic device 150 further presents a target event graph 130 as a result of the query 110. As shown in Figure 1, the target event graph 130 includes several nodes, each node representing one event. One of these nodes represents a target event, and one or more other nodes represent events related to the searched target event. The target event graph 130 further includes at least one directed edge, each directed edge representing a relationship between events indicated by the nodes connected by it, also called an event relationship.

[0026] The target event graph 130 is determined from a larger event graph (also called a reference event graph). In comparison to the target event graph 130, the reference event graph may be considered a global event graph. In some embodiments, the reference event graph is constructed for a specific field, such as finance or semiconductors. Alternatively, the reference event graph may be constructed across multiple fields, or without any specific fields. The reference event graph can depict the relationships between various different events from a global perspective.

[0027] The target event graph 130 may be a part of the reference event graph (also called a sub-bluff), or a variation of a sub-bluff of the reference event graph. In some embodiments, the electronic device 150 can store or access the reference event graph. Thus, the electronic device 150 can search the reference event graph based on the conditions specified by the query 110 to determine and present the target event graph 130.

[0028] In some other embodiments, as shown in Figure 1, the electronic device 150 may send a query 110 to an electronic device 120 (for example, a service-side device providing an event graph search service) and receive information about a target event graph 130 from the electronic device 120. That is, in such embodiments, the electronic device 120 performs a search based on the conditions specified by the query 110.

[0029] In environment 100, the electronic device 150 may be any device having computing capabilities, including terminal devices. Terminal devices may be any mobile terminal, fixed terminal or portable terminal, and include mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia computers, personal communication system (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, locator devices, television receivers, radio receivers, e-book devices, game devices, or any combination thereof, accessories and peripherals including such devices, or any combination thereof. The electronic device 120 may be any device having computing capabilities, such as server-side devices. Server-side devices may include, for example, computing systems / servers, such as mainframes, edge computing nodes, and computing devices in a cloud environment.

[0030] The structure and function of Environment 100 are described for illustrative purposes only and do not constitute any limitation of the scope of this disclosure. For example, Environment 100 may further include a reference matter graph. Furthermore, the structure and style of the target matter graph 130 shown in Figure 1 are illustrative and not intended to limit the scope of this disclosure.

[0031] To provide users with the desired query results, it is necessary to search the global events graph. As the events graph database continues to expand, the number of events and relationships between events included in the global events graph increases, sometimes reaching millions or even tens of millions. The events in the global events graph are derived from a vast amount of historical news, reports, and other text. Each event may be associated with multiple texts, and users may spend considerable time searching for the text corresponding to an event or the relationships between events.

[0032] In another aspect, history is always similar, and each event in the global events graph may have occurred many times in history. By visually displaying how many times an event has occurred in history and at what specific time, users can perceive patterns in how events occur. When users search for events graphs of interest, failing to consider the temporal factor can lead to illogical event chains and potentially mislead users.

[0033] While large-scale event graphs provide a foundation for users to perform event searches, current search and visualization methods are still relatively homogeneous. Temporal elements are not considered in the search process, nor is any information related to temporal elements presented to the user when displaying search results.

[0034] To address one or more of the above problems and other potential problems, embodiments of the present disclosure provide solutions for presenting information. According to one or more embodiments, a query is received for an event graph, the query indicating at least a target event to be searched for. As a result of the query, a target event graph is presented, which includes a plurality of nodes and at least one directed edge connecting the plurality of nodes. Each of these nodes represents a target event and one or more events associated with the target event, and the directed edge indicates the event relationships between the events represented by the connected nodes. For at least one of these nodes, temporal information of the event represented by each node is presented.

[0035] In the embodiments of this disclosure, query results are presented to the user, along with time information of events within those results. This allows the user to gain a deeper understanding of the event timing rules. In this way, the user can gain insight into the evolutionary rules of events, thereby improving the user experience.

[0036] Exemplary construction process of a reference graph To better understand the presentation of the event graph query results, the following describes an exemplary process for constructing a reference event graph as a search source. In this exemplary process, the reference event graph is constructed based on various media content.

[0037] Media content may be in any appropriate format that can provide information. For example, media content may be a news report in the form of text, images, audio, video, or a combination thereof. Media content may be media content obtained from various platforms (e.g., news platforms) or used and stored media content. In the case of text-based media content, information for constructing an event graph may be directly extracted from the text. In the case of media content in the form of images, videos, audio, etc., information for constructing an event graph may be extracted from images, audio, or video using any known or future-developed technology. For example, relevant information can be directly extracted from image, video, or audio formats based on image recognition or speech recognition technology.

[0038] The electronic device 120 first generates an event graph corresponding to a single media content, also called an individual event graph. The individual event graph is used to show events extracted from a single media content and the relationships between those events. For this reason, the individual event graph contains multiple nodes, each representing multiple events extracted from the media content. The individual event graph further includes at least one directed edge that shows event relationships between different events. Then, the reference event graph is updated using the individual event graph.

[0039] Figure 2 is a flowchart showing the process 200 for constructing a reference event graph according to some embodiments of this disclosure. The process 200 will be described below using the case where the construction of the reference event graph is realized using an electronic device 120 as an example, but this is merely illustrative and not intended to be limiting in any way.

[0040] In block 210, the electronic device 120 collects media content. Media content may include, for example, current political news, social news, and general scientific information. If news is used as an example of media content, the electronic device 120 can periodically collect news based on a list of news websites, via interfaces provided by those websites. The list of news websites may include, for example, mainstream news platforms, industry-specific news platforms, policy announcement platforms, and knowledge-sharing platforms. The list of news websites may be specified by the user.

[0041] In block 220, the electronic device 120 performs a duplicate removal process on the collected media content. The media content may be, for example, current political news, and the example will be explained using the case where news is collected from a list of news websites. There may be cross-referencing or reprinting of news from different news websites, so the collected news may be duplicates. The electronic device 120 may filter the collected news based on a duplicate removal algorithm.

[0042] In some embodiments, the electronic device 120 deduplication processing of collected media content using the Simhash algorithm. The deduplication process includes steps such as word segmentation, hash value calculation, weighting, merging, dimensionality reduction, and deduplication. Specifically, the electronic device 120 may perform word segmentation on the text in the media content or the text recognized or transformed from the media content to obtain valid feature vectors, and further weight each feature vector. The electronic device 120 may calculate the hash value of each feature vector using a hash function and weight each feature vector. The electronic device 120 may further weight the feature vectors based on their hash values. Furthermore, the electronic device 120 may accumulate the weighting results of each feature vector to obtain a sequence string. The electronic device 120 determines each digit of the sequence string. Digits greater than or equal to 0 are set to 1, and digits less than 0 are set to 0. In this way, the electronic device 120 obtains a Simhash value corresponding to the media content. Finally, the electronic device 120 calculates a new hash distance between any two media contents based on the Simhash value of each media content. If the hash distance is less than a predetermined threshold, the two media contents are considered to be duplicates. The electronic device 120 then deletes one of the media contents to perform the deduplication process.

[0043] Note that the Simhash algorithm is merely an example. In the embodiments of this disclosure, duplicate removal may be achieved using any suitable algorithm.

[0044] In block 230, the electronic device 120 extracts events and event relationships. Block 230 may be performed on any media content after deduplicating, or on each media content. The electronic device 120 automatically extracts events and event relationships from the deduplicated media content based on an event extraction algorithm. One or more events can be extracted from a single media content. In some cases, no events may be extracted from a given media content. Event relationships may include those event relationships described with reference to Figure 1 above. For example, in the news item "Enriching feed sources to cope with rising aquaculture costs due to rising feed prices," the electronic device 120 can extract the first event "rising feed prices," the second event "increasing aquaculture costs," and the causal relationship between the two.

[0045] Furthermore, in some embodiments, the electronic device 120 may further determine the relevance of event relationships, also referred to herein as the relevance coefficient. The relevance can indicate the strength of the event relationship, the probability of event transfer, or the likelihood of the event relationship. In some embodiments, the electronic device 120 can store the relevance of event relationships indicated by a directed edge in relation to the directed edge.

[0046] In block 230, events and event relationships can be extracted using any appropriate event extraction algorithm. Examples of event extraction algorithms include classification-based event extraction methods, sequence labeling-based event extraction methods, comprehension-based event extraction methods, and generation-based event extraction methods. The scope of this disclosure is not limited in this respect.

[0047] As an example, the electronic device 120 extracts events and event relationships using an event extraction algorithm based on sequence labeling. Continuing with the example of news text, the electronic device 120 may preprocess the deduplication news text by filtering, for example, removing extra spaces, garbled characters, executing text phrases, and substituting interfering strings. The electronic device 120 can train a sequential event string sequence model to recognize the start and end positions of events in the preprocessed news text and obtain descriptive fragments of events, i.e., event names. Event names typically include the event's trigger word, which defines the event type. Furthermore, based on the event's trigger word, the electronic device 120 can determine event relationships between events and calculate the degree of relevance between events.

[0048] In block 240, the electronic device 120 extracts event elements such as time. The electronic device 120 can extract event elements that an event possesses. Event elements include, but are not limited to, the event subject, event object, time, place, person, industry, company, product, etc. Depending on the amount of information in the media content, each event may have one or more event elements, or may have no event elements at all. For example, the event "Increased Aquaculture Costs" and its corresponding event elements are extracted from a news text. The event elements of the event "Increased Aquaculture Costs" include the time element "April 1, 2022", the industry element "Aquaculture Industry", and the place element "XX Prefecture", etc. The electronic device 120 extracts at least the time element of the event and may extract other elements as well. The time element of the event indicates the time the event occurred. If the time element of an event cannot be extracted from the media content, the publication time of the media content may be used as the time the event occurred.

[0049] Next, the electronic device 120 may generate an individual event graph. Specifically, the electronic device 120 generates an individual event graph based on the events and event relationships extracted in block 230. Continuing with the aquaculture industry example described above, the generated individual event graph includes a node representing the first event "feed price increase," a node representing the second event "aquaculture cost increase," and a directed edge connected between these two nodes to show the causal relationship between the two events. In this example, the directed edge points from the node representing the first event "feed price increase" to the node representing the second event "aquaculture cost increase."

[0050] The electronic device 120 further associates event elements, such as time elements, with corresponding events in the individual event graph. For example, the time elements of an event are stored as attributes of the event and associated with the node representing that event. Figure 3 is a schematic diagram of how time elements are associated with the individual event graph according to some embodiments of the present disclosure. In the example in Figure 3, the electronic device 120 extracts from the media content event A, represented by node 301, event B, represented by node 302, the event relationship between event A and event B, and the time elements corresponding to each event. Specifically, the electronic device 120 extracts the occurrence time TA of event A and the occurrence time TB of event B. Thus, time TA is associated with node 301 representing event A, and time TB is associated with node 302 representing event B.

[0051] The above has been an example of the process for constructing an individual event graph. However, this is merely an example, and it should be understood that individual event graphs can be constructed in any appropriate manner in the embodiments of this disclosure. Furthermore, the events, event relationships, number of events, and event elements described above are merely illustrative and are not intended to limit the scope of this disclosure.

[0052] Refer to Figure 2 again. In block 250, the electronic device 120 calculates the similarity between an event in the individual event graph and an event in the reference event graph. The similarity is calculated based on the event name, event elements, etc. As an example, the electronic device 120 may determine the similarity between events based on Jaccard similarity. Referring to the example in Figure 3, the electronic device 120 compares event A in the individual event graph with another event in the reference event graph. It performs word segmentation on the name of event A and the elements it has to obtain a first word segmentation set for event A. The electronic device 120 performs word segmentation on the name of the event to be compared in the reference event graph and the elements it has to obtain a second word segmentation set. Based on the first and second word segmentation sets, the electronic device 120 determines the number of words in the intersection set of these two sets and the number of words in the concatenated set of these two sets. Furthermore, the electronic device 120 calculates the Jaccard similarity by calculating the numerical ratio of the number of words in the intersection set to the number of words in the concatenated set.

[0053] The Jaccard similarity described above is merely one example of how to determine the similarity between events. Any suitable similarity calculation method may be used in the embodiments of this disclosure.

[0054] In block 260, the electronic device 120 updates the reference event graph. Specifically, the electronic device 120 may update the reference event graph using the individual event graph. In this specification, updating the reference event graph is also referred to as merging the individual event graph and the reference event graph. Merging may mean merging one or more nodes in the individual event graph with one or more nodes in the reference event graph, or adding the individual event graph itself as part of the reference event graph. The specific operations are merely illustrative and are not intended to limit the scope of this disclosure. Therefore, the individual event graph may be considered an event graph sub-bluff with respect to the reference event graph or the global event graph.

[0055] The individual event graph and the reference event graph are merged based on similarity. The electronic device 120 merges the individual event graph and the reference event graph based on the relationship between the similarity value and one or more pre-defined thresholds. In some embodiments, two thresholds, namely a first threshold and a second threshold, may be pre-defined, with the first threshold being greater than the second threshold. If the similarity between two events being compared is greater than the first threshold, these two events may be considered identical. Therefore, the electronic device 120 can merge nodes in the individual event graph with nodes in the reference event graph that correspond to them without adding new nodes to the reference event graph. The event occurrence time associated with a node in the individual event graph is added to or associated with the corresponding node in the reference event graph.

[0056] If the similarity between two events is less than a second threshold, these two events are considered independent events. Therefore, the electronic device 120 may add nodes in the individual events graph to the reference events graph to achieve graph fusion. The event occurrence times associated with nodes in the individual events graph are also added to the reference events graph accordingly.

[0057] If the similarity between two events lies between a first threshold and a second threshold, the two events can be considered similar events. Therefore, the electronic device 120 may add nodes in the individual events graph to the reference events graph and establish indications of similarity relationships for similar events (e.g., represented by directed edges of different styles). The event occurrence times associated with nodes in the individual events graph are also added to the reference events graph accordingly.

[0058] Figures 4A to 4C show examples of updating reference matter graphs in several embodiments of this disclosure. The examples in Figures 4A to 4C will be explained in conjunction with Figure 3.

[0059] In the example in Figure 4A, the individual event graph includes node 301 representing event A and node 302 representing event B. The occurrence time TA of event A is stored in relation to node 301, and the occurrence time TB of event B is stored in relation to node 302. The electronic device 120 performs a traversal calculation of the similarity between events A and B and the events represented by each node in the reference event graph (in the figure, dashed arrows indicate the similarity calculation between the two events, but not all dashed arrows of the traversal calculation are shown). The similarity between event A and the event represented by node 401 in the reference event graph is greater than the first threshold (e.g., 0.9). The electronic device 120 merges node 301 and node 401. Before merging, the event occurrence times T1 and T2 are stored in relation to node 401. After merging, the occurrence time TA of event A is also stored in relation to node 401. The similarity between event B and the event represented by node 402 in the reference event graph is also greater than the first threshold (e.g., 0.9). The electronic device 120 merges nodes 302 and 402. Before merging, event occurrence times T3 and T4 are stored in relation to node 402. After merging, the occurrence time TB of event B is also stored in relation to node 402. Simultaneously, a directed edge 411 pointing from node 401 to node 402 is added to the reference event graph for the original relationship between event A and event B. As shown in the figure, after merging, instead of adding a new node to the reference event graph, a directed edge between event A and event B is added, and the occurrence times of events A and B are also added.

[0060] In the example in Figure 4B, the electronic device 120 performs a traversal calculation of the similarity between events A and B in the individual event graph and each event in the reference event graph (only the dashed arrows representing part of the traversal calculation are shown in the figure). The similarity between event A and the event represented by node 401 in the reference event graph is greater than the first threshold (e.g., 0.9). The electronic device 120 merges node 301 and node 401. Before merging, event occurrence times T1 and T2 are stored in relation to node 401. After merging, the occurrence time TA of event A is also stored in relation to node 401. The similarity between event B and the events represented by each node in the reference event graph is all less than the second threshold (e.g., 0.6). The electronic device 120 adds node 404 representing event B to the reference event graph and stores the occurrence time TB of event B in relation to node 404. Therefore, in order to preserve the original relationship between event A and event B, a directed edge 412 is added to the reference event graph, pointing from node 401 to node 404. After merging, a new node is added to the reference event graph, a directed edge is added between event A and event B, and the occurrence times of events A and B are added.

[0061] In the example in Figure 4C, the electronic device 120 performs a traversal calculation of the similarity between events A and B in the individual event graph and each event in the reference event graph (only the dashed arrows representing part of the traversal calculation are shown in the figure). The similarity between event A and the event indicated by node 401 in the reference event graph lies between the first and second thresholds. Therefore, the electronic device 120 adds node 301 to the reference event graph and adds a directed edge 413 (bidirectional edge) between node 301 and node 401 to indicate that event A and the event indicated by node 401 have a similarity relationship. In the reference event graph, the occurrence time TA of event A is stored in relation to node 301. The similarity between event B and the event indicated by node 402 in the reference event graph lies between the first and second thresholds. Therefore, the electronic device 120 adds node 302 to the reference event graph and adds a directed edge 414 (bidirectional edge) between node 302 and node 402 to indicate that event B and the event indicated by node 402 have a similarity relationship. In the reference event graph, the occurrence time TB of event B is stored in relation to node 302. After merging, a new node is added to the reference event graph, indicating similarity relationships between events similar to event A and events similar to event B, and the occurrence times of events A and B are added.

[0062] The process of updating the reference event graph described above can be considered an incremental construction of the reference event graph. Such incremental construction can be used to create the initial reference event graph and can be used to incrementally update the created reference event graph. The reference event graph is continuously updated by continuously merging added individual event graphs into the reference event graph. In this way, a rich and comprehensive event chain and event relationship network can be formed.

[0063] The above describes an exemplary process for constructing a reference event graph as a search source. The described process is illustrative and not intended to limit the scope of this disclosure. Embodiments of this disclosure may use a reference event graph containing time information of events constructed in any suitable manner.

[0064] Example of query result presentation As the reference event graph continues to expand as a search source, the number of events and relationships between them increases, sometimes reaching millions or even tens of millions. To make it easier for users to view event graphs related to events of interest, they can search event graphs according to user-specified criteria.

[0065] To determine search criteria, a user interface (UI) can be provided to allow the user to specify conditions. Through user-UI interaction, queries are received for the event graph. Such queries indicate at least the target event to be searched for, i.e., the event of interest or attention to the user. In some embodiments, the query may further specify the time range to be searched. The same event may show different developmental stages at different times. For example, due to factor XX, the YY event may show significant differences between related events in 2022 and related event presentations of the same event in the past. Therefore, including a time factor in the search criteria makes it easier to focus on the time range of interest to the user. Alternatively, the query may further specify other search criteria such as region or organization.

[0066] Figure 5 is a schematic diagram of a user interface in which search criteria are specified by a user according to some embodiments of the present disclosure. For example, UI 510 is provided by an electronic device 150. Through UI 510, the user can input one or more search criteria. In the example of Figure 5, UI area 501 is available for the user to input the event to be searched for, i.e., to specify the target event. UI area 502 is available for the user to input a time range of interest. UI area 503 is available for the user to input a region, for example, the region where the target event occurred.

[0067] As shown in Figure 5, the user specifies Event C as the target event, the time range from TS to TE, and the region A. The user may then click the "Search" button 504 to submit a query for the event graph.

[0068] The UI and search criteria shown in Figure 5 are for illustrative purposes only and are not intended to limit the scope of this disclosure. In the embodiments of this disclosure, the user may be provided with any appropriate UI to specify the query.

[0069] After the user submits a query, the electronic device 150 searches the reference event graph and obtains the target event graph as the query result. Alternatively, the electronic device 150 may also send a request for the query to the electronic device 120, in which case the electronic device 120 may search the reference event graph and obtain the target event graph as the query result. The target event graph may be at least a part of the reference event graph, or may be determined based on at least a part of the reference event graph.

[0070] In some embodiments, when the search criteria include a time range, it should be understood that, during the search, the time information of the events shown by the target event graph falls within that time range, by considering the time range. In other words, the events shown by the target event graph occurred within that time range.

[0071] In some embodiments, the temporal information contained in the reference event graph can be used during the search. Specifically, during the search, the temporal information of events is used as a constraint so that the temporal order between different events that have event relationships in the target event graph satisfies the event relationships between them. In other words, during the search, event chains that do not logically satisfy the event relationships can be removed.

[0072] Figure 6 is a schematic diagram of the removal of an unreasonable event chain according to some embodiments of the present disclosure. As shown in Figure 6, based on certain media content, an individual event graph 610 is generated showing that events D and E have an event relationship, and based on the media content, event D has an occurrence time TD and event E has an occurrence time TD+1, which is after TD. Based on other media content, an individual event graph 620 is generated showing that events E and F have an event relationship, and based on the media content, event E has an occurrence time TD-2 and event F has an occurrence time TD-1. A sub-graph 630 is generated as part of a reference event graph by the fusion method described above with reference to Figures 4A to 4C. The time information in individual event graphs 610 and 620 is also fused into the reference event graph.

[0073] Arrows in the event graph indicate relationships between two events, such as causal relationships or sequential relationships, and also imply temporal relationships. When searching the event graph based on user-defined conditions, the time information of events can be used as a constraint.

[0074] In the example in Figure 6, event chains 640 and 650 can be derived based on sub-bluff 630. In event chain 640, the occurrence time TD-1 of event F is earlier than the occurrence time TD+1 of event E. In other words, in this chain, the temporal order between events E and F does not satisfy the event relationship between them. Similarly, in event chain 650, the occurrence time TD-2 of event E is earlier than the occurrence time TD of event D. In other words, in this chain, the temporal order between events E and D does not satisfy the event relationship between them. Therefore, event chains 640 and 650 are irrational event chains and, as a result, do not appear in the target event graph related to event D.

[0075] By using event time information as a constraint during the search, logical errors such as the occurrence time of a previous event being later than a later event can be avoided, resulting in a more rational search of the event chain. In this way, more rational query results can be provided to the user, offering more accurate support for subsequent decision-making.

[0076] After obtaining the target event graph, the electronic device 150 can present the target event graph as a query result. The target event graph includes multiple nodes and at least one directed edge connecting these nodes, each of which represents a target event and one or more events related to the target event, and each directed edge represents the event relationships between the events represented by the connected nodes. For at least one of these nodes, time information for the event represented by that node can be presented. In particular, time information is presented for each node.

[0077] Figure 7A shows an example of a visual presentation of query results. The presented target event graph 700 includes node 701-1 representing event C, node 701-2 representing event G, node 701-3 representing event H, node 701-4 representing event K, node 701-5 representing event L, node 701-6 representing event M, and node 701-7 representing event N, which are collectively referred to as node 701. The target event graph 700 further includes directed edges that represent event relationships, for example, directed edge 702 that represents the event relationship between event G and event M.

[0078] For each node 701, time information for the corresponding event, such as the occurrence time, is provided. Specifically, the occurrence time TC for event C, TG for event G, TH for event H, TK for event K, TL for event L, TM for event M, and TN for event N are shown.

[0079] By including event time information in the query results, users can understand the time interval between previous and subsequent events, making it easier to predict event trends and occurrence times.

[0080] The user can interact with the presented target event graph to obtain richer information. Event relationships in the event graph are extracted from media content (e.g., news). Taking this into consideration, the source of the event relationship can be presented to the user. In some embodiments, a selection for a directed edge in the target event graph can be received. Thus, one or more media contents of the event relationship indicated by the directed edge determined therefrom are presented, i.e., the source of the event relationship indicated by the directed edge is presented. If multiple media contents exist, they may be presented to the user at once or in a switchable manner.

[0081] Figure 7B shows an exemplary presentation of event-related sources. In this example, directed edge 702 is selected, and for example, the user clicks directed edge 702. In response, media content 710 is presented. In addition, the text of related events (events M and G in this example) in the selected directed edge and media content is highlighted.

[0082] In such an embodiment, a user can select an event relationship in the event graph and obtain the news source for that event relationship. The event graph itself is highly generalized, and in this way, users can view the event graph and simultaneously obtain its source, allowing them to understand the event relationships of interest concretely and intuitively.

[0083] An event may occur multiple times throughout history. Taking this into consideration, in some embodiments, information related to the historical occurrence of an event is provided to the user. Specifically, the user can select a node in a presented event graph. In response, the occurrence time distribution of the event indicated by the selected node can be presented. The occurrence time distribution indicates the frequency of occurrence of the corresponding event within a historical time period. The range of this historical time period may be the same as, or different from, the time range specified by the user in the search criteria. In particular, in some embodiments, the range of the historical time period may be greater than the time range specified in the search criteria. In this way, more comprehensive event information can be provided to the user.

[0084] Figure 7C shows an exemplary presentation of the occurrence time distribution. In this example, it is shown that node 701-2 of event G has been selected. Therefore, the occurrence time distribution 721 of event G is displayed. Furthermore, node 701-2 is highlighted. It is shown that node 701-6 of event M has been selected. Therefore, the occurrence time distribution 722 of event M is displayed. Node 701-6 is also highlighted.

[0085] In such embodiments, the user sequentially displays multiple nodes and sequentially displays the occurrence time distribution of the corresponding events. The user may also select multiple nodes at once and display the occurrence time distribution of the corresponding events simultaneously. By providing the user with the occurrence time distribution, the user can grasp the distribution rules of event occurrence times. Furthermore, by displaying the occurrence time distribution of events with event relationships, the user can intuitively grasp the degree of relevance between events. For example, in the example in Figure 7C, by comparing occurrence time distributions 721 and 722, the user can understand that not all occurrences of event G lead to the occurrence of event M.

[0086] Furthermore, in some embodiments, interaction with the distribution of occurrence times may be implemented. For example, a user may want to pay more attention to certain or some historical time periods and therefore want to know more about those historical time periods. In such cases, the user can select a time within a historical time period for the distribution of occurrence times of a given time. The electronic device 150 receives the selection of the time and may present one or more media contents as sources. That is, the occurrence of the event at that time is determined from the presented media contents.

[0087] Refer to the example in Figure 7D. The user selects time 703 to learn more details about event M that occurred at time 703. Therefore, media content 730 is presented as the source. That is, it is determined from media content 720 that event M occurred at time 703. In this way, the user can obtain more information about the event of interest without further searching.

[0088] Please note that the target event graphs, media content, and occurrence time distributions shown in Figures 7A to 7D are merely illustrative examples and are not intended to limit the scope of this disclosure. Furthermore, while all elements are shown in the same schematic diagram in these examples, please understand that in reality, some of these elements may be displayed in different UIs.

[0089] Exemplary process Figure 8 shows a flowchart of the information presentation process 800 according to some embodiments of the present disclosure. Process 800 may be carried out in at least one of the electronic devices 150 or 120.

[0090] In block 810, the electronic device 150 receives a query for the event graph. The query indicates at least one target event to be searched for.

[0091] In block 820, the electronic device 150 presents a target event graph as a query result, which includes multiple nodes and at least one directed edge connecting the multiple nodes. Each node represents a target event and one or more events associated with the target event, and each directed edge represents an event relationship between the events shown in the connected nodes.

[0092] In block 830, the electronic device 150 presents time information for at least one event represented by at least one node among a plurality of nodes.

[0093] In some embodiments, to present time information, the electronic device 150 receives the selection of a first node among a plurality of nodes, the first node representing a first event. In response to the selection of the first node, the electronic device 150 presents the occurrence time distribution for the first event, which indicates the frequency of occurrence of the first event within a historical time period.

[0094] In some embodiments, the electronic device 150 can receive a selection of a first time within a historical time zone. In response to the selection of the first time, the electronic device 150 presents one or more media contents, and the occurrence of a first event in the first time is determined from one or more media contents.

[0095] In some embodiments, the electronic device 150 receives a selection of a first directed edge among at least one directed edge, the first directed edge representing a first event relationship. In response to the selection of the first directed edge, the electronic device 150 presents one or more media contents, and the first event relationship is determined from one or more media contents.

[0096] In some embodiments, for a second node among multiple nodes, the electronic device 150 can indicate the second time in which the second event indicated by the second node occurs. For a third node among multiple nodes, the electronic device 150 can indicate the third time in which the third event indicated by the third node occurs. The second event has a second event relationship with the third event, and the temporal order between the second time and the third time satisfies the second event relationship.

[0097] In some embodiments, the query further specifies the time range to search, and the time included in the time information is within that time range.

[0098] In some embodiments, the target event graph is determined based on the reference event graph, and each node in the reference event graph is associated with the occurrence time of the event represented by that node.

[0099] In some embodiments, the reference event graph is constructed as follows, generating an individual event graph corresponding to the media content, the individual event graph including at least a fourth node indicating the fourth event, a fifth node indicating the fifth event, and a third directed edge indicating the third event relationship between the fourth and fifth events, the fourth event, the fifth event, and the third event relationship being determined from the media content, the fourth time when the fourth event occurs and the fifth time when the fifth event occurs are determined based on the media content, a first similarity between the fourth event and the sixth event indicated by the sixth node in the reference event graph, and a second similarity between the fifth event and the seventh event indicated by the seventh node in the reference event graph are determined, and the reference event graph is updated using the fourth and fifth times based on the first similarity, second similarity, first threshold, and second threshold which is smaller than the first threshold. Construction is performed, for example, by an electronic device 120.

[0100] In some embodiments, to update the reference event graph, directed edges indicating a third event relationship may be added between the sixth and seventh nodes in response to the first similarity exceeding a first threshold and the second similarity exceeding a first threshold. The reference event graph may store a fourth time in relation to the sixth node. The reference event graph may store a fifth time in relation to the seventh node.

[0101] In some embodiments, the reference event graph is updated. In response to the first similarity exceeding a first threshold and the second similarity being less than a second threshold, an eighth node representing the fifth event may be added to the reference event graph. A directed edge representing a third event relationship may be added between the sixth and eighth nodes. The fourth time may be stored in relation to the sixth node in the reference event graph. The fifth time may be stored in relation to the eighth node in the reference event graph.

[0102] In some embodiments, individual event graphs may be added to the reference event graph in response to both the first and second similarity scores being between the first and second thresholds, in order to update the reference event graph. Indicators that the fourth and sixth events are similar and that the fifth and seventh events are similar may be added to the reference event graph. The fourth time may be stored in relation to the fourth node in the reference event graph. The fifth time may be stored in relation to the fifth node in the reference event graph.

[0103] Exemplary device Figure 9 is a block diagram of one or more embodiments of the electronic device 900 that are implementable of this disclosure. It should be understood that the electronic device 900 shown in Figure 9 is merely illustrative and does not limit in any way the functions and scope of the embodiments described herein. The electronic device 900 shown in Figure 9 may be used to implement the electronic device 120 of Figure 1.

[0104] As shown in Figure 9, the electronic device 900 is in the form of a general-purpose electronic device. The components of the electronic device 900 include, but are not limited to, one or more processors or processing units 910, memory 920, storage device 930, one or more communication units 940, one or more input devices 950, and one or more output devices 960. The processing unit 910 may be an actual or virtual processor and performs various processes according to a program stored in the memory 920. In a multiprocessor system, multiple processing units execute computer executable commands in parallel to enhance the parallel processing capability of the electronic device 900.

[0105] The electronic device 900 typically includes multiple computer storage media. Such media may be any available media accessible to the electronic device 900, and may include, but are not limited to, volatile and non-volatile media, and removable and non-removable media. Memory 920 may be volatile memory (e.g., registers, caches, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or a combination thereof. Storage device 930 may be removable or non-removable media, and may be instrument-readable media, such as flash memory drives, magnetic disks, or any other media, and may store information and / or data (e.g., training data for training) that is accessible within the electronic device 900.

[0106] The electronic device 900 may further include other removable / non-removable, volatile / non-volatile storage media. Although not shown in Figure 9, a magnetic disk drive capable of reading from or writing to removable non-volatile magnetic disks (e.g., “floppy disks”) and an optical disk drive capable of reading from or writing to removable non-volatile optical disks may be provided. In these embodiments, each drive is connected to a bus (not shown) via one or more data media interfaces. The memory 920 may include a computer program product 925 having one or more program modules, which are configured to perform various methods or operations of various embodiments of the present disclosure.

[0107] The communication unit 940 can communicate with other electronic devices via a communication medium. Furthermore, the functions of the components of the electronic device 900 can be implemented as a single computing cluster or as multiple computing machines, and these computing machines can communicate via a communication connection. Therefore, the electronic device 900 can operate in a networked environment via logical connections to one or more other servers, network personal computers (PCs), or other network nodes.

[0108] The input device 950 may be one or more input devices, such as a mouse, keyboard, or tracking ball. The output device 960 may be one or more output devices, such as a display, speaker, or printer. The electronic device 900 may, if necessary, communicate via the communication unit 940 with one or more external devices (not shown), such as a storage device or display device, one or more devices for user-to-electronic device 900 interaction, or optional devices (e.g., a network card or modem) for communication between the electronic device 900 and one or more other electronic devices. Such communication may be performed via an input / output (I / O) interface (not shown).

[0109] According to exemplary embodiments of the present disclosure, the method described above is carried out when a computer-readable storage medium is provided, computer-executable instructions are stored therein, and the computer-executable instructions are executed by a processor. According to exemplary embodiments of the present disclosure, a computer program product is further provided, the computer program product is tangibly stored on a non-temporary computer-readable medium, includes computer-executable instructions, and the method described above is carried out when the computer-executable instructions are executed by a processor.

[0110] Herein, each aspect of the disclosure will be described with reference to flowcharts and / or block diagrams of methods, apparatus, devices, and computer program products implemented in accordance with the disclosure. Note that each block in the flowcharts and / or block diagrams, and each combination of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0111] These computer-readable program instructions are provided to a processing unit of a general-purpose computer, a dedicated computer, or other programmable data processing device to manufacture equipment, and when these instructions are executed by the computer or other programmable data processing device processing unit, the device realizes a function / operation specified in one or more blocks in a flowchart and / or block diagram. These computer-readable program instructions may be stored in a computer-readable storage medium, and these instructions cause a computer, programmable data processing device, and / or other device to operate in a specific manner, and the computer-readable medium on which the instructions are stored contains a product having various instructions for realizing a function / operation specified in one or more blocks in a flowchart and / or block diagram.

[0112] Computer-readable program instructions are loaded into a computer, other programmable data processing device, or other device; a series of operational steps are performed in the computer, other programmable data processing device, or other device to generate a computer implementation process; and the instructions executed in the computer, other programmable data processing device, or other device realize the functions / operations specified in one or more blocks in a flowchart and / or block diagram.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the implementable architectures, functions, and operations of systems, methods, and computer program products that may be implemented according to several embodiments of this disclosure. In this regard, each block in a flowchart or block diagram represents a module, program segment, or part of a directive, and a module, program segment, or part of a directive includes one or more executable directives for implementing a specified logical function. In some alternative embodiments, the functions attached to a block may occur in an order different from that shown in the accompanying drawings. For example, two consecutive blocks may be executed substantially in parallel, and such functions may be executed in reverse order. Also, each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, may be implemented by a system based on dedicated hardware that performs a specified function or operation, or by a combination of dedicated hardware and computer directives.

[0114] The above descriptions illustrate various aspects of the disclosure, but are not exhaustive and are not limited to the disclosed aspects. Many modifications and changes will be apparent to those skilled in the art, provided they do not deviate from the scope and spirit of the described aspects. The terminology used herein is chosen to best describe the principles, practical applications, or improvements in the technology in the market of each aspect, or to enable those skilled in the art to understand each embodiment disclosed herein.

Claims

1. A query is received for the event graph, and the query indicates at least the target event to be searched. The query presents a target event graph as a result of the query, which includes multiple nodes and at least one directed edge connecting the multiple nodes, where each of the multiple nodes represents the target event and one or more events related to the target event, and each of the at least one directed edge represents the event relationships between the events shown in the connected nodes. The aforementioned event-related matters will be determined based on information extracted from media content. To provide time information for the event indicated by at least one of the aforementioned multiple nodes, Furthermore, in response to the user's selection operation for the node, media content related to the time distribution of the event will be presented. Information presentation methods, including those mentioned above.

2. Presenting the aforementioned time information means The selection of the first node among the plurality of nodes is received, and the first node indicates the first event. The method according to claim 1, comprising presenting a time distribution for the first event in response to the selection of the first node, wherein the time distribution indicates the frequency of occurrence of the first event within a historical time period.

3. To receive a selection for the first hour within the aforementioned historical time period, The method according to claim 2, further comprising presenting one or more media contents in response to the selection of the first time, and determining whether the occurrence of the first event in the first time is determined from the one or more media contents.

4. A selection is received for a first directed edge among the at least one directed edge, and the first directed edge represents a first event relationship. The method according to claim 1, further comprising presenting one or more media contents in response to the selection of the first directed edge, and the first event relationship being determined from the one or more media contents.

5. Presenting the aforementioned time information means With respect to the second node among the plurality of nodes, the second time in which the second event indicated by the second node occurs is presented. With respect to the third node among the plurality of nodes, the third time in which the third event indicated by the third node occurs is provided, The method according to claim 1, wherein the second event has a second event relationship with the third event, and the temporal order between the second time and the third time satisfies the second event relationship.

6. The method according to claim 1, wherein the query further specifies a time range to be searched, and the time included in the time information is within the time range.

7. Each node in the reference event graph is associated with the occurrence time of the event represented by the node, The aforementioned event graph is merged with the aforementioned reference event graph to update the aforementioned reference event graph. The aforementioned target event graph is determined based on the aforementioned reference event graph, which is constructed based on multiple past media contents. The information presentation method described in claim 1.

8. The aforementioned reference graph is constructed as follows: A graph of individual events corresponding to the media content is generated, and the graph of individual events includes at least a fourth node representing a fourth event, a fifth node representing a fifth event, and a third directed edge representing a third event relationship between the fourth event and the fifth event, and the fourth event, the fifth event, and the third event relationship are determined from the media content. Based on the aforementioned media content, the fourth time when the fourth event occurs and the fifth time when the fifth event occurs are determined. Determine the first similarity between the fourth event and the sixth event indicated by the sixth node in the reference event graph, and the second similarity between the fifth event and the seventh event indicated by the seventh node in the reference event graph. The method according to claim 7, wherein the reference event graph is updated using the fourth and fifth time periods based on the first similarity, the second similarity, the first threshold, and the second threshold which is smaller than the first threshold.

9. Updating the aforementioned reference graph means In response to the first similarity exceeding the first threshold and the second similarity exceeding the first threshold, a directed edge indicating the third event relationship is added between the sixth node and the seventh node. To store the fourth time in relation to the sixth node in the aforementioned reference event graph, The method according to claim 8, comprising storing the fifth time in relation to the seventh node in the reference event graph.

10. Updating the aforementioned reference graph means In response to the first similarity exceeding the first threshold and the second similarity being less than the second threshold, an eighth node representing the fifth event is added to the reference event graph. Adding a directed edge between the sixth node and the eighth node that represents the third event relationship, To store the fourth time in relation to the sixth node in the aforementioned reference event graph, The method of claim 8, comprising storing the fifth time in relation to the eighth node in the reference event graph.

11. Updating the aforementioned reference graph means In response to the fact that both the first similarity and the second similarity are between the first threshold and the second threshold, the individual event graph is added to the reference event graph. Add to the aforementioned reference graph indications that the fourth event and the sixth event are similar, and that the fifth event and the seventh event are similar. In the aforementioned reference event graph, the fourth time is stored in relation to the fourth node, The method according to claim 8, comprising storing the fifth time in relation to the fifth node in the reference event graph.

12. An electronic device comprising at least one processing circuit, wherein the at least one processing circuit is configured to perform the method according to any one of claims 1 to 11.

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