JP7068404B2 - A method and system for providing a document timeline using clusters of issue units that are relevant over a long period of time. - Google Patents

Description

The following description relates to techniques for providing a document timeline.

In recent years, various studies have been conducted to systematically classify and group documents for intelligent information services such as information retrieval and recommendation.

Grouping, that is, clustering, is one of data mining, and is a technique of calculating the similarity based on the attributes of a large number of items and grouping them.

Clustering is the process of dividing a given data set into multiple clusters (Crusters) that have similarities to each other, and data belonging to one group is separated from data in different groups. It will have similarities.

As such a document clustering method, various methods such as a K-means clustering method and a clustering method using an ontology are being studied in the field of information retrieval.

For example, Patent Document 1 (publication date: September 27, 2011) discloses a technique for clustering documents by using an ontology including a keyword of a document.

Korean Registered Patent No. 10-1067819 Gazette

It provides a method and a system that can generate an issue cluster as a cluster group of issue units that are related in the medium / long term and provide a document timeline using the issue cluster.

A method of providing a document timeline performed by a computer system, wherein the computer system includes at least one processor configured to execute a computer-readable instruction contained in the memory. The step of creating an issue cluster as a cluster group by merging the clusters based on the similarity between clusters composed of similar documents by the at least one processor, and the issue by the at least one processor. Provided is a document timeline providing method including a step of displaying a timeline for a document included in the issue cluster using the cluster.

According to one aspect, the display step may include determining for display an issue cluster that includes a document identified by a user's selection or settings or a document identified by a content provider.

According to another aspect, the display stage includes a stage in which an issue cluster in which at least one of the number of documents, the elapsed time after clustering, and the number of comments meets a predetermined condition is determined as a display target. It's fine.

According to another aspect, in the display stage, the time domain in which the number of documents by unit time included in the issue cluster is displayed in a graph form and the document list included in the issue cluster are displayed by unit time. You may display a timeline that includes the displayed document area.

Further, according to another aspect, the navigation function may be provided by a structure in which the time domain and the document domain are organically connected.

Further, according to another aspect, the time domain may be scrollable in one direction, and the document area may include an interface capable of scrolling in a direction different from the time domain.

Further, according to another aspect, the time domain may be automatically scrolled according to the screen display of the document list according to the scrolling to the document area.

Further, according to another aspect, when the document area is scrolled, the time domain may be displayed in a simplified form in a reduced form of the size of the time domain or the graph of the time domain.

Further, according to another aspect, the display state or the hidden state of the time domain may be selectively applied according to the scrolling direction with respect to the document area.

According to yet another aspect, if a particular unit time graph bar is selected in the time domain, the document area may be scrolled into and displayed in the selected unit time document list.

Provided is a computer program recorded on a non-temporary computer-readable recording medium for the computer system to execute the document timeline providing method.

Provided is a non-temporary computer-readable recording medium in which a program for causing a computer to execute the document timeline providing method is recorded.

A computer system that includes at least one processor configured to execute computer-readable instructions contained in memory, said at least one processor based on the degree of similarity between clusters configured by similar documents. A computer including a cluster generator that creates an issue cluster as a cluster group by merging the clusters, and a cluster display unit that displays a timeline for documents included in the issue cluster using the issue cluster. Provide a system.

According to the embodiment of the present invention, by merging short-term clusters generated by time period based on the similarity between clusters, an issue cluster is generated as a cluster group of issue units related in the medium to long term. It is possible to use issue clusters to provide a document timeline that shows articles with high long-term relevance in chronological order.

It is a figure which showed the example of the network environment in one Embodiment of this invention. It is a block diagram for demonstrating the internal structure of the electronic device and the server in one Embodiment of this invention. It is a figure which showed the example of the component which the processor of a server can include in one Embodiment of this invention. It is a flowchart which showed the example of the method which a server can execute in one Embodiment of this invention. It is an exemplary diagram which showed the process of merging clusters based on the similarity between clusters in one Embodiment of this invention. It is an exemplary diagram which showed the process of merging clusters based on the similarity between clusters in one Embodiment of this invention. It is an exemplary diagram which showed the process of merging clusters based on the similarity between clusters in one Embodiment of this invention. It is an exemplary diagram which showed the process of merging clusters based on the similarity between clusters in one Embodiment of this invention. It is a flowchart which showed an example of the cluster merge process in one Embodiment of this invention. It is an exemplary diagram which showed the interface screen of the issue timeline using an issue cluster in one Embodiment of this invention. It is an exemplary diagram which showed the interface screen of the issue timeline using an issue cluster in one Embodiment of this invention. It is an exemplary diagram which showed the interface screen of the issue timeline using an issue cluster in one Embodiment of this invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention relate to document clustering techniques.

An embodiment including the matters specifically disclosed herein is a medium / long-term relevant issue unit by merging short-term clusters generated by time zone based on the similarity between clusters. Issue clusters can be created as cluster groups, and issue clusters can be used to provide a document timeline that shows articles with high long-term relevance in chronological order.

In the embodiment including the matters specifically disclosed in the present specification, a document having high long-term relevance is viewed at a glance by displaying a display area for a unit time and a document clustered for each unit time by an issue cluster. By providing a navigation function for document confirmation in a structure in which areas are organically connected, it is possible to improve user convenience.

FIG. 1 is a diagram showing an example of a network environment according to an embodiment of the present invention. The network environment of FIG. 1 shows an example including a plurality of electronic devices 110, 120, 130, 140, a plurality of servers 150, 160, and a network 170. Such FIG. 1 is merely an example for explaining the invention, and the number of electronic devices and the number of servers are not limited as in FIG.

The plurality of electronic devices 110, 120, 130, 140 may be fixed terminals or mobile terminals realized by a computer system. Examples of a plurality of electronic devices 110, 120, 130, 140 include AI speakers, smartphones, mobile phones, navigation systems, PCs (personal computers), notebook PCs, digital broadcasting terminals, PDAs (Personal Digital Assistants), and PMPs (PMPs). There are Portable Multimedia Players, tablets, game consoles, wearable devices, IoT (internet of things) devices, VR (visual reality) devices, AR (augmented reality) devices, and the like. As an example, FIG. 1 shows a smartphone as an example of the electronic device 110, but in the embodiment of the present invention, the electronic device 110 substantially utilizes a wireless or wired communication method, and another via the network 170. It may mean one of a variety of physical computer systems capable of communicating with the electronic devices 120, 130, 140 and / or the servers 150, 160.

The communication method is not limited, and not only a communication method using a communication network that can be included in the network 170 (for example, a mobile communication network, a wired Internet, a wireless Internet, a broadcasting network, a satellite network, etc.), but also a device. Short-range wireless communication between may be included. For example, the network 170 includes a PAN (personal area network), a LAN (local area network), a CAN (campus area network), a MAN (metropolitan area network), a WAN (wise Internet) network, etc. It may include any one or more of the networks. Further, network 170 may include, but is limited to, any one or more of network topologies, including bus networks, star networks, ring networks, mesh networks, star-bus networks, tree or hierarchical networks, and the like. Will not be done.

Each of the servers 150, 160 is realized by one or more computer devices that communicate with a plurality of electronic devices 110, 120, 130, 140 via a network 170 to provide instructions, codes, files, contents, services, and the like. good. For example, the server 150 may be a system that provides the first service to a plurality of electronic devices 110, 120, 130, 140 connected via the network 170, and the server 160 may also be a plurality of systems connected via the network 170. It may be a system that provides a second service to electronic devices 110, 120, 130, 140. As a more specific example, the server 150 is a service (as an example, a news service) aimed at by the application through an application which is a computer program installed and executed in a plurality of electronic devices 110, 120, 130, 140. Etc.) may be provided to a plurality of electronic devices 110, 120, 130, 140 as a first service. As another example, the server 160 may provide a service for distributing the above-mentioned application installation and execution files to a plurality of electronic devices 110, 120, 130, 140 as a second service.

FIG. 2 is a block diagram for explaining an internal configuration of an electronic device and a server according to an embodiment of the present invention. FIG. 2 describes the internal configuration of the electronic device 110 and the internal configuration of the server 150 as examples for the electronic device. Further, the other electronic devices 120, 130, 140 and the server 160 may have the same or similar internal configuration as the above-mentioned electronic device 110 or the server 150.

The electronic device 110 and the server 150 may include memories 211, 221s, processors 212, 222, communication modules 213, 223, and input / output interfaces 214, 224. The memory 211 and 221 are non-temporary computer-readable recording media, and are a RAM (random access memory), a ROM (read only memory), a disk drive, an SSD (sold state drive), and a flash memory (flash memory). Permanent mass recording devices such as, etc. may be included. Here, even if a permanent large-capacity recording device such as a ROM, SSD, flash memory, or disk drive is included in the electronic device 110 or the server 150 as another permanent recording device that is separated from the memories 211 and 221. good. Further, the memory 211 and 221 are installed with an operating system and at least one program code (for example, a browser installed and executed in the electronic device 110, or installed in the electronic device 110 to provide a specific service. Code for applications etc.) may be recorded. Such software components may be loaded from a computer-readable recording medium separate from the memories 211 and 221. Such other computer-readable recording media may include computer-readable recording media such as floppy (registered trademark) drives, discs, tapes, DVD / CD-ROM drives, and memory cards. In other embodiments, software components may be loaded into memory 211, 221 through communication modules 213, 223, which are not computer readable recording media. For example, at least one program is a computer program installed by a file provided by a file distribution system (eg, server 160 described above) that distributes a developer or application installation file via a network 170 (eg, described above). It may be loaded into the memory 211 or 221 based on the application.

Processors 212 and 222 may be configured to process instructions in a computer program by performing basic arithmetic, logic, and input / output operations. Instructions may be provided to processor 212, 222 by memory 211, 221 or communication modules 213, 223. For example, the processors 212 and 222 may be configured to execute instructions received according to a program code recorded in a recording device such as memories 211 and 221.

The communication modules 213 and 223 may provide a function for the electronic device 110 and the server 150 to communicate with each other via the network 170, and the electronic device 110 and / or the server 150 may provide another electronic device (as an example). , Electronic device 120) or another server (eg, server 160). As an example, a request generated by a processor 212 of an electronic device 110 according to a program code recorded in a recording device such as a memory 211 may be transmitted to a server 150 via a network 170 under the control of a communication module 213. On the contrary, control signals, instructions, contents, files, etc. provided under the control of the processor 222 of the server 150 are received by the electronic device 110 through the communication module 213 of the electronic device 110 via the communication module 223 and the network 170. May be done. For example, control signals, instructions, contents, files, etc. of the server 150 received through the communication module 213 may be transmitted to the processor 212 and the memory 211, and the contents, files, etc. may be further recorded by the electronic device 110. It may be recorded on a medium (permanent recording device described above).

The input / output interface 214 may be a means for an interface with the input / output device 215. For example, the input device may include a device such as a keyboard, mouse, microphone, camera, and the output device may include a device such as a display, speaker, haptic feedback device, and the like. As another example, the input / output interface 214 may be a means for an interface with a device that integrates functions for input and output, such as a touch screen. The input / output device 215 may be composed of an electronic device 110 and one device. Also, the input / output interface 224 of the server 150 may be a means for connecting to the server 150 or for interfacing with a device (not shown) for input or output that the server 150 can include. As a more specific example, when the processor 212 of the electronic device 110 processes an instruction of a computer program loaded in the memory 211, a service screen or content configured by using data provided by the server 150 or the electronic device 120. May be displayed on the display through the input / output interface 214.

Also, in other embodiments, the electronic device 110 and the server 150 may include more components than the components of FIG. However, most prior art components need not be clearly shown in the figure. For example, the electronic device 110 may be implemented to include at least a portion of the input / output devices 215 described above, and may further include other components such as transceivers, cameras, various sensors, databases, and the like. But it may be. As a more specific example, when the electronic device 110 is an AI speaker, various sensors generally included in the AI speaker, a camera module, various physical buttons, buttons using a touch panel, input / output ports, and vibrations. Various components such as a loudspeaker for the device 110 may be further incorporated into the electronic device 110.

In the following, specific embodiments of methods and systems for document clustering that are highly relevant over a long period of time will be described.

In the present specification, the document may mean an information unit to be searched or recommended on the Internet.

In this embodiment, articles provided through a news service will be described as a typical example of a document, but the target of clustering should not be limited to articles, and all provided on the Internet in units of information. It can be expanded and applied to documents in the form of.

Document clustering technology is used to effectively classify and convey many articles by subject, and based on the size and importance of clustered articles, a specific clustered article is used using a predetermined algorithm. Is also used to display at the top of the service screen.

Such a clustering technique clusters articles with similar contents, and the quality is improved when mainly the latest articles are used, but the quality of clustering decreases as the time range is widened. In addition, there is a limit to clustering current articles whose subject changes with time, and there is a problem that the processing time increases sharply as the number of articles increases.

An object of the present invention is to generate an issue cluster as a cluster group of issue units related in the medium to long term by merging short-term clusters generated by time zone.

FIG. 3 is a block diagram showing an example of components that the processor of the server can include in one embodiment of the present invention, and FIG. 4 is a block diagram of what the server executes in one embodiment of the present invention. It is a flowchart which showed the example of the possible method.

The server 150 according to the present embodiment may play the role of a news service platform for providing articles. In particular, the server 150 may effectively cluster and provide articles corresponding to medium / long-term issues.

As shown in FIG. 3, the processor 222 of the server 150 may include a cluster collection unit 310, a cluster generation unit 320, and a cluster display unit 330 as components for executing the document clustering method according to FIG. Depending on the embodiment, the components of processor 222 may be selectively included or excluded from processor 222. Also, depending on the embodiment, the components of processor 222 may be separated or merged to represent the functionality of processor 222.

Such a processor 222 and components of the processor 222 may control the server 150 to perform steps 410-450 included in the document clustering method of FIG. For example, the processor 222 and the components of the processor 222 may be implemented to execute an instruction by the code of the operating system included in the memory 221 and the code of at least one program.

Here, the components of the processor 222 may be representations of different functions executed by the processor 222 according to the instructions provided by the program code recorded in the server 150. For example, the cluster collection unit 310 may be used as a functional representation of the processor 222 that controls the server 150 according to the instructions described above so that the server 150 collects short-term clusters.

The processor 222 may read the necessary instructions from the memory 221 in which the instructions related to the control of the server 150 are loaded. In this case, the read instruction may include an instruction for controlling the processor 222 to execute steps 410 to 450 described below. The steps 410-450 described below may be performed in a different order than that shown in FIG. 4, and some of the steps 410-450 may be omitted or may include additional steps. ..

In the following, clusters bundled by articles that are highly related based on time are referred to as "short-term clusters", and when one issue unit is generated by being bundled as a highly related cluster, the cluster group corresponding to the issue unit. Is an "issue cluster".

Referring to FIG. 4, at step 410, the cluster collection unit 310 may collect short-term clusters clustered as similar articles based on the degree of similarity between articles. The cluster collection unit 310 may collect short-term clusters generated by clustering articles within a certain period of time in recent years. As the article clustering method for generating short-term clusters, at least one of the widely used clustering techniques may be used. At this time, a unique identifier (ID) may be assigned to each short-term cluster in the cluster generation process. During the work of article clustering, previously generated existing clusters may retain the previously assigned identifier.

For example, referring to FIG. 5, the cluster collecting unit 310 may generate a short-term cluster 501 by bundling them as one cluster when the similarity between the vectors of articles 50 different from each other is a certain level or more. At this time, the vector of each article 50 may mean the vector average of the words included in the corresponding article 50. The cluster collection unit 310 may bundle similar articles within the last 36 hours as a short-term cluster 501. Even if the identifier (ID) previously assigned to the short-term cluster 501 is maintained, articles that have passed 36 hours will be deleted from the cluster, and only articles within the last 36 hours will be displayed as service targets. May be done. In the embodiment of the present invention, when collecting the short-term cluster 501, all the articles deleted from the short-term cluster 501 over time may be accumulated and collected by the existing identifier (ID).

Referring to FIG. 4, at step 420, the cluster generator 320 may generate an issue cluster by merging short-term clusters based on the similarity between the clusters. Some of the short-term clusters are composed of articles with similar subjects, but they are often not bundled as one cluster or exist as different clusters due to the time difference of the articles. In order to solve such a problem, the cluster generation unit 320 may bundle the short-term clusters as one issue cluster when the short-term clusters meet the criteria for cluster merging, that is, when the similarity between the short-term clusters is a certain level or higher. ..

For example, referring to FIG. 6, when the similarity between the vectors of the short-term clusters 501 is equal to or higher than a certain level among the short-term clusters 501, the cluster generation unit 320 merges them as one cluster to generate the issue cluster 602. good. The vector of the short-term cluster 501 may mean the vector average of the articles contained in the cluster.

Similarity between clusters is applied as a criterion for cluster merging, but as an example, cluster vectors are compared and clusters in which at least one of the Euclidean and cosine values is within a defined range. It may be bundled as one cluster. For example, if the cosine similarity between the vectors of two clusters is 0.98 or higher, and / or if the Euclidean similarity between the vectors of the two clusters is 0.71 or higher, the two clusters are bundled as one cluster. It's okay. At this time, the similarity between the vectors may be defined as "1 / (distance between 1 + 2 vectors)".

In order to obtain the vector value of the cluster, in the past, when articles were added to the cluster, the method of newly calculating the overall average using the vector of the entire article was applied, but in such cases, there are many cases. It now includes API calls and a large number of calculations, and as the number of articles increases, so does the amount of calculations.

In the present embodiment, when the article n is added to the short-term cluster c, the new vector v'can be obtained at once by using the vector v previously calculated for the short-term cluster c, which is a mathematical formula. It may be defined as (1).

v' ₌ (vn + (v × _mc )) / (1 + _mc ) ・ ・ ・ (1)

Here, v _n means the vector value of the article n to be added, and mc means the number of existing articles included in the short-term cluster _c .

By such a method, the vector value of the short-term cluster to which the article is added can be easily and quickly obtained by using the vector value of the short-term cluster calculated previously.

Referring to FIG. 4, at stage 430, the cluster generator 320 may merge the newly generated short-term clusters based on the similarity between the clusters with the issue clusters generated at stage 420.

As shown in FIG. 7, the cluster generation unit 320 compares the vector of the issue cluster 602 generated in the stage 420 with the vector of the newly generated short-term cluster 501', and the vector similarity satisfying the criteria of cluster merger. The short-term cluster 501'may be included in the issue cluster 602. At this time, the vector of the issue cluster may mean the vector average of the short-term clusters included in the corresponding cluster, and the merge criterion of the short-term cluster and the issue cluster is equal to the merge criterion between the short-term clusters described above.

Referring to FIG. 4, at stage 440, the cluster generator 320 may merge the previously generated issue clusters with the issue clusters generated at stage 430 based on the similarity between the clusters. The merge criteria between issue clusters and issue clusters are the same as the merge criteria between short-term clusters described above.

As shown in FIG. 8, the cluster generator 320 compares the vector of the issue cluster generated by the merger of short-term clusters with the vector of the previously generated issue cluster 602', and vector similarity satisfying the criteria of cluster merger. If it has a degree, it may be merged as one issue cluster 602. In other words, the cluster generation unit 320 may compare the vectors between the issue clusters with each other and bundle them as one issue cluster 602 if the criteria for cluster merging are met. At this time, the cluster generation unit 320 may compare the number of articles of the issue cluster satisfying the criteria of cluster merger, and merge the articles of the remaining issue clusters into the issue cluster having a large number of articles.

In this embodiment, when a new short-term cluster c is added to the issue cluster C, or a small issue cluster C'(with a smaller number of articles) is merged with a large issue cluster C (with a larger number of articles), an issue is issued. A new vector V'can be obtained at once using the previously calculated vector V for the cluster C, which may be defined as math (2) or math (3).

V'= ((v _c x m _c ) + (V x m _C )) / (m _c + m _C ) ... (2)

Here, v _c means the vector value of the short-term cluster c, mc means the number of articles included in the short-term cluster _c , and m _C means the number of existing articles included in the issue cluster C.

V'= ((v C'x m _{C '} ) + (V x m _C )) / (m _C' + m _C ) ... (3)

Here, v C'means the vector value of the small issue cluster _{C '} , m C'means the number of articles contained in the small issue cluster C', and m _C means the number of existing articles contained in the issue cluster C.

By using such a previously calculated vector value of an issue cluster, it is possible to easily and quickly obtain a new vector value of an issue cluster in which a short-term cluster or a small issue cluster is merged.

Compared to the case where the vector average of the entire article is calculated for the cluster every time, by using the vector value calculated in advance in the previous process, the article is added or merged with other clusters. New vectors can be obtained dramatically and quickly.

The issue cluster generation processes 410 to 440 described above are merely exemplary and are not limited thereto.

Also, assuming that there are short-term clusters or issue clusters of A, B, C, D, AB, AC, BC, CD are cluster merged in the merge process 420-440 between the clusters. If the merging is performed at once when the above conditions are satisfied, A, B, C, and D are all merged as one cluster.

However, when merging clusters that satisfy the conditions for cluster merging at once, the following problems may occur.

First, as a result of merging clusters A and B, the vector distance between the vector of the merged cluster AB and the vector D may become too long to satisfy the condition of cluster merging, which is completely unsuitable for the condition of cluster merging. The vector distance between the cluster E and the merged cluster AB may become close to each other, and the condition of cluster merge may be satisfied.

Next, when the cluster merge process is carried out in parallel, clusters A and B may be merged into cluster B, and at the same time, clusters B and C may be merged into cluster B.

An example of a cluster merging method for solving these two problems is shown in FIG.

Referring to FIG. 9, the cluster generation unit 320 compares all clusters with the clusters generated after the corresponding cluster for each cluster, and only the cluster with the shortest vector distance (short-term cluster or issue cluster). Is selected as the merge target (S901). This step 901 is performed by a parallel processing method.

The cluster generation unit 320 merges the clusters selected as merge targets in step 901 one by one by a serial processing method (S902). Clusters that have already been merged may be ignored even if they are reselected as targets for merging in the next process, and may be excluded so that they will not be selected as targets for merging after merging.

As a result of executing step 902, the cluster generation unit 320 determines whether the number of clusters to be merged is 0 (S903), and if there is one or more clusters to be merged, the cluster generation unit 320 includes the merged clusters. However, the steps from step 901 are repeated again for the entire cluster.

The cluster generation unit 320 repeats the steps 901 to 902 until the number of clusters to be merged becomes 0, and then ends the cluster merger when the number of clusters to be merged becomes 0 (S904).

In the present embodiment, cluster merging can be executed quickly and stably by parallel processing a portion having a large amount of calculation without affecting the results before and after the cluster merging.

The cluster merging method may utilize various features indicating similarity such as existence / nonexistence of the same article, vector Euclidean, vector cosine, etc., and uses at least one of the widely used merging methods. It may be selectively applied according to the requirements such as the number of articles, the number of clusters, the similarity or relevance of articles in the cluster, etc. in the merged result by each method.

In this embodiment, an issue cluster is generated as a medium / long-term related issue-based cluster group by merging volatile cluster data and fragmented cluster data through a service that provides articles. Can be done.

In the past, when clustering articles collected over a long period of time, it was only necessary to bundle articles with similar texts around the text and eventually generate a collection of similar documents, but in the present invention, By merging clusters bundled based on time based on the similarity between clusters, it is possible to generate cluster groups for each issue, and although the contents of the document change, issues that are common in terms of context can be created. It is possible to generate a collection of documents with. By merging clusters based on the similarity between clusters to generate an issue cluster, articles that were difficult to merge due to the similarity between articles can be bundled as one cluster having a common issue.

Referring to FIG. 4, at step 450, the cluster display unit 330 may display the article of the issue cluster finally merged at step 440 through the article providing service. The cluster display unit 330 may provide a timeline for articles included in the issue cluster among articles on the Internet as an article timeline using the issue cluster. In other words, the cluster display unit 330 may display the articles included in the issue cluster in chronological order by using the issue cluster.

The cluster display unit 330 may display at least one issue cluster that satisfies a predetermined display condition among the issue clusters through the service. As an example, the cluster display unit 330 provides an issue cluster in which an article specified by a content provider (for example, a news organization) or an article specified by the selection or setting of a user who uses the service exists. It may be determined as a display target. In other words, the cluster display unit 330 may display an issue timeline on the service page for the issue cluster corresponding to the main issue handled by the news media or the issue of interest to the individual user. As another example, the cluster display unit 330 may determine an issue cluster in which at least one of the number of documents, the elapsed time after clustering, and the number of comments meets a predetermined condition as a service display target. The display condition of the issue cluster is, for example, when the first clustered article among the articles contained in the cluster has passed for 2 days or more, or when the total number of articles contained in the cluster is 200 or more, the number of comments is It may include the case where 100 or more articles are 3 or more per day and the date of the corresponding condition is 2 days or more. In addition to the above-mentioned issue cluster display conditions, it is also possible to combine news media issues and individual issues to determine the service display target.

An example of the interface screen of the issue timeline using the above-mentioned issue cluster is as shown in FIGS. 10 to 12.

Referring to FIG. 10, the cluster display unit 330 may display an issue cluster, that is, an issue timeline screen 1000 for displaying articles having high relevance in the medium / long term in chronological order through a news service. On the issue timeline screen 1000, the time domain 1010 showing the number of articles in graph form for each unit time (for example, 1 day) included in the issue cluster, and the article list included in the issue cluster are shown separately for each unit time. Article area 1020 may be included.

The issue timeline screen 1000 can grasp articles that are highly related in the medium / long term at a glance, and has a navigation function for article confirmation due to the structure in which the time domain 1010 and the article domain 1020 are organically connected. May be provided.

A part of the issue timeline screen 1000, for example, the upper end may include the period information 1001 in which the issue cluster is generated, the issue title 1002 associated with the issue cluster, and the like. The issue title 1002 is generated by utilizing the title or tag of at least one article included in the issue cluster. For example, the title of the article having the largest number of comments is displayed as the issue title 1002. Alternatively, the issue title 1002 may be generated and displayed by a combination of keywords that mainly appear in the title or tag of the article.

The time domain 1010 includes the time information and the number of articles of each unit time included in the issue cluster. For example, one axis shows the time information and the other axis shows the number of articles and the length of the bar. The form of the bar graph shown by may be displayed. At this time, the display elements (for example, color, brightness, etc.) of the graph bar may be classified and displayed according to the number of articles. For example, the larger the number of articles, the darker the color of the graph bar, and the smaller the number of articles, the lighter the color of the graph bar.

In the article area 1020, the article list by unit time merged as one issue cluster may be arranged by a certain criterion such as date order, article number order, for example, the recent cluster is displayed at the top. Alternatively, the cluster containing the most articles may be displayed at the top.

Referring to FIG. 11, in the issue timeline screen 1000, the time domain 1010 can be scrolled in one direction (for example, left-right direction), and the article area 1020 is in the same direction as the time domain 1010 or in another direction (for example, for example). The interface may be configured to allow scrolling 1102 (up and down).

By displaying the issue cluster through the service, the user can check the number of articles by unit time within the entire clustered period after the corresponding issue appears by scrolling 1101 to the time domain 1010 of the issue cluster. It is possible to check at a glance the change in the issue over time, such as when the issue appears and when it becomes the most issue.

Further, by scrolling 1102 to the article area 1020, the article list by unit time included in the issue cluster can be shown in a predetermined arrangement order, and the user can confirm the articles clustered by unit time. can. The article area 1020 shows only a certain number of articles (for example, 3 articles) for each unit time, and a separate request from the user to the article list on a specific date (for example, more, whole display, etc.). If is entered, the entire article may be shown.

When the scroll 1102 is scrolled to the article area 1020, the time domain 1010 may be automatically scrolled according to the screen display of the article list. As an example, scroll 1102 for article area 1020 automatically scrolls the unit time graph bar of the article list displayed in a predetermined reference range (eg, centerline) of the screen in time domain 1010 to the center. It may be displayed so as to be distinguished from other unit time graph bars.

Referring to FIG. 12, the time domain 1010 may be simplified as compared with the initial state (FIG. 10) in the process of confirming the article list by unit time by the scroll 1102 for the article area 1020. For example, if the scroll 1102 with respect to the article area 1020 continues for a certain period of time (for example, 1 second) or more, the size of the time domain 1010 may be reduced or the graph bar of the time domain 1010 may be displayed in a reduced form. When the article list aligned at the top edge by the scroll 1102 of the article area 1020 is displayed again on the screen, the time area 1010 may be restored to the initial state (FIG. 10).

Further, whether or not the time domain 1010 can be displayed, that is, the display state or the hidden state may be selectively applied depending on the direction of the scroll 1102 with respect to the article area 1020. For example, when the article area 1020 is scrolled downward, the time domain 1010 is hidden, while when the article area 1020 is scrolled upward, the time domain 1010 may be displayed again.

Similarly, at the time of scrolling 1101 with respect to the time domain 1010, the article area 1020 may be automatically scrolled according to the screen display of the unit time graph bar. In other words, the time domain 1010 and the article domain 1020 may be interconnected, and the other areas may be automatically scrolled according to the scrolling of one area.

As another example, the time domain 1010 is automatically scrolled when the scroll 1102 is scrolled to the article area 1020, while the article area 1020 is in the existing position when the scroll 1101 is scrolled to the time domain 1010. Of course, it is possible to maintain a fixed state and vice versa.

If the interface is configured to keep the article area 1020 in a fixed state without being automatically scrolled when the scroll 1101 is made to the time area 1010, then a graph of a particular date in the time area 1010, eg, 7 If the graph bar of the 26th of the month is selected, the article area 1020 may be automatically scrolled and displayed in the article list dated the 26th of July. In the time domain 1010, the graph bar for the selected date may be displayed so as to be distinct from other unit time graph bars. When the graph bar of a specific date is selected in the initial state of the time domain 1010 (FIG. 10), the article list of the selected date is displayed in the article area 1020, and at the same time, the time domain 1010 is displayed in a simplified manner. May be done.

Thus, according to the embodiment of the present invention, by merging short-term clusters generated by time zone based on the similarity between clusters, issue clusters are formed as cluster groups of issue units that are related in the medium to long term. Can be generated. By merging clusters based on the similarity between clusters to create an issue cluster, articles with related issues will be effective even if the subject or content changes over time and the similarity between articles decreases. Can be clustered. By performing cluster merging by using the vector value of the previously calculated cluster to calculate the vector value of the cluster to which the article was added or the cluster merged with other clusters, the amount of calculation is dramatically increased. It can be reduced to provide fast and stable clustering performance.

Further, according to the embodiment of the present invention, by using the issue cluster, it is possible to provide an article timeline capable of showing articles with high relevance in the medium / long term in chronological order. By displaying the display area for each unit time and the articles clustered for each unit time by the issue cluster, it is possible to grasp the articles that are highly related for a long period of time at a glance, and the time area and the article area are organically separated. By providing a navigation function for checking articles in a connected structure, it is possible to improve user convenience.

The above-mentioned device may be realized by a hardware component, a software component, and / or a combination of the hardware component and the software component. For example, the apparatus and components described in the embodiments include a processor, a controller, an ALU (arithmetic logic unit), a digital signal processor, a microcomputer, an FPGA (field programgable gate array), a PLU (programmable log unit), a microprocessor, and the like. Alternatively, it may be implemented using one or more general purpose computers or special purpose computers, such as various devices capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the OS. The processing device may also respond to the execution of the software, access the data, and record, manipulate, process, and generate the data. For convenience of understanding, one processing device may be described as being used, but one of ordinary skill in the art may include a plurality of processing elements and / or a plurality of types of processing elements. You can understand. For example, the processing device may include multiple processors or one processor and one controller. Also, other processing configurations such as parallel processors are possible.

The software may include computer programs, codes, instructions, or a combination of one or more of these, configuring the processing equipment to operate at will, or instructing the processing equipment independently or collectively. You may do it. The software and / or data is embodied in any type of machine, component, physical device, computer recording medium or device to be interpreted based on the processing device or to provide instructions or data to the processing device. good. The software is distributed on a computer system connected by a network and may be recorded or executed in a distributed state. The software and data may be recorded on one or more computer-readable recording media.

The method according to the embodiment may be realized in the form of program instructions that can be executed by various computer means and recorded on a computer-readable medium. At this time, the medium may be a continuous recording of a computer-executable program, or a temporary recording for execution or download. Further, the medium may be various recording means or storage means in the form of a combination of a single piece of hardware or a plurality of pieces of hardware, and is not limited to a medium directly connected to a certain computer system, but is distributed over a network. It may exist. Examples of media include hard disks, floppy disks, magnetic media such as magnetic tapes, optical media such as CD-ROMs and DVDs, optical magnetic media such as floppy disks, and ROMs, RAMs. It may be configured to include a flash memory or the like and record program instructions. Other examples of media include recording media or storage media managed by application stores that distribute applications, sites that supply or distribute various other software, servers, and the like.

As described above, the embodiments have been described based on the limited embodiments and drawings, but those skilled in the art can make various modifications and modifications from the above description. For example, the techniques described may be performed in a different order than the methods described, and / or components such as the systems, structures, devices, circuits described may be in a different form than the methods described. Appropriate results can be achieved even if they are combined or combined, and confronted or replaced by other components or equivalents.

Therefore, even if it is a different embodiment, if it is equivalent to the claims, it belongs to the attached claims.

222: Processor 310: Cluster collection unit 320: Cluster generation unit 330: Cluster display unit

Claims (16)

A method of providing a document timeline executed by a computer system.
The computer system comprises at least one processor configured to execute a computer-readable instruction contained in memory.
The method for providing the document timeline is as follows.
The stage of creating an issue cluster as a cluster group by merging the clusters based on the similarity between clusters composed of similar documents by the at least one processor, and the issue cluster by the at least one processor. For the documents included in the issue cluster, the time domain in which the number of documents included in the issue cluster by unit time is displayed in a graph format and the document list included in the issue cluster. Includes the stage of displaying a timeline that includes a document area that is displayed by unit time .
A document timeline characterized in that the time domain is simplified and displayed in a reduced form of the size of the time domain or the graph of the time domain when scrolling to the document area. Providing method. A method of providing a document timeline executed by a computer system.
The computer system comprises at least one processor configured to execute a computer-readable instruction contained in memory.
The method for providing the document timeline is as follows.
The stage of creating an issue cluster as a cluster group by merging the clusters based on the similarity between clusters composed of similar documents by the at least one processor, and
A time domain in which the number of documents included in the issue cluster by unit time is displayed in a graph form for the documents included in the issue cluster by using the issue cluster by the at least one processor. The stage of displaying the timeline including the document area in which the document list included in the issue cluster is displayed by unit time.
Including
A method for providing a document timeline, characterized in that a displayed state or a hidden state of the time area is selectively applied according to a scrolling direction with respect to the document area. The stage to be displayed is
The document timeline providing method according to claim 1 or 2 , which comprises a step of determining an issue cluster containing a document specified by a user's selection or setting or a document specified by a content provider as a display target. The stage to be displayed is
Any one of claims 1 to 3, including the step of determining an issue cluster whose display target is at least one of the number of documents, the elapsed time after clustering, and the number of comments. How to provide the document timeline described in the section . The document timeline providing method according to any one of claims 1 to 4, wherein the navigation function is provided in a structure in which the time domain and the document area are organically connected. One of claims 1 to 5, wherein the time domain is scrollable in one direction, and the document area includes an interface capable of scrolling in a direction different from that of the time domain. How to provide the document timeline described in the section . The document timeline according to any one of claims 1 to 6, wherein the time area is automatically scrolled according to the screen display of the document list according to the scrolling to the document area. Providing method. Of claims 1 to 7 , when a graph bar for a particular unit time is selected in the time domain, the document area is scrolled and displayed in the document list for the selected unit time. The method of providing the document timeline described in any one of the above. A computer program for causing the computer system to execute the method for providing a document timeline according to any one of claims 1 to 8 . A non-temporary computer-readable recording medium in which a program for causing a computer to execute the document timeline providing method according to any one of claims 1 to 8 is recorded. It ’s a computer system,
Contains at least one processor configured to execute computer-readable instructions contained in memory.
The at least one processor
A cluster generator that creates an issue cluster as a cluster group by merging the clusters based on the similarity between clusters composed of similar documents, and a document included in the issue cluster using the issue cluster. On the other hand, it includes a time domain in which the number of documents by unit time included in the issue cluster is displayed in a graph form, and a document area in which the document list included in the issue cluster is displayed by unit time. Includes a cluster display that displays the timeline
A computer system characterized in that, when scrolling to the document area, the time domain is simplified and displayed in a reduced form of the size of the time domain or the graph of the time domain . It ’s a computer system,
At least one processor configured to execute computer-readable instructions contained in memory
Including
The at least one processor
A cluster generator that creates an issue cluster as a cluster group by merging the clusters based on the similarity between clusters composed of similar documents, and a cluster generator.
For the documents included in the issue cluster using the issue cluster, the time domain in which the number of documents by unit time included in the issue cluster is displayed in a graph form and the documents included in the issue cluster are included. Cluster display unit that displays the timeline including the document area where the document list is displayed by unit time
Including
A computer system, characterized in that the displayed or hidden state of the time domain is selectively applied according to the scrolling direction with respect to the document area. The cluster display unit is
The computer system according to claim 11 or 12 , wherein an issue cluster including a document specified by a user's selection or setting or a document specified by a content provider is determined as a display target. The cluster display unit is
Any of claims 11 to 13 , characterized in that at least one of the number of documents, the elapsed time after clustering, and the number of comments determines an issue cluster that meets a predetermined condition as a display target. The computer system described in one paragraph . The computer system according to any one of claims 11 to 14, wherein the navigation function is provided in a structure in which the time domain and the document domain are organically connected. One of claims 11 to 15, wherein the time domain is scrollable in one direction, and the document area includes an interface capable of scrolling in a direction different from that of the time domain. The computer system described in the section .

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