TWI776020B - Apparatus, method, and computer program product thereof for locating user interests - Google Patents

Abstract

An apparatus, method, and computer program product thereof for locating user interests are provided. The apparatus stores a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to each of the articles, and a reading record of a user. The apparatus establishes a plurality of association rules according to the articles, wherein each of the association rules is between one of the interest categories and one of the keywords. The apparatus determines a plurality of read articles of the user according to the reading record and determines a keyword set of the user according to the read articles of the user, wherein the read articles is a subset of the articles and the keyword set is a subset of the keywords. The apparatus determines an interest distribution of the user according to the association rules corresponding to the keyword set of the user.

Description

Apparatus, method and computer program product for locking user interest

The present invention relates to a device, method and computer program product for locking user interests. Specifically, the present invention relates to a device, method and computer program product for locking user's interests based on user's reading habits.

With the advent of the digital age, the general public has become accustomed to reading articles on various electronic devices. Many content providers classify articles (eg, politics, sports), so that users can easily select articles to read according to the categories. In addition, some content providers will mark each article with keywords so that users can easily retrieve it.

Under this trend, some technologies currently provide digital services based on users' reading habits. Specifically, some technologies analyze the interests of users based on the categories of articles read by the users (eg, politics, sports), but because the categories of articles are too high-level, the results of the analysis will be too rough. Some other technologies analyze the interests of users based on the keywords of the articles that the users have read, but the information conveyed by each keyword is too specific, and the keyword groups of the articles that the users have read often cannot Focus, which makes it impossible to lock the user's interest.

In view of this, there is still an urgent need in the art for a method that can find the Information mining techniques for users' interests.

In order to solve the problems of the prior art, the present invention provides a device, method and computer program product for locking user interests.

The device for locking user interest provided by the present invention includes a storage and a processor, and the storage is electrically connected to the processor. The storage stores a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles and a reading record of one of the users. The processor uses the articles to establish a plurality of association rules, wherein each association rule is between one of the interest categories and one of the keywords. The processor also confirms a plurality of read articles of the user according to the reading record, and determines a keyword set of the user according to the read articles of the user, wherein the read articles of the user are the articles a subset, and the keyword set of the user is a subset of the keywords. The processor also confirms an interest distribution of the user according to the association rules corresponding to the keyword set of the user.

The method for locking user interests provided by the present invention is suitable for an electronic computing device. The electronic computing device stores a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles and a reading record of a user. The method includes the following steps: (a) using the articles to establish a plurality of association rules, wherein each of the association rules is between one of the interest categories and one of the keywords, (b) confirming according to the reading record a plurality of articles read by the user, (c) determine a keyword set for the user based on the articles read by the user, wherein the articles read by the user are a subset of the articles, and the article The keyword set of the user is a subset of the keywords, and (d) according to the association rules corresponding to the keyword set of the user, an interest distribution of the user is confirmed.

The computer program product provided by the present invention includes a plurality of program instructions. After an electronic computing device loads the computer program product, the electronic computing device executes the program instructions contained in the computer program product, thereby realizing a method of locking user interests. The electronic computing device stores a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles and a reading record of a user. The method includes the following steps: (a) using the articles to establish a plurality of association rules, wherein each of the association rules is between one of the interest categories and one of the keywords, (b) confirming according to the reading record a plurality of articles read by the user, (c) determine a keyword set for the user based on the articles read by the user, wherein the articles read by the user are a subset of the articles, and the article The keyword set of the user is a subset of the keywords, and (d) according to the association rules corresponding to the keyword set of the user, an interest distribution of the user is confirmed.

The interest locking technology (at least including the device, the method and the computer program product thereof) provided by the present invention establishes a plurality of association rules between different keywords collected from a plurality of articles and a plurality of interest categories. After these association rules are established, the interest locking technology provided by the present invention can analyze a single user, multiple users, a target user group or/and all users, so as to lock the interest distribution of different users and lock the interests of different users. Key interest categories and even target key users for different interest categories. Because the interest locking technology provided by the present invention does not simply judge the distribution of the user's interest according to the classification of the article (for example: politics, sports) or simply according to the keywords of the article, but cross-comparisons the article itself with Therefore, the interest locking technology provided by the present invention can more accurately confirm the user's interest distribution, find out its key interest categories, and can lock key users according to different interest categories, thereby providing more accurate information. Serve for accurate digits.

The detailed techniques and embodiments of the present invention are described below with reference to the drawings, so that those with ordinary knowledge in the technical field to which the present invention pertains can understand the technical features of the claimed invention.

1‧‧‧Interest Locking Device

11‧‧‧Storage

13‧‧‧Processor

C1, C2, ..., Cm‧‧‧Interest category

A1, A2, ..., An‧‧‧Articles

SA‧‧‧Article Database

RR1, RR2, ..., RRs‧‧‧Reading records

K1, K2, ..., Kt‧‧‧Keywords

R1, R2,...,Rz‧‧‧association rules

U1, U2, ..., Us‧‧‧Users

SA1, SA2, ..., SAs‧‧‧Multiple read articles

SK1, SK2, ..., SKs‧‧‧Keyword Set

ID1, ID2, ..., IDs‧‧‧Interest distribution

Steps S201~S207‧‧‧

Fig. 1A is a schematic diagram of the structure of the interest locking device 1 according to the first embodiment of the present invention; Fig. 1B is a diagram showing the establishment of complex numbers between keywords K1, K2, ..., Kt and interest categories C1, C2, ..., Cm A schematic diagram of the association rules R1, R2, ..., Rz; Figure 1C depicts the message generation process of the interest locking device 1 when obtaining the interest distribution of the user U1; and Figure 2 depicts the interests of the second embodiment of the present invention The flow chart of the locking method.

The following will explain the device, method and computer program product of locking user interest provided by the present invention through implementation. However, these embodiments are not intended to limit the implementation of the present invention in any environment, application or manner as described in these embodiments. Therefore, the description of the following embodiments is only for the purpose of explaining the present invention, rather than limiting the scope of the present invention. It should be understood that, in the following embodiments and drawings, elements not directly related to the present invention have been omitted and not shown, and the size of each element and the size ratio between the elements in the drawings are only for convenience of illustration and description, and It is not intended to limit the scope of the present invention.

The first embodiment of the present invention is a device for locking a user's interests (hereinafter referred to as "interest locking device") 1 , the schematic diagram of which is depicted in FIG. 1A . The interest locking device 1 includes a storage 11 and a processor 13, and the two are electrically connected to each other. The storage 11 can be a memory, a Universal Serial Bus (USB) disk, a hard disk, a compact disk (CD), a flash disk or other devices capable of storing digital data known to those skilled in the art to which the present invention pertains A non-transitory storage medium or storage circuit. The processor 13 can be various processors, a central processing unit (CPU), a microprocessor (Microprocessor Unit; MPU), a digital signal processor (DSP), or a conventional processor in the technical field to which the present invention pertains. Other computing devices known to the knowledgeable.

The storage 11 stores a plurality of interest categories C1, C2, ..., Cm. It should be noted that the present invention does not limit the generation method and specific number of interest categories C1, C2, . For example: the interest category defined by Facebook, Inc., the interest category defined by Google LLC). In addition, the present invention does not limit the form in which the interest categories C1 , C2 , . . . , Cm are stored in the storage 11 . For example, the interest categories C1, C2, ..., Cm can be recorded in a file or a database, but not limited thereto.

The storage 11 also stores a plurality of articles A1, A2, . . . , An. Articles A1, A2, ..., An as a whole can be regarded as an article database SA. In addition, the storage 11 stores a plurality of keywords (not shown) corresponding to the chapters A1, A2, . . . , An. In different embodiments of the present invention, multiple keywords corresponding to each of the articles A1, A2, ..., An can be generated in different ways.

The storage 11 also stores a plurality of reading records RR1, RR2, ..., RRs corresponding to the plurality of users U1, U2, ..., Us, respectively. Specifically, the reading records RR1, RR2, ..., RRs each record which of the articles A1, A2, ..., An the corresponding user has read. Taking the reading record RR1 as an example, it records that the user U1 has read articles A1, A2, ..., Which articles in An.

In some embodiments, the keywords corresponding to each of the articles A1, A2, . . In some embodiments, the keywords corresponding to each of the articles A1 , A2 , . . . , An can be generated by the interest locking device 1 . For example, the processor 13 may individually perform word segmentation processing and stop words filtering on articles A1, A2, ..., An, thereby obtaining the corresponding corresponding articles A1, A2, ..., An and other keywords. For another example, the processor 13 may individually perform word segmentation processing, stop word filtering, and Tenn Frequency-Inverse Document Frequency (TF-IDF) calculation for the articles A1, A2, ..., An. method to filter, thereby obtaining the keywords corresponding to each of articles A1, A2, ..., An. Those skilled in the art to which the present invention pertains should be familiar with the operation details of word segmentation processing, stop word filtering, and word frequency-inverse document frequency algorithm, which will not be repeated here.

In this embodiment, the processor 13 uses the articles A1, A2, . Establish a plurality of association rules between them. Each of the association rules established by the processor 13 is between one of the interest categories C1, C2, ..., Cm and one of the keywords collected from the articles A1, A2, ..., An.

In some embodiments, the processor 13 establishes the associations according to a plurality of ratios of the keywords and the interest categories C1, C2, ..., Cm appearing in the articles A1, A2, ..., An at the same time rule. If the number of articles (or the ratio of the number of articles) in which a certain interest category and a certain keyword appear at the same time is higher than a threshold, the processor 13 will establish an association rule between the interest category and the keyword. In some embodiments, the processor 13 may The keyword and the multiple ratios of the interest categories C1, C2, . If the number of paragraphs (or the proportion of the number of paragraphs) in which a certain interest category and a certain keyword appear at the same time is higher than a threshold, the processor 13 will establish an association rule between the interest category and the keyword.

For ease of understanding, please refer to a specific example shown in FIG. 1B, but it is not intended to limit the scope of the present invention. In this specific example, the processor 13 assembles different keywords K1, K2, . The information possessed by An establishes a plurality of association rules R1, R2, ..., Rz between different keywords K1, K2, ..., Kt and interest categories C1, C2, ..., Cm. As shown in FIG. 1B, each straight line between keywords and interest categories represents an association rule. The association rules R1, R2, ..., Rz are each between one of the interest categories C1, C2, ..., Cm and one of the keywords K1, K2, ..., Kt.

After establishing the association rules R1, R2, ..., Rz, the processor 13 can analyze a single user, multiple users, a target user group or/and all users to lock the interest distribution of different users, or even lock different users. User's key interest categories.

It is assumed that the interest distribution of the user U1 among all users is to be obtained, and the message generation process when the interest locking device 1 operates is as shown in FIG. 1C . Specifically, the processor 13 confirms a plurality of read articles SA1 of the user U1 according to the reading record RR1 of the user U1. The read articles SA1 of the user U1 are a subset of the aforementioned articles A1, A2, ..., An (ie, the articles A1, A2, ..., An that have been read by the user U1). The processor 13 then determines a keyword set SK1 of the user U1 according to the read articles SA1 of the user U1. The keyword set SK1 of the user U1 is a subset of the keywords K1, K2, . the set formed). Then, the processor 13 according to the association rules corresponding to the keyword set SK1 of the user U1 (that is, the association rules corresponding to the keywords included in the keyword set SK1 are the association rules R1, R2, ..., a subset of Rz), confirming the interest distribution ID1 of one of the users U1.

It should be noted that the interest locking device 1 can present the interest distribution ID1 in several different ways. In some embodiments, the processor 13 may calculate the ratio of the keywords belonging to the interest categories C1, C2, . . . , Cm to the keyword set SK1 among the keywords included in the keyword set SK1 of the user U1 , and these proportions can be regarded as one of user U1's interest distribution ID1. To make the interest distribution ID1 more distributed, the processor 13 may further normalize it so that the sum of these proportions is 100%. For another example, the processor 13 can also calculate the number of keywords belonging to the interest categories C1, C2, ..., Cm among the keywords included in the keyword set SK1 of the user U1, and these numbers can be viewed as An interest distribution ID1 for one of the users U1.

If necessary, for other users U2, . In short, the processor 13 can confirm that the users U2, . A plurality of read articles SAs, wherein the read articles of each user are a subset of the aforementioned articles A1, A2, ..., An. The processor 13 determines the keyword sets SK2, . . . respectively corresponding to the users U2, . ..., SKs, wherein the keyword sets SK2, ..., SKs are each a subset of the keywords K1, K2, ..., Kt. The processor 13 then confirms the user U2, . The interest distribution ID2, . . . , IDs of the user Us respectively.

In some embodiments, the processor 13 may analyze all users (ie, users U1 , U2 , . . . , Us) to find out the distribution of interests of all users. Specifically, the processor 13 determines a keyword set for all users according to the articles read by all users. Similarly, the read articles of all users are a subset of the aforementioned articles A1, A2, ..., An (that is, the articles A1, A2, ..., An have been read by any user), and The keyword set of the entire user is a subset of keywords K1, K2, . Afterwards, the processor 13 confirms an interest distribution of the entire user according to the association rules corresponding to the keyword set of the entire user (using any of the aforementioned techniques for determining interest distribution). The interest distribution of the public can be seen from the interest distribution of all users.

In some embodiments, the processor 13 may determine at least one key interest category of a user (eg, user U1 ) by comparing the interest distribution of a certain user (eg, user U1 ) with the interest distribution of all users. Each of the at least one key interest category is one of the interest categories C1, C2, ..., Cm. Specifically, if a certain (or some) interest category occupies a higher proportion in the interest distribution of the user than in the interest distribution of all users, then that interest category (or those) are the key interest categories of the user. For example, the interest category "reading" accounts for 86.06% of the interest distribution ID1 of the user U1, and accounts for 32.9% of the interest distribution of all users, so the interest category "reading" is the key interest category of the user U1.

If necessary, for other users U2, .

In some embodiments, the processor 13 may analyze a target user group to find out the interest distribution of the target user group. The target user group is a subset of all users (ie, users U1, U2, . . . , Us). For example, the target user group may be users who have donated money and users who have participated in a certain activity, but not limited thereto.

In these embodiments, the processor 13 determines a keyword set of the target user group according to a plurality of read articles of the target user group. The read articles of the target user group are a subset of the aforementioned articles A1, A2, ..., An (that is, the articles A1, A2, ..., An are read by any user in the target user group past), and the keyword set of the target user group is a subset of keywords K1, K2, . a collection of words). Afterwards, the processor 13 confirms an interest distribution of the target user group according to the association rules corresponding to the keyword set of the target user group (using any of the aforementioned techniques for determining interest distribution).

In some embodiments, the processor 13 may also confirm at least one key interest category of the target user group by comparing the interest distribution of the target user group with the interest distribution of the entire user group, which will not be repeated here.

In some embodiments, the processor 13 may further analyze the plurality of target users included in the target user group to find out their commonalities. As mentioned above, the target user group is a subset of all users (ie, users U1, U2, . . . , Us), so each target user is one of users U1, U2, . . . , Us. The processor 13 confirms the key interest categories of the target users in the aforementioned manner, and then finds an intersection of the key interest categories corresponding to the target users as a common key interest category of the target users.

For example, the target user group includes user U1, user U2 and user Us, which The key interest categories of user U1 are "reading", "movies" and "games", the key interest categories of user U2 are "movies" and "sports", and the key interest categories of user Us are "movies", "food" and "tourism". The processor 13 can find the intersection of the key interest category of the user U1, the key interest category of the user U2 and the key interest category of the user Us as the common key interest category of the user U1, the user U2 and the user Us (ie, the interest category). "Movie").

With the aforementioned technology, when the interest locking device 1 locks a target user group according to a certain behavior or certain information (for example, users who have donated money, participated in a certain activity), it can find out the target users of the target user group. of commonality.

In some embodiments, the processor 13 may further find out at least one key user corresponding to each of the interest categories C1 , C2 , . . . , Cm. Specifically, the processor 13 first finds at least one key interest category corresponding to each of the users U1, U2, . . . , Us. Since each of the key interest categories is one of the interest categories C1, C2, ..., Cm, the processor 13 can confirm the interest categories C1, C2, ... ..., at least one key user corresponding to each of Cm. Specifically, if an interest category belongs to a certain (or some) user's key interest categories, the user(s) are the key users of the interest category. For example, if the interest category C2 is the key interest category of the users U1 , U2 and Us, then the users U1 , U2 and Us are the key users of the interest category C2 .

As can be seen from the above description, the interest locking device 1 establishes association rules R1, R2, ···, Rz between different keywords of articles A1, A2, ···, An and interest categories C1, C2, ···, Cm. After establishing the association rules R1, R2, ..., Rz, the processor 13 can analyze a single user, multiple users, a target user group or/and all users to lock the interest distribution of different users, lock different users of key interest categories, or even for different interest categories Lock out key users. Because the interest locking device 1 does not simply judge the user's interest distribution according to the classification of the article (for example: politics, sports) or simply according to the keywords of the article, but cross-comparisons the information and interests of the article itself Therefore, the interest locking device 1 can more accurately confirm the user's interest distribution, find out its key interest categories, and can lock key users according to different interest categories.

The second embodiment of the present invention is a method for locking a user's interest (hereinafter referred to as "interest locking method"), the flowchart of which is depicted in FIG. 2 . The interest locking method is suitable for an electronic computing device (for example, the interest locking device 1 described in the first embodiment), and the electronic computing device stores a plurality of interest categories, a plurality of articles, and a plurality of keys corresponding to the articles. A word and a plurality of reading records corresponding to a plurality of users respectively. Each of the reading records records which of the articles the corresponding user has read. It should be noted that the present invention does not limit the generation method and specific number of these interest categories, which can be created by an administrator, and can also be any existing clearly defined interest categories.

It should be noted that, in some embodiments, the keywords corresponding to each article can be directly given by a user (eg, article editor, article author, manager). In some embodiments, the keywords corresponding to each article can be generated by an interest targeting method. For example, the interest locking method may include at least one step (not shown), wherein the electronic computing device performs word segmentation processing and stop word filtering on each article, thereby obtaining the keywords corresponding to each article . For another example, the interest locking method may include at least one step (not shown) of performing word segmentation processing, stop word filtering, and word frequency-inverse document frequency algorithm filtering on each article by the electronic computing device, thereby Obtain the keywords corresponding to each article.

The interest locking method includes at least steps S201 to S207. in step S201, the electronic computing device uses the articles to establish a plurality of association rules, wherein each of the association rules is between one of the interest categories and one of the keywords. In some embodiments, step S201 establishes the association rules according to a plurality of ratios of the keywords and the interest categories appearing in the articles at the same time. In some embodiments, step S201 is to establish the association rules according to a plurality of ratios of the keywords and the interest categories appearing simultaneously in the same paragraph in the articles.

In step S203, the electronic computing device confirms a plurality of read articles of a user according to a reading record of the user, wherein the read articles of the user are a subset of the articles. In step S205, the electronic computing device determines a keyword set of the user according to the read articles of the user, wherein the keyword set of the user is a subset of the keywords. In step S207, the electronic computing device confirms an interest distribution of the user according to the association rules corresponding to the keyword set of the user. In some embodiments, the interest locking method may perform steps S203 to S207 for each user among all users, thereby confirming the interest distribution of each user.

In some embodiments, the interest locking method further includes a step of determining, by the electronic computing device, a keyword set of all users according to a plurality of read articles of all users. The interest locking method further includes a step of confirming, by the electronic computing device, an interest distribution of all users according to the association rules corresponding to the keyword set of all users.

In some embodiments, the interest locking method further includes a step of confirming at least one key interest category of a user by the electronic computing device by comparing the interest distribution of a user with the interest distribution of all users. Similarly, if necessary, the interest locking method can perform this step for each user among all users, thereby confirming at least one level of each user. Key interest distribution.

In some embodiments, the interest locking method further includes a step of determining, by the electronic computing device, a keyword set of the target user group according to a plurality of read articles of the target user group. The interest locking method further includes a step of confirming, by the electronic computing device, an interest distribution of the target user group according to the association rules corresponding to the keyword set of the target user group, wherein the target user group is the entire group A subset of users.

In some embodiments, the interest locking method further includes a step of confirming at least one key of the target user group by the electronic computing device by comparing the interest distribution of the target user group with the interest distribution of all users Interest categories.

In some embodiments, the interest locking method may further analyze a plurality of target users included in the target user group to find out their commonalities. The target user group is a subset of all users, so each target user is one of the aforementioned users. The interest locking method confirms the key interest categories of the target users in the aforementioned manner, and then executes a step to find, by the electronic computing device, an intersection of the key interest categories corresponding to the target users as the targets A common key interest category for one of the users.

In some embodiments, the interest locking method may further find at least one key user corresponding to each interest category. Specifically, the interest locking method first uses the aforementioned technology to find at least one corresponding key interest category for each user. Since each of the key interest categories is one of the interest categories, the interest locking method further includes a step of confirming at least one key user of each of the interest categories according to the key interest categories of the users. Specifically, if an interest category belongs to a certain (or some) user's key interest categories, the user(s) are the key users of the interest category.

Except for the above steps, the second embodiment can perform all the operations and steps of the interest locking device 1 described in the first embodiment, has the same function, and achieves the same technical effect. Those with ordinary knowledge in the technical field to which the present invention pertains can directly understand how the second embodiment performs these operations and steps based on the above-mentioned first embodiment, has the same functions, and achieves the same technical effects, so it is not repeated here.

The interest locking method described in the second embodiment can be implemented by a computer program product comprising a plurality of program instructions. The computer program product can be a file that can be transmitted over a network, or can be stored in a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium can be an electronic product, such as: a read only memory (ROM), a flash memory, a floppy disk, a hard disk, a compact disk (Compact Disk); CD), a Digital Versatile Disc (DVD), a pen drive, a network accessible database, or any other storage having the same function known to those of ordinary skill in the art to which this invention pertains media. After the program instructions included in the computer program product are loaded into an electronic computing device (eg, the interest locking device 1 ), the computer program executes the interest locking method described in the second embodiment.

It should be noted that in the patent specification of the present invention and the scope of the patent application, certain terms (including: user, subset, etc.) are prefixed with "first" or "second", such "first" and "first" "Second" and "Third" are used only to distinguish that these terms refer to different items.

To sum up, the interest locking technology (at least including the device, method and computer program product thereof) provided by the present invention establishes a plurality of association rules between different keywords collected from a plurality of articles and a plurality of interest categories. After the association rules are established, the interest locking technology provided by the present invention can target a single user, multiple users, a target user group or/and all users Users can be analyzed to lock the interest distribution of different users, lock the key interest categories of different users, and even lock key users for different interest categories. Because the interest locking technology provided by the present invention does not simply judge the distribution of the user's interest according to the classification of the article (for example: politics, sports) or simply according to the keywords of the article, but cross-comparisons the article itself with Therefore, the interest locking technology provided by the present invention can more accurately confirm the user's interest distribution, find out its key interest categories, and can lock key users according to different interest categories, thereby providing more accurate information. Serve for accurate digits.

The above-mentioned embodiments are only used to illustrate some embodiments of the present invention and illustrate the technical characteristics of the present invention, but are not intended to limit the protection scope and scope of the present invention. Any changes or equality arrangements that can be easily accomplished by those skilled in the art fall within the claimed scope of the present invention, and the scope of protection of the present invention should be subject to the scope of the patent application.

A1, A2, ..., An‧‧‧Articles

SA‧‧‧Article Database

U1, U2, ..., Us‧‧‧Users

SA1, SA2, ..., SAs‧‧‧Multiple read articles

SK1, SK2, ..., SKs‧‧‧Keyword Set

ID1, ID2, ..., IDs‧‧‧Interest distribution

Claims (15)

A device for locking user interests, comprising: a storage for storing a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles and a first reading record of a first user; and a processor, electrically connected to the storage, and using the articles to establish a plurality of association rules, each of the association rules being between one of the interest categories and one of the keywords, wherein the processor Also confirm a plurality of read articles of the first user according to the first reading record, and determine a keyword set of the first user according to the read articles of the first user, wherein the first user's The read articles are a first subset of the articles, and the keyword set of the first user is a first subset of the keywords, wherein the processor is further based on the keyword of the first user The association rules corresponding to the word set confirm an interest distribution of the first user, wherein the first user and a plurality of second users form a whole user, the processor also The read article and the plurality of read articles of each second user determine a keyword set of all users, and the processor also confirms the all users' keywords according to the association rules corresponding to the keyword set of all users an interest distribution, and the processor further confirms at least one key interest category of the first user by comparing the interest distribution of the first user with the interest distribution of all users. The device of claim 1, wherein the storage further stores a plurality of second reading records corresponding to the second users, and the processor further performs the following operations for the second users: according to the second user The second reading record of the second user confirms the read articles of the second user chapter, determine a keyword set of the second user according to the read articles of the second user, wherein the read articles of the second user are a second subset of the articles, and the second The keyword set of the user is a second subset of the keywords, and an interest distribution of the second user is confirmed according to the association rules corresponding to the keyword set of the second user. The apparatus of claim 1, wherein the processor further determines a keyword set of the target user group according to a plurality of read articles of the target user group, and the processor further determines the keyword of the target user group according to the keywords of the target user group The association rules corresponding to the set are used to confirm an interest distribution of the target user group, wherein the target user group is a subset of the total users. The apparatus of claim 3, wherein the processor further determines at least one key interest category of the target user group by comparing the interest distribution of the target user group with the interest distribution of all users. The apparatus of claim 2, wherein the processor further identifies at least one key interest category of each second user by comparing the interest distribution of each second user with the interest distribution of all users, and the The processor also determines at least one key user of each interest category according to the at least one key interest category of the first user and the at least one key interest category of each of the second users. The apparatus of claim 2, wherein the processor further determines at least one key interest category of each second user by comparing the interest distribution of each second user with the interest distribution of all users, wherein, A target user group includes a plurality of target users, each of the target users is one of the first user and the second users, and the processor also finds out the corresponding target users of the target users. The intersection of one of the key interest categories should be regarded as a common key interest category of the target users. The apparatus of claim 1, wherein the processor establishes the association rules according to a plurality of proportions of the keywords and the interest categories co-occurring in the articles. A method for locking user interests, which is applicable to an electronic computing device, the electronic computing device stores a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles, and a first reading record of a first user, The first user and a plurality of second users form a whole user group, and the method includes the following steps: (a) using the articles to establish a plurality of association rules, wherein each association rule is between one of the interest categories and the (b) confirm a plurality of read articles of the first user according to the first reading record; (c) determine a key of the first user according to the read articles of the first user A word set, wherein the read articles of the first user are a first subset of the articles, and the keyword set of the first user is a first subset of the keywords; (d) Confirm an interest distribution of the first user according to the association rules corresponding to the keyword set of the first user; (e) according to the read articles of the first user and the plural numbers of the second users (f) confirming an interest distribution of all users according to the association rules corresponding to the keyword set of all users; and (g) by comparing The interest distribution of the first user and the interest distribution of all users identify at least one key interest category of the first user. The method of claim 8, wherein the electronic computing device further stores a plurality of second reading records corresponding to each of the second users, the method further comprises the following steps: performing the following steps for each of the second users: The second reading record of the second user confirms the read articles of the second user; according to the read articles of the second user, a keyword set of the second user is determined, wherein the second user's the read articles are a second subset of the articles, and the keyword set of the second user is a second subset of the keywords; and according to the keyword set of the second user Corresponding to the association rules, an interest distribution of the second user is confirmed. The method according to claim 8, further comprising the steps of: determining a keyword set of the target user group according to a plurality of read articles of the target user group; and according to the corresponding keyword set of the target user group The association rules confirm an interest distribution of the target user group, wherein the target user group is a subset of all the users. The method of claim 10, further comprising the step of: confirming at least one key interest category of the target user group by comparing the interest distribution of the target user group with the interest distribution of all users. The method of claim 9, further comprising the steps of: confirming at least one key interest category of each second user by comparing the interest distribution of each second user with the interest distribution of all users; and according to The at least one key interest category of the first user and the at least one key interest category of each of the second users A key interest category, identifying at least one key user for each of the interest categories. The method of claim 9, further comprising the steps of: confirming at least one key interest category of each second user by comparing the interest distribution of each second user with the interest distribution of all users; and finding An intersection of the key interest categories corresponding to the target users respectively is obtained as a common key interest category of the target users. The method of claim 8, wherein the step (a) is to establish the association rules according to a plurality of proportions of the keywords and the interest categories appearing in the articles at the same time. A computer program product, after the computer program product is loaded through an electronic computing device, the electronic computing device executes a plurality of program instructions contained in the computer program product to execute a method of locking user interests, the electronic computing device stores a plurality of program instructions a plurality of interest categories, a plurality of articles, a plurality of keywords corresponding to the articles, and a reading record of a user, the first user and a plurality of second users form a whole user, and the method includes the following steps: using the The article establishes a plurality of association rules, wherein each association rule is between one of the interest categories and one of the keywords; confirms the user's multiple read articles according to the reading record; according to the user's multiple articles Read articles determine a keyword set of the user, wherein the read articles of the user are a subset of the articles, and the keyword set of the user is a subset of the keywords; according to the The association rules corresponding to the keyword set of the user confirm the distribution of interests of the user; according to the read articles of the first user and the read articles of the second users determine a keyword set of all users; confirm an interest distribution of all users according to the association rules corresponding to the keyword set of all users; and compare the interest distribution of the first user with The interest distribution of all users confirms at least one key interest category of the first user.

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