Word cloud generation processing method and device and medium

Abstract

The invention relates to the technical field of electric digital data processing, in particular to a word cloud generation processing method and device and a medium. The method comprises the steps of obtaining a value range of each data type tag corresponding to a second user group; dividing the value range of each data type label into a plurality of equal-length subintervals; adjusting the equal-length subinterval corresponding to each data type tag for a first preset number of times, and obtaining an optimal value range of each attribute value corresponding to each data type tag according to a relative index of each attribute value of each data type tag corresponding to the first user group after each adjustment, determining an attribute value of each data type tag corresponding to each user in the first user group and the second user group; and determining a target word set displayed on the user interface according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group. According to the invention, the number of the obtained features of the specific target user group can be increased.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a processing method, device and medium for generating a word cloud. Background Art

[0002] The existing database stores the attribute values ​​of labels of different dimensions of a large number of users. The attribute values ​​of user labels can reflect the basic information and preferences of users. By comparing the differences in the attribute values ​​of labels of a specific target user group and all users stored in the database, the characteristics of the specific target user group can be obtained, and then matching information can be pushed to the target user group based on the characteristics of the specific target user group.

[0003] There are usually two types of user labels: one is a data type label, and the other is a non-data type label. A data type label refers to a label whose corresponding different attribute values ​​correspond to a value range. For example, a data type label is a consumption level label, and its corresponding three attribute values ​​are low consumption level, medium consumption level, and high consumption level. The corresponding value range of low consumption level is less than 300, which means that when the single consumption amount is less than 300, it is judged as a low consumption level; the corresponding value range of medium consumption level is 300-700, which means that when the single consumption amount is between 300-700, it is judged as a medium consumption level; the corresponding value range of high consumption level is greater than 700, which means that when the single consumption amount is greater than 700, it is judged as a high consumption level. Non-data type labels refer to labels whose corresponding different attribute values ​​do not correspond to a value range. For example, a non-data type label is a gender label, and its corresponding two attribute values ​​are male and female.

[0004] The attribute value of the user's data type label is related to the value range corresponding to each attribute value. If the value range corresponding to each attribute value of the data type label is not set well, the difference in the attribute value of the data type label of the specific target user group compared with all users is not obvious, and it will be difficult to obtain the characteristics of the specific target user group. How to increase the number of characteristics of the specific target user group obtained to display more information about the characteristics of the specific target user group is an urgent problem to be solved. Summary of the invention

[0005] The present invention aims to provide a processing method, device and medium for generating a word cloud, so as to increase the number of features of a specific target user group obtained and display more information on the features of the specific target user group.

[0006] According to a first aspect of the present invention, a method for generating a word cloud is provided, the method comprising the following steps:

[0007] The value range of each data type label corresponding to the second user group is obtained; any data type label belongs to a preset label set, and the preset label set includes a plurality of data type labels and a plurality of non-data type labels.

[0008] The value range of each data type label is divided into a number of equal-length sub-intervals; wherein the number of sub-intervals corresponding to any data type label is the number of attribute values ​​corresponding to the data type label.

[0009] The equal-length subintervals corresponding to each data type label are adjusted a first preset number of times, and the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment is obtained; any user in the first user group belongs to the second user group, and the number of users included in the first user group is less than the number of users included in the second user group; the relative index of any attribute value of any data type label corresponding to the first user group is the ratio of the proportion of users corresponding to the attribute value of the data type label in the first user group to the proportion of users corresponding to the attribute value of the data type label in the second user group.

[0010] The preferred value range of each attribute value corresponding to each data type label is obtained according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment, and the attribute value of each data type label corresponding to each user in the first user group and the second user group is determined according to the preferred value range of each attribute value corresponding to each data type label.

[0011] A target word set displayed on the user interface is determined according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group; the target word set includes a plurality of target words, any target word is an attribute value of a tag, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, and the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group.

[0012] According to a second aspect of the present invention, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned processing method for generating a word cloud when executing the computer program.

[0013] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processing method for generating a word cloud is implemented.

[0014] Compared with the prior art, the present invention has at least the following beneficial effects:

[0015] The present invention obtains the value range of each data type label corresponding to the second user group (i.e., the group including all users in the database). For the value range of any data type label, it is first divided into a number of equal-length sub-intervals, and then the equal-length sub-intervals are adjusted a first preset number of times, and the relative index of each attribute value of the data type label of the first user group (i.e., the specific target user group) corresponding to each adjustment is obtained. The relative index can reflect the difference in attribute values ​​of the data type label between the first user group and the second user group; by adjusting the equal-length sub-intervals a first preset number of times, the present invention obtains the preferred value range corresponding to each attribute of the data type label. Using the preferred value range as the basis for judging the attribute value of the data type label of each user can highlight the difference in attribute values ​​of the data type label between the first user group and the second user group, which is beneficial to increase the number of features of the first user group obtained, and further beneficial to displaying more information on the features of the first user group on the user interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flowchart of a method for generating a word cloud provided in Embodiment 1 of the present invention;

[0018] Figure 2 A flowchart of the steps of obtaining a preferred value range for each attribute value corresponding to each data type tag provided in the first embodiment of the present invention;

[0019] Figure 3 A flowchart of the steps of determining a target word set displayed on a user interface provided in the first embodiment of the present invention;

[0020] Figure 4 A flowchart of the steps of determining an initial word set provided in the first embodiment of the present invention;

[0021] Figure 5 A flowchart of the steps of screening the initial word set provided in the first embodiment of the present invention;

[0022] Figure 6 A flowchart of steps performed when the number of target words included in the intermediate word set is greater than a preset target display number provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] Embodiment 1:

[0025] According to this embodiment, Figure 1 As shown, a processing method for generating a word cloud is provided, and the method comprises the following steps:

[0026] S100, obtaining a value range of each data type label corresponding to the second user group; any data type label belongs to a preset label set, and the preset label set includes a plurality of data type labels and a plurality of non-data type labels.

[0027] In this embodiment, the preset tag set is a pre-constructed tag set, and any tag in the preset tag set is a data type tag or a non-data type tag. The data type label refers to a label whose corresponding different attribute values ​​correspond to a value range, such as a consumption level label; the non-data type label refers to a label whose corresponding different attribute values ​​do not correspond to a value range, such as a gender label.

[0028] In this embodiment, the second user group is a group composed of users stored in a pre-constructed database, which is a larger group. The value range of each data type label of each user in the second user group is known; for example, the values ​​corresponding to the consumption levels of all users in the second user group are known, so the minimum value (for example, 1) and the maximum value (for example, 1000) corresponding to the consumption levels of all users in the second user group are also known, and thus, the value range of the consumption level labels of all users in the second user group (for example, [1,1000]) is also determined.

[0029] S200, dividing the value range of each data type label into a number of sub-intervals of equal length; wherein the number of sub-intervals corresponding to any data type label is the number of attribute values ​​corresponding to the data type label.

[0030] In this embodiment, the number of attribute values ​​corresponding to each data type label is an empirical value; for example, the number of attribute values ​​corresponding to the consumption level label is 3, so the value range corresponding to the consumption level label is divided into 3 equal-length sub-intervals. If the value range corresponding to the consumption level label is [1,1000], then the 3 equal-length sub-intervals obtained are: [1,334), [334,667) and [667,1000].

[0031] S300, adjust the equal-length subintervals corresponding to each data type label a first preset number of times, and obtain the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment; any user in the first user group belongs to the second user group, and the number of users included in the first user group is less than the number of users included in the second user group; the relative index of any attribute value of any data type label corresponding to the first user group is the ratio of the proportion of users corresponding to the attribute value of the data type label in the first user group to the proportion of users corresponding to the attribute value of the data type label in the second user group.

[0032] In this embodiment, the first preset number of times is an empirical value, and the amplitude of adjusting the equal-length subinterval corresponding to each data type label each time is also an empirical value. The amplitudes of adjusting the equal-length subintervals corresponding to different data type labels can be the same or different. For any adjustment, the relative index of each attribute value of each data type label corresponding to the first user group after the adjustment is obtained; the process of obtaining the relative index of any attribute value of any data type label corresponding to the first user group after the adjustment includes: obtaining the ratio of the number of users corresponding to the attribute value of the data type label in the first user group after the adjustment to the number of users included in the first user group (that is, the proportion of users corresponding to the attribute value of the data type label in the first user group), obtaining the ratio of the number of users corresponding to the attribute value of the data type label in the second user group after the adjustment to the number of users included in the second user group (that is, the proportion of users corresponding to the attribute value of the data type label in the second user group), and determining the ratio of the two as the relative index of the attribute value of the data type label corresponding to the first user group after the adjustment.

[0033] As an optional specific implementation method, the value range corresponding to the consumption level label is divided into three equal-length sub-intervals [1,334), [334,667) and [667,1000]. These three equal-length sub-intervals are adjusted four times. The three sub-intervals obtained after the first adjustment are: [1,335), [335,665) and [665,1000], so that the division points of the adjusted sub-intervals are the closest multiples of 5; the three sub-intervals obtained after the second adjustment are: [1,330), [ The three sub-intervals obtained after the third adjustment are [1,350), [350,650) and [650,1000], so that the division points of the adjusted sub-intervals are the nearest multiples of 50; the three sub-intervals obtained after the fourth adjustment are [1,300), [300,700) and [700,1000], so that the division points of the adjusted sub-intervals are the nearest multiples of 100.

[0034] S400, obtaining the preferred value range of each attribute value corresponding to each data type label according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment, and determining the attribute value of each data type label corresponding to each user in the first user group and the second user group according to the preferred value range of each attribute value corresponding to each data type label.

[0035] As a preferred embodiment, Figure 2 As shown, obtaining the preferred value range of each attribute value corresponding to each data type label according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment includes:

[0036] S410, obtaining a relative index set of each data type label corresponding to the first user group after each adjustment according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment; the relative index set of any data type label includes the relative index of each attribute value of the data type label.

[0037] S420, obtaining the number of target relative indexes included in the relative index set of each data type label corresponding to the first user group after each adjustment; the target relative index is a relative index that does not belong to a preset relative index range, the minimum value of the preset relative index range is less than 1 and the maximum value of the preset relative index range is greater than 1.

[0038] In this embodiment, the minimum value and the maximum value of the preset relative index range are both empirical values; preferably, the minimum value of the preset relative index range is 0.8, and the maximum value of the preset relative index range is 1.2.

[0039] S430, determining the adjustment corresponding to the relative index set including the largest number of target relative indexes corresponding to each data type label as the optimal adjustment corresponding to each data type label.

[0040] As a specific implementation, if there are more than two relative index sets including the largest target relative index, the adjustment corresponding to any relative index set including the largest target relative index may be determined as the optimal adjustment corresponding to each data type label.

[0041] S440, determining a preferred value range for each attribute value corresponding to each data type label according to a value range for each sub-interval corresponding to the optimal adjustment corresponding to each data type label.

[0042] As a specific implementation method, the relative index set corresponding to the third adjustment of the three equal-length sub-intervals corresponding to the consumption level label includes the largest number of target relative indexes, then the sub-intervals [1,350), [350,650) and [650,1000] corresponding to the third adjustment are respectively determined as the preferred value ranges corresponding to the first attribute value (i.e., low consumption level), the second attribute value (medium consumption level) and the third attribute value (high consumption level) of the consumption level label.

[0043] Based on S410-S440, the preferred value range of each attribute value corresponding to each data type label can be obtained. Using the preferred value range as the basis for judging the attribute value of the data type label of each user can highlight the difference in the attribute value of the data type label between the first user group and the second user group, which is conducive to increasing the number of features (i.e., target words) of the first user group that are subsequently obtained.

[0044] S500, determining a target word set displayed on the user interface according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group; the target word set includes a plurality of target words, any target word is an attribute value of a tag, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, and the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group.

[0045] In this embodiment, the target word set is a word cloud; when each target word included in the target word set is displayed on the user interface, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, that is, the larger the relative index of a target word corresponding to the first user group is, the darker the display color of the target word is; the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group, that is, the larger the number of users corresponding to a target word corresponding to the first user group is, the larger the display area of ​​the target word on the user interface is.

[0046] In this embodiment, based on S400, the attribute value of each data type label corresponding to each user in the first user group and the second user group can be obtained. On this basis, the relative index of each attribute value of each data type label corresponding to the first user group in S500 can be further obtained.

[0047] In this embodiment, the attribute value of each non-data type tag corresponding to each user in the first user group and the second user group is also known, so the relative index of each attribute value of each non-data type tag corresponding to the first user group can be obtained. The process of obtaining the relative index of each attribute value of each non-data type tag corresponding to the first user group is similar to the process of obtaining the relative index of each attribute value of each data type tag corresponding to the first user group, and will not be repeated here.

[0048] As a preferred embodiment, Figure 3 As shown, determining the target word set displayed on the user interface according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group includes:

[0049] S510, determining an initial word set according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group and the preset relative index range; the initial word set includes a plurality of initial words, any initial word is an attribute value of a tag, the relative index of any initial word corresponding to the first user group does not belong to the preset relative index range, the minimum value of the preset relative index range is less than 1 and the maximum value of the preset relative index range is greater than 1.

[0050] As a specific implementation, Figure 4 As shown, determining the initial word set according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group and the preset relative index range includes:

[0051] S511, determine whether the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group belongs to the preset relative index range. If not, add the attribute value of the tag corresponding to the relative index to the first preset set, and the first preset set is initialized to an empty set; otherwise, do not add the attribute value of the tag corresponding to the relative index to the first preset set.

[0052] S512: After the determination is completed, the first preset set is determined as the initial word set.

[0053] Based on S511 - S512 , the attribute values ​​of all tags that meet the condition that the relative index does not belong to the preset relative index range can be obtained.

[0054] S520, filtering the initial word set according to the number of users corresponding to each initial word in the first user group and a preset user number threshold to obtain an intermediate word set; the intermediate word set includes a plurality of intermediate words, and the number of users corresponding to any intermediate word in the first user group is greater than or equal to the preset user number threshold.

[0055] As a specific implementation, Figure 5 As shown, screening the initial word set according to the number of users corresponding to each initial word in the first user group and a preset user number threshold includes:

[0056] S521, determine whether the number of users corresponding to each initial word in the first user group is greater than or equal to a preset user number threshold. If so, add the initial word to a second preset set, which is initialized to an empty set; otherwise, do not add the initial word to the second preset set.

[0057] In this embodiment, the preset user quantity threshold is an empirical value.

[0058] S522: After the determination is completed, the second preset set is determined as the intermediate word set.

[0059] Based on S521-S522, all initial words that meet the condition that the corresponding number of users is greater than or equal to a preset user number threshold can be obtained, and these initial words constitute an intermediate word set.

[0060] S530: If the number of intermediate words included in the intermediate word set is less than or equal to a preset target display number, the intermediate word set is determined as a target word set.

[0061] In this embodiment, the preset target display quantity is an empirical value, which corresponds to the maximum number of words that can be displayed on the user interface.

[0062] As a preferred embodiment, Figure 6As shown, if the number of target words included in the intermediate word set is greater than the preset target display number, the process proceeds to S540.

[0063] S540, updating the preset relative index range to obtain an updated relative index range; the minimum value of the updated relative index range is smaller than the minimum value of the preset relative index range, and the maximum value of the updated relative index range is larger than the maximum value of the preset relative index range.

[0064] As a specific implementation, the preset relative index range is [0.8, 1.2], and the updated relative index range is [0.75, 1.25].

[0065] S550, obtain the number of intermediate words included in the updated intermediate word set based on the updated relative index range, if the number of intermediate words included in the updated intermediate word set is less than or equal to the preset target display number, then determine the updated intermediate word set as the target word set; otherwise, continue to update the updated relative index range until the number of intermediate words included in the updated intermediate word set is less than or equal to the preset target display number.

[0066] Based on S540-S550, when the number of target words included in the intermediate word set is greater than the preset target display number, further screening of the target words displayed on the user interface can be achieved, and the characteristics of the first user group after further screening are more prominent.

[0067] This embodiment obtains the value range of each data type label corresponding to the second user group (i.e., the group including all users in the database). For the value range of any data type label, it is first divided into a number of equal-length sub-intervals, and then the equal-length sub-intervals are adjusted a first preset number of times, and the relative index of each attribute value of the data type label of the first user group (i.e., the specific target user group) corresponding to each adjustment is obtained. The relative index can reflect the difference in attribute values ​​of the data type label between the first user group and the second user group; by adjusting the equal-length sub-intervals a first preset number of times, this embodiment obtains the preferred value range corresponding to each attribute of the data type label. Using the preferred value range as the basis for judging the attribute value of the data type label of each user can highlight the difference in attribute values ​​of the data type label between the first user group and the second user group, which is beneficial to increase the number of features of the first user group obtained, and further beneficial to displaying more information on the features of the first user group on the user interface.

[0068] As a preferred specific implementation manner, after S500, the method further includes:

[0069] S10, obtain the user quantity list Q of the target word set; Q=(q1,q2,…,qi ,…,q n ), q i is the number of users corresponding to the i-th target word in the first user group, where the value range of i is from 1 to n, and n is the number of target words included in the target word set.

[0070] S20. Obtain the initial display area list E of the target word set according to Q; E = (e1, e2, …, e i , …, e n ), e i is the initial display area of the i-th target word on the user interface; e i = c0 × q i / (∑ n i＝1 q i ), c0 is the area of the region on the user interface for displaying the word cloud, c0 > n × c’, e i ≥ c’, c’ is the preset minimum display area of a single target word.

[0071] In this embodiment, c0 is a preset value.

[0072] S30. Obtain the number of users q0 corresponding to the specified word in the first user group; the specified word belongs to the target word set.

[0073] In this embodiment, the specified word is the word pre-entered by the user.

[0074] S40. Obtain the target display area e’ of the i-th target word i ; when q i ≥ q0, e’ i = k1 × e i ; when q i < q0, e’ i = (c0 - ∑ b j＝1 f j ) × (q i / ∑ M m＝1 h m ); f j is the target display area of the j-th target word in the target word set that satisfies the condition that the number of corresponding users in the first user group is greater than or equal to q0, where the value range of j is from 1 to b, and b is the number of target words in the target word set that satisfy the condition that the number of corresponding users in the first user group is greater than or equal to q0; h mis the number of users corresponding to the mth target word in the target word set in the first user group that satisfies the condition that the number of users corresponding to the first user group is less than q0, the value range of m is 1 to M, M is the number of target words in the target word set that satisfies the condition that the number of users corresponding to the first user group is less than q0; k1 is the preset amplification coefficient, k1>1, c0-∑ b j＝1 f j ≥M×c',e' i ≥c'.

[0075] Based on S10-S40, the designated word can be highlighted on the user interface, and the relative size relationship of each target word in the target word set is maintained unchanged, which is conducive to the user to quickly locate the designated word and the target word with a larger number of corresponding users in the first user group.

[0076] Embodiment 2:

[0077] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0078] The value range of each data type label corresponding to the second user group is obtained; any data type label belongs to a preset label set, and the preset label set includes a plurality of data type labels and a plurality of non-data type labels.

[0079] The value range of each data type label is divided into a number of equal-length sub-intervals; wherein the number of sub-intervals corresponding to any data type label is the number of attribute values ​​corresponding to the data type label.

[0080] The equal-length subintervals corresponding to each data type label are adjusted a first preset number of times, and the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment is obtained; any user in the first user group belongs to the second user group, and the number of users included in the first user group is less than the number of users included in the second user group; the relative index of any attribute value of any data type label corresponding to the first user group is the ratio of the proportion of users corresponding to the attribute value of the data type label in the first user group to the proportion of users corresponding to the attribute value of the data type label in the second user group.

[0081] The preferred value range of each attribute value corresponding to each data type label is obtained according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment, and the attribute value of each data type label corresponding to each user in the first user group and the second user group is determined according to the preferred value range of each attribute value corresponding to each data type label.

[0082] A target word set displayed on the user interface is determined according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group; the target word set includes a plurality of target words, any target word is an attribute value of a tag, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, and the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group.

[0083] Embodiment three:

[0084] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0085] The value range of each data type label corresponding to the second user group is obtained; any data type label belongs to a preset label set, and the preset label set includes a plurality of data type labels and a plurality of non-data type labels.

[0086] The value range of each data type label is divided into a number of equal-length sub-intervals; wherein the number of sub-intervals corresponding to any data type label is the number of attribute values ​​corresponding to the data type label.

[0087] The equal-length subintervals corresponding to each data type label are adjusted a first preset number of times, and the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment is obtained; any user in the first user group belongs to the second user group, and the number of users included in the first user group is less than the number of users included in the second user group; the relative index of any attribute value of any data type label corresponding to the first user group is the ratio of the proportion of users corresponding to the attribute value of the data type label in the first user group to the proportion of users corresponding to the attribute value of the data type label in the second user group.

[0088] The preferred value range of each attribute value corresponding to each data type label is obtained according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment, and the attribute value of each data type label corresponding to each user in the first user group and the second user group is determined according to the preferred value range of each attribute value corresponding to each data type label.

[0089] A target word set displayed on the user interface is determined according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group; the target word set includes a plurality of target words, any target word is an attribute value of a tag, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, and the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group.

[0090] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0091] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A method for generating a word cloud, characterized in that: The processing method comprises the following steps: Obtaining a value range of each data type label corresponding to the second user group; any data type label belongs to a preset label set, and the preset label set includes a plurality of data type labels and a plurality of non-data type labels; Divide the value range of each data type label into several sub-intervals of equal length; wherein the number of sub-intervals corresponding to any data type label is the number of attribute values ​​corresponding to the data type label; The equal-length subintervals corresponding to each data type label are adjusted a first preset number of times, and the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment is obtained; any user in the first user group belongs to the second user group, and the number of users included in the first user group is less than the number of users included in the second user group; the relative index of any attribute value of any data type label corresponding to the first user group is the ratio of the proportion of users corresponding to the attribute value of the data type label in the first user group to the proportion of users corresponding to the attribute value of the data type label in the second user group; Obtaining a preferred value range for each attribute value corresponding to each data type label according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment, and determining the attribute value of each data type label corresponding to each user in the first user group and the second user group according to the preferred value range for each attribute value corresponding to each data type label; A target word set displayed on the user interface is determined according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group; the target word set includes a plurality of target words, any target word is an attribute value of a tag, the display color depth of any target word is positively correlated with the relative index of the target word corresponding to the first user group, and the display size of any target word is positively correlated with the number of users corresponding to the target word in the first user group.

2. The method for generating a word cloud according to claim 1, characterized in that: Obtaining the preferred value range of each attribute value corresponding to each data type label according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment includes: Obtaining a relative index set of each data type label corresponding to the first user group after each adjustment according to the relative index of each attribute value of each data type label corresponding to the first user group after each adjustment; the relative index set of any data type label includes the relative index of each attribute value of the data type label; Obtaining the number of target relative indexes included in the relative index set of each data type label corresponding to the first user group after each adjustment; the target relative index is a relative index that does not belong to a preset relative index range, the minimum value of the preset relative index range is less than 1 and the maximum value of the preset relative index range is greater than 1; Determine the adjustment corresponding to the relative index set including the largest number of target relative indexes corresponding to each data type label as the optimal adjustment corresponding to each data type label; The preferred value range of each attribute value corresponding to each data type label is determined according to the value range of each sub-interval corresponding to the optimal adjustment corresponding to each data type label.

3. The method for generating a word cloud according to claim 1, characterized in that: Determining the target word set displayed on the user interface according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group includes: An initial word set is determined according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group and a preset relative index range; the initial word set includes a plurality of initial words, any initial word is an attribute value of a tag, the relative index of any initial word corresponding to the first user group does not belong to the preset relative index range, the minimum value of the preset relative index range is less than 1 and the maximum value of the preset relative index range is greater than 1; The initial word set is screened according to the number of users corresponding to each initial word in the first user group and a preset user number threshold to obtain an intermediate word set; the intermediate word set includes a plurality of intermediate words, and the number of users corresponding to any intermediate word in the first user group is greater than or equal to the preset user number threshold; If the number of intermediate words included in the intermediate word set is less than or equal to the preset target display number, the intermediate word set is determined as the target word set.

4. The method for generating a word cloud according to claim 3, characterized in that: The processing method further comprises the following steps: if the number of target words included in the intermediate word set is greater than the preset target display number, the preset relative index range is updated to obtain an updated relative index range; the minimum value of the updated relative index range is less than the preset minimum value of the relative index range, and the maximum value of the updated relative index range is greater than the preset maximum value of the relative index range; The number of intermediate words included in the updated intermediate word set is obtained according to the updated relative index range. If the number of intermediate words included in the updated intermediate word set is less than or equal to the preset target display number, the updated intermediate word set is determined as the target word set; otherwise, the updated relative index range is continued to be updated until the number of intermediate words included in the updated intermediate word set is less than or equal to the preset target display number.

5. The method for generating a word cloud according to claim 3, characterized in that: Determining the initial word set according to the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group and the preset relative index range includes: Determine whether the relative index of each attribute value of each tag in the preset tag set corresponding to the first user group belongs to the preset relative index range, if not, add the attribute value of the tag corresponding to the relative index to the first preset set, the first preset set is initialized to an empty set; otherwise, do not add the attribute value of the tag corresponding to the relative index to the first preset set; After the determination is completed, the first preset set is determined as the initial word set.

6. The method for generating a word cloud according to claim 3, characterized in that: Screening the initial word set according to the number of users corresponding to each initial word in the first user group and a preset user number threshold includes: Determine whether the number of users corresponding to each initial word in the first user group is greater than or equal to a preset user number threshold, if so, add the initial word to a second preset set, the second preset set being initialized to an empty set; otherwise, do not add the initial word to the second preset set; After the determination is completed, the second preset set is determined as the intermediate word set.

7. The method for generating a word cloud according to claim 2, characterized in that: The preset minimum value of the relative index range is 0.8, and the preset maximum value of the relative index range is 1.

2.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for generating a word cloud as described in any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating a word cloud as claimed in any one of claims 1 to 7 is implemented.

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