Recommendation method, device and electronic device

Abstract

Embodiments of the present invention provide a recommendation method, device and electronic device, wherein the method includes: obtaining input information; determining the association candidates corresponding to the input information, and obtaining the recommendation cost information and recommendation benefit information of the association candidates; recommending the association candidates based on the recommendation benefit information and recommendation cost information corresponding to the association candidates; and then being able to recommend association candidates by comprehensively considering the degree to which the recommended association candidates improve the user's input efficiency and the degree of interference caused to the user, thereby avoiding interference to the user caused by recommending unnecessary association candidates, thereby improving input efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of input methods, and in particular to a recommendation method, device and electronic equipment. Background Art

[0002] With the development of computer technology, electronic devices such as mobile phones and tablet computers are becoming more and more popular, bringing great convenience to people's life, study and work. These electronic devices are usually installed with input method applications (input methods for short), so that users can use the input methods to input information.

[0003] When a user uses an input method to input, the input method can make associations based on the input environment, previous context, etc., obtain association candidates and recommend them to the user; further, the required candidates can be displayed on the screen from the candidate area without the user having to enter an input sequence, thereby improving user input efficiency.

[0004] However, when the quality of the association candidates of the input method association is low, the user is likely not to click on the association candidate, or the frequency of clicking on the association candidate is low, which is not conducive to improving input efficiency. Summary of the invention

[0005] The embodiment of the present invention provides a recommendation method to improve input efficiency.

[0006] Correspondingly, the embodiment of the present invention further provides a recommendation device and an electronic device to ensure the implementation and application of the above method.

[0007] In order to solve the above problems, an embodiment of the present invention discloses a recommendation method, which specifically includes: obtaining input information; determining the association candidate corresponding to the input information, and obtaining the recommendation cost information and recommendation benefit information of the association candidate; and recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate.

[0008] Optionally, the association candidates include multiple association candidates displayed on the first screen; obtaining the recommendation cost information of the association candidates includes: obtaining the upper screen cost information and probability information respectively corresponding to the multiple association candidates displayed on the first screen; and determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates.

[0009] Optionally, obtaining the upper-screen cost information corresponding to the multiple association candidates displayed on the first screen includes: for an association candidate displayed on the first screen, determining the position of the association candidate displayed on the first screen; and obtaining the upper-screen cost information corresponding to the association candidate based on the position of the association candidate displayed on the first screen.

[0010] Optionally, determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates includes: for an association candidate displayed on the first screen, determining the product of the upper screen cost information and the probability information corresponding to the association candidate to obtain the product value corresponding to the association candidate; determining the recommendation cost information corresponding to the multiple association candidates displayed on the first screen based on the product value corresponding to each association candidate in the multiple association candidates.

[0011] Optionally, obtaining the recommendation benefit information corresponding to the association candidate includes: obtaining input cost information of an input sequence corresponding to the association candidate input by a user; and determining the recommendation benefit information corresponding to the association candidate based on the input cost information of an input sequence corresponding to the association candidate input by the user.

[0012] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: judging whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, displaying the association candidate; if the recommendation cost information is greater than the recommendation benefit information, not displaying the association candidate.

[0013] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: when it is determined that the recommendation benefit information is greater than the recommendation cost information, judging whether the difference between the recommendation benefit information and the recommendation cost information is greater than a preset threshold; if the difference between the recommendation benefit information and the recommendation cost information is greater than the preset threshold, displaying the association candidate; if the difference between the recommendation benefit information and the recommendation cost information is less than the preset threshold, not displaying the association candidate.

[0014] An embodiment of the present invention also discloses a recommendation device, which specifically includes: a first acquisition module, used to acquire input information; a second acquisition module, used to determine the association candidate corresponding to the input information, and acquire the recommendation cost information and recommendation benefit information of the association candidate; and a recommendation module, used to recommend the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate.

[0015] Optionally, the second acquisition module includes: a recommendation cost acquisition sub-module, used to obtain the upper screen cost information and probability information corresponding to the multiple association candidates displayed on the first screen; based on the upper screen cost information and probability information corresponding to the multiple association candidates, determine the recommendation cost information corresponding to the multiple association candidates for recommendation on the first screen.

[0016] Optionally, the recommendation cost acquisition submodule includes: an upper screen cost information determination unit, used to determine the position of an association candidate displayed on the first screen; and obtain the upper screen cost information corresponding to the association candidate based on the position of the association candidate displayed on the first screen.

[0017] Optionally, the recommendation cost acquisition submodule includes: a recommendation cost information acquisition unit, used to determine, for an association candidate displayed on the first screen, the product of the upper screen cost information and the probability information corresponding to the association candidate, and obtain the product value corresponding to the association candidate; based on the product value corresponding to each of the multiple association candidates, determine the recommendation cost information corresponding to the multiple association candidates displayed on the first screen.

[0018] Optionally, the second acquisition module includes: a recommendation benefit acquisition submodule, used to obtain input cost information of an input sequence corresponding to the association candidate input by the user; and determine the recommendation benefit information corresponding to the association candidate based on the input cost information of the input sequence corresponding to the association candidate input by the user.

[0019] Optionally, the recommendation module includes: a first candidate recommendation submodule, used to determine whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, the association candidate is displayed; if the recommendation cost information is greater than the recommendation benefit information, the association candidate is not displayed.

[0020] Optionally, the recommendation module includes: a second candidate recommendation sub-module, which is used to determine whether the difference between the recommended benefit information and the recommended cost information is greater than a preset threshold when the recommended benefit information is greater than the recommended cost information; if the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold, the association candidate is displayed; if the difference between the recommended benefit information and the recommended cost information is less than the preset threshold, the association candidate is not displayed.

[0021] An embodiment of the present invention further discloses a readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute a recommendation method as described in any one of the embodiments of the present invention.

[0022] An embodiment of the present invention also discloses an electronic device, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include instructions for performing the following operations: obtaining input information; determining association candidates corresponding to the input information, and obtaining recommendation cost information and recommendation benefit information of the association candidates; and recommending the association candidates based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

[0023] Optionally, the association candidates include multiple association candidates displayed on the first screen; obtaining the recommendation cost information of the association candidates includes: obtaining the upper screen cost information and probability information respectively corresponding to the multiple association candidates displayed on the first screen; and determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates.

[0024] Optionally, obtaining the upper-screen cost information corresponding to the multiple association candidates displayed on the first screen includes: for an association candidate displayed on the first screen, determining the position of the association candidate displayed on the first screen; and obtaining the upper-screen cost information corresponding to the association candidate based on the position of the association candidate displayed on the first screen.

[0025] Optionally, determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates includes: for an association candidate displayed on the first screen, determining the product of the upper screen cost information and the probability information corresponding to the association candidate to obtain the product value corresponding to the association candidate; determining the recommendation cost information corresponding to the multiple association candidates displayed on the first screen based on the product value corresponding to each association candidate in the multiple association candidates.

[0026] Optionally, obtaining the recommendation benefit information corresponding to the association candidate includes: obtaining input cost information of an input sequence corresponding to the association candidate input by a user; and determining the recommendation benefit information corresponding to the association candidate based on the input cost information of an input sequence corresponding to the association candidate input by the user.

[0027] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: judging whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, displaying the association candidate; if the recommendation cost information is greater than the recommendation benefit information, not displaying the association candidate.

[0028] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: when it is determined that the recommendation benefit information is greater than the recommendation cost information, judging whether the difference between the recommendation benefit information and the recommendation cost information is greater than a preset threshold; if the difference between the recommendation benefit information and the recommendation cost information is greater than the preset threshold, displaying the association candidate; if the difference between the recommendation benefit information and the recommendation cost information is less than the preset threshold, not displaying the association candidate.

[0029] The embodiments of the present invention include the following advantages:

[0030] In an embodiment of the present invention, input information can be obtained; then, the association candidates corresponding to the input information are determined, and the recommendation cost information and recommendation benefit information of the association candidates are obtained; then, based on the recommendation benefit information and recommendation cost information corresponding to the association candidates, the association candidates are recommended; and then, by comprehensively considering the degree to which the recommended association candidates improve the user's input efficiency and the degree of interference caused to the user, the association candidates can be recommended to avoid interference to the user caused by recommending unnecessary association candidates, thereby improving input efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a flowchart of steps of a recommended method embodiment of the present invention;

[0032] Figure 2 is a flowchart of steps of an optional embodiment of a recommended method of the present invention;

[0033] Figure 3 is a flowchart of the steps of another preferred method alternative embodiment of the present invention;

[0034] Figure 4 is a structural block diagram of a recommended device embodiment of the present invention;

[0035] Figure 5 is a structural block diagram of an optional embodiment of a recommended device of the present invention;

[0036] Figure 6 A structural block diagram of an electronic device for recommendation according to an exemplary embodiment;

[0037] Figure 7 FIG. 4 is a schematic structural diagram of an electronic device for recommendation according to another exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] One of the core concepts of the embodiment of the present invention is to recommend association candidates by comprehensively considering the degree to which the recommended association candidates improve user input efficiency and the degree of interference caused to the user, so as to avoid interference to the user caused by recommending unnecessary association candidates.

[0040] Reference Figure 1 , shows a flowchart of a recommended method embodiment of the present invention, which may specifically include the following steps:

[0041] Step 102: Obtain input information.

[0042] In an embodiment of the present invention, input information can be obtained during the process of a user using an input method to input; the input information can include all information related to the input, such as input information, input-related information such as weather information, location information, associated information of the application that calls the input method, input scene, input sequence, information in the clipboard, etc.; when the input scene is a chat scene, the input information can also include interaction information, etc., which is not limited in this embodiment of the present invention.

[0043] Step 104: determine the association candidates corresponding to the input information, and obtain the recommendation cost information and recommendation benefit information of the association candidates.

[0044] Step 106: Recommend the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate.

[0045] In the embodiment of the present invention, association can be performed based on the input information to determine the corresponding association candidate. The input method can perform association based on the input information locally, or send the input information to a server, which performs association and returns the association candidate, thereby obtaining the corresponding association candidate.

[0046] In an embodiment of the present invention, the input cost of an association candidate may refer to the cost spent by a user to obtain the association candidate by inputting an input sequence. In other words, the input cost of an association candidate is the cost of the user to obtain the association candidate by inputting an input sequence reduced by recommending the association candidate; it can be used to measure the degree to which the recommended association candidate improves the user input efficiency. Among them, for the convenience of subsequent explanation, the input cost (or the cost of the user to obtain the association candidate by inputting an input sequence reduced by recommending the association candidate) can be quantified to obtain the recommendation benefit information. The cost of the user's on-screen association candidate brought by the recommended association candidate can be used to measure the degree of interference caused to the user by the recommended association candidate; among them, the cost of the user's on-screen association candidate brought by the recommended association candidate can be quantified to obtain the recommendation cost information. Then, by comparing the recommendation benefit information and the recommendation cost information corresponding to the association candidate, it can be determined whether the association candidate needs to be recommended. If it is determined based on the comparison result that the association candidate needs to be recommended, the association candidate is displayed; if it is determined based on the comparison result that the association candidate does not need to be recommended, the association candidate may not be displayed.

[0047] In summary, in an embodiment of the present invention, input information can be obtained; then, the association candidates corresponding to the input information are determined, and the cost information and benefit information of the association candidates are obtained; then, based on the recommendation benefit information and recommendation cost information corresponding to the association candidates, the association candidates are recommended; and then, by comprehensively considering the degree to which the recommended association candidates improve the user's input efficiency and the degree of interference caused to the user, the association candidates can be recommended to avoid interference to the user caused by recommending unnecessary association candidates, thereby improving input efficiency.

[0048] The following describes how to obtain the cost information and benefit information of the association candidate, and how to recommend the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate.

[0049] Reference Figure 2 , shows a flowchart of an optional embodiment of a recommended method of the present invention, which may specifically include the following steps:

[0050] Step 202: Obtain input information.

[0051] Step 204: Determine association candidates corresponding to the input information.

[0052] In the embodiment of the present invention, when the input information includes the input information, the information after the input information can be associated based on other information in the input information to obtain the association candidate. When the input information does not include the input information, the information required to be input by the user can be directly associated based on the input information to obtain the association candidate.

[0053] Among them, the determined association candidates may include multiple ones; and while determining each association candidate, the probability information corresponding to each association candidate can also be determined. Then, based on the probability information corresponding to each association candidate, each association candidate can be sorted; and then based on the sorting result, multiple association candidates displayed on the first screen of the candidate area are determined. Among them, the top N association candidates with the highest probability information can be determined as the association candidates displayed on the first screen; the said N is a positive integer, which can be set according to the requirements, and the embodiment of the present invention does not limit this.

[0054] The candidate area may include a local candidate area and a cloud candidate area; when the association candidates include local association candidates obtained by local association and cloud association candidates obtained by server association, the local association candidates and the cloud association candidates may be deduplicated first; then the top N1 local association candidates with the highest probability information may be displayed in the local candidate area, and the top N2 cloud association candidates may be displayed in the cloud candidate area. N1 and N2 are positive integers, which may be equal to or less than N, and may be set specifically as required, and the embodiments of the present invention do not limit this.

[0055] Wherein, the acquisition of the recommendation cost information of the association candidate in step 104 may refer to steps 206 to 208:

[0056] Step 206: Obtain the upper screen cost information and probability information corresponding to the multiple association candidates displayed on the first screen.

[0057] Step 208: Determine to display the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information corresponding to the multiple association candidates.

[0058] In an embodiment of the present invention, the upper screen cost information and probability information corresponding to the multiple association candidates displayed on the first screen can be obtained first; then, calculations can be performed based on the upper screen cost information and probability information corresponding to the multiple association candidates to determine the recommendation cost information corresponding to the multiple association candidates displayed on the first screen.

[0059] The step of obtaining the upper screen cost information corresponding to the plurality of association candidates displayed on the first screen may include the following sub-steps 22 to 24:

[0060] Sub-step 22: for an association candidate displayed on the first screen, determining a position of the association candidate displayed on the first screen;

[0061] Sub-step 24: acquiring the upper-screen cost information corresponding to the association candidate according to the position of the association candidate on the first screen.

[0062] In an embodiment of the present invention, the duration of the candidates displayed at each position of the first screen of the target user (the target user may include users of the entire network and / or group users and / or users corresponding to the above-mentioned input information) can be counted in advance; then, based on the duration of the candidates displayed at each position of the first screen of the target user, the upper screen cost information of the candidates corresponding to each position of the first screen of the upper screen can be determined. Among them, the duration of each candidate displayed at each position of the first screen of the upper screen can refer to the duration between displaying the candidate at that position of the first screen and displaying the candidate at that position of the upper screen. Among them, for a position of the first screen, the upper screen cost information of the candidates corresponding to that position of the first screen of the upper screen can be determined based on the average duration of the candidates displayed at that position of the first screen of the target user. The upper screen cost information corresponding to a position of the first screen can be proportional to the average duration of the candidates displayed at that position of the first screen of the target user.

[0063] Furthermore, in the process of obtaining the upper screen cost information corresponding to the multiple association candidates displayed on the first screen, the position of the association candidate displayed on the first screen can be determined for each association candidate displayed on the first screen. Then, based on the position of the association candidate displayed on the first screen, the upper screen cost information of the candidate corresponding to each position of the upper screen can be found to determine the upper screen cost information corresponding to the association candidate.

[0064] Of course, after pre-counting the duration of the candidates displayed at each position on the first screen of the target user, the upper screen cost information of the candidates corresponding to each position on the first screen may be temporarily determined; instead, after executing the above-mentioned sub-step 22, the upper screen cost information of the candidates corresponding to each position on the first screen of the target user is determined based on the duration of the candidates displayed at each position on the first screen of the target user; and then sub-step 24 is executed, and the embodiment of the present invention does not limit this.

[0065] The step 208 may include the following sub-steps 42 to 44:

[0066] Sub-step 42: for an association candidate displayed on the first screen, determine the product of the upper screen cost information and the probability information corresponding to the association candidate, and obtain the product value corresponding to the association candidate;

[0067] Sub-step 44: determining recommendation cost information corresponding to recommending the multiple association candidates on the first screen according to the product value corresponding to each of the multiple association candidates.

[0068] For an association candidate displayed on the first screen, the product of the upper screen cost information and the probability information corresponding to the association candidate can be calculated to obtain the product value corresponding to the association candidate. Then, based on the product values ​​corresponding to the multiple association candidates displayed on the first screen, the recommendation cost information corresponding to the multiple association candidates displayed on the first screen can be determined. In one example, the sum of the product values ​​corresponding to the multiple association candidates displayed on the first screen can be used as the recommendation cost information corresponding to the multiple association candidates displayed on the first screen; that is, the total recommendation cost information corresponding to a screen of association candidates.

[0069] Of course, the step 208 can also perform other calculations based on the upper screen cost information and probability information corresponding to the multiple association candidates to obtain other calculation results; and then determine the recommended cost information corresponding to the multiple association candidates to be displayed on the first screen based on the other calculation results; the embodiment of the present invention does not limit this.

[0070] The acquisition of the recommendation income information of the association candidate in the above step 104 may refer to the following steps 210 to 212:

[0071] Step 210: Determine an input sequence corresponding to the association candidate, and obtain input cost information corresponding to the input sequence input by the user.

[0072] Step 212: Determine the recommendation benefit information corresponding to the association candidate according to the input cost information corresponding to the input sequence input by the user.

[0073] In the embodiment of the present invention, for each association candidate displayed on the first screen, an input sequence corresponding to the association candidate can be determined, such as phonetic notation of the association candidate; and input cost information corresponding to the input sequence input by the user can be obtained.

[0074] In one example, the length information corresponding to the input sequence can be determined, and the position of each character in the input sequence in the current input method keyboard can be determined; then, based on the length information corresponding to the input sequence and the position of each character in the input sequence in the current input method keyboard, the duration corresponding to the user inputting the input sequence can be determined; and based on the duration of the user inputting the input sequence, the input cost information corresponding to the user inputting the input sequence can be determined. The input cost information corresponding to the user inputting the input sequence can be determined in advance in the above manner, or can be determined in the above manner when executing step 210, and the embodiment of the present invention does not limit this.

[0075] In one example, the time duration of the target user inputting the input sequence corresponding to each candidate item can be counted in advance; then, based on the time duration of the target user inputting the input sequence corresponding to each candidate item, the input cost information of the user inputting the input sequence corresponding to each candidate item can be determined. Furthermore, when executing step 210, based on the input sequence of the association candidate, the input cost information corresponding to each input sequence determined in advance can be searched to determine the input cost information of the user inputting the input sequence corresponding to the association candidate.

[0076] Then, since after the association candidate is recommended, the user does not need to input the input sequence corresponding to the association candidate to obtain the association candidate; therefore, the recommendation benefit information corresponding to the association candidate can be determined according to the input cost information corresponding to the input sequence input by the user. In one example, the input cost information corresponding to the input sequence input by the user to the association candidate can be determined as the recommendation benefit information corresponding to the association candidate.

[0077] Among them, by adding up the recommendation profit information of multiple association candidates displayed on the first screen, the recommendation profit information corresponding to the multiple association candidates displayed on the first screen can be obtained, that is, the total recommendation profit information corresponding to one screen of association candidates.

[0078] Step 214: Determine whether the recommendation benefit information is greater than the recommendation cost information.

[0079] In the embodiment of the present invention, it can be determined whether the degree of improvement in user input efficiency caused by the recommended association candidate is greater than the degree of interference caused to the user by determining whether the recommended benefit information is greater than the recommended cost information. If the recommended benefit information is greater than the recommended cost information, step 216 can be executed. If the recommended cost information is greater than the recommended benefit information, step 218 can be executed. If the recommended benefit information is equal to the recommended cost information, either step 216 or step 218 can be executed, and the embodiment of the present invention does not limit this.

[0080] Step 216: display the association candidates.

[0081] If the recommendation benefit information is greater than the recommendation cost information, then the degree to which the recommended association candidates improve the user's input efficiency is greater than the degree of interference caused to the user, which means that recommending these association candidates can improve the user's input efficiency; at this time, these multiple association candidates can be controlled to be displayed on the first screen of the candidate area.

[0082] Step 218: Do not display the association candidates.

[0083] If the recommendation cost information is greater than the recommendation benefit information, the degree of interference caused by the recommended association candidates to the user is greater than the degree of improvement in the user's input efficiency, which means that recommending these association candidates is of little use and will interfere with the user; at this time, these multiple association candidates can be controlled not to be displayed on the first screen of the candidate area.

[0084] In addition, when the user performs a screen flipping operation, the recommended benefit information and recommended cost information corresponding to the association candidate displayed on the second screen can be determined according to steps 206-212; then, according to the recommended benefit information and recommended cost information corresponding to the association candidate displayed on the second screen, it is determined according to steps 214-218 whether the corresponding association candidate is displayed on the second screen. Similarly, for any screen in the input method candidate display area, the association candidate displayed on the screen can be recommended according to steps 208-218.

[0085] In summary, in an embodiment of the present invention, in the process of obtaining the recommendation cost information of the association candidates, the upper screen cost information and probability information respectively corresponding to the multiple association candidates displayed on the first screen can be obtained; based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates, the recommendation cost information corresponding to the multiple association candidates recommended on the first screen is determined; and thus the recommendation cost information of a screen of association candidates can be accurately determined.

[0086] Secondly, in an embodiment of the present invention, in the process of obtaining the recommendation benefit information corresponding to the association candidate, the input sequence corresponding to the association candidate can be obtained, and the input cost information corresponding to the input sequence input by the user can be obtained; then, based on the input cost information corresponding to the input sequence input by the user, the recommendation benefit information corresponding to the association candidate is determined; and thus the recommendation benefit information of a screen of association candidates can be accurately determined.

[0087] Again, in an embodiment of the present invention, if the recommendation benefit information is greater than the recommendation cost information, the association candidate is displayed; if the recommendation cost information is greater than the recommendation benefit information, the association candidate is not displayed; and further, when the degree to which the recommended association candidate improves the user input efficiency is greater than the degree of interference caused to the user, the association candidate is recommended to improve the user input efficiency; and when the degree of interference caused to the user by the recommended association candidate is greater than the degree to which the user input efficiency is improved, the association candidate is not recommended to avoid interference to the user caused by recommending unnecessary association candidates.

[0088] Reference Figure 3 , shows a flowchart of another optional embodiment of a recommended method of the present invention, which may specifically include the following steps:

[0089] Step 302: Obtain input information.

[0090] Step 304: Determine the association candidates corresponding to the input information.

[0091] Step 306: Obtain the upper screen cost information and probability information corresponding to the multiple association candidates displayed on the first screen.

[0092] Step 308: Determine to display the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information corresponding to the multiple association candidates.

[0093] Step 310: Determine an input sequence corresponding to the association candidate, and obtain input cost information corresponding to the input sequence input by the user.

[0094] Step 312: Determine the recommendation benefit information corresponding to the association candidate according to the input cost information corresponding to the input sequence input by the user.

[0095] Step 314: Determine whether the recommendation benefit information is greater than the recommendation cost information.

[0096] Among them, steps 302 to 314 are similar to the above-mentioned steps 202 to 214 and are not repeated here.

[0097] If the recommendation benefit information is greater than the recommendation cost information, then step 316 is executed; if the recommendation cost information is greater than the recommendation benefit information, then step 320 is executed. If the recommendation benefit information is equal to the recommendation cost information, then either step 318 or step 320 may be executed, and this embodiment of the present invention does not limit this.

[0098] Step 316: Determine whether the difference between the recommended benefit information and the recommended cost information is greater than a preset threshold.

[0099] If the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold, step 318 is executed; if the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold, step 320 is executed. The preset threshold can be set as required, and the embodiment of the present invention does not limit this.

[0100] Step 318: display the association candidates.

[0101] In an embodiment of the present invention, when the difference is greater than a preset threshold, it indicates that the degree to which the recommended association candidates improve the user input efficiency is greater than a certain value of the interference to the user; at this time, the multiple association candidates can be controlled to be displayed on the first screen of the candidate area.

[0102] Step 320: Do not display the association candidates.

[0103] In an embodiment of the present invention, when the difference is greater than a preset threshold, it indicates that the degree of improvement in user input efficiency caused by the recommended association candidates is not greater than a certain value of interference to the user; at this time, the first screen of the candidate area may not display these multiple association candidates.

[0104] In summary, when it is determined that the recommended benefit information is greater than the recommended cost information, it is determined whether the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold; if the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold, the association candidate is displayed; if the difference between the recommended benefit information and the recommended cost information is less than the preset threshold, the association candidate is not displayed; relative to the above embodiment, the embodiment of the present invention displays the association candidate when the degree of improvement in the user input efficiency of the recommended association candidate is greater than a certain value of the interference to the user, which can more effectively avoid the interference to the user caused by recommending unnecessary association candidates.

[0105] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0106] Reference Figure 4 , shows a structural block diagram of an embodiment of a recommendation device of the present invention, which may specifically include the following modules:

[0107] A first acquisition module 402, used to acquire input information;

[0108] The second acquisition module 404 is used to determine the association candidate corresponding to the input information, and obtain the recommendation cost information and recommendation benefit information of the association candidate;

[0109] The recommendation module 406 is used to recommend the association candidates based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

[0110] Reference Figure 5 , showing a structural block diagram of an optional embodiment of a recommendation device of the present invention.

[0111] In an optional embodiment of the present invention, the second acquisition module 404 includes:

[0112] The recommendation cost acquisition submodule 4042 is used to obtain the upper screen cost information and probability information corresponding to the multiple association candidates displayed on the first screen; based on the upper screen cost information and probability information corresponding to the multiple association candidates, determine the recommendation cost information corresponding to the multiple association candidates for recommendation on the first screen.

[0113] In an optional embodiment of the present invention, the recommended cost acquisition submodule 4042 includes:

[0114] The upper screen cost information determination unit 40422 is used to determine the position of an association candidate displayed on the first screen; according to the position of the association candidate displayed on the first screen, obtain the upper screen cost information corresponding to the association candidate.

[0115] In an optional embodiment of the present invention, the recommended cost acquisition submodule 4042 includes:

[0116] The recommendation cost information acquisition unit 40424 is used to determine, for an association candidate displayed on the first screen, the product of the upper screen cost information and the probability information corresponding to the association candidate, and obtain the product value corresponding to the association candidate; based on the product value corresponding to each of the multiple association candidates, determine the recommendation cost information corresponding to the multiple association candidates displayed on the first screen.

[0117] In an optional embodiment of the present invention, the second acquisition module 404 includes:

[0118] The recommendation benefit acquisition submodule 4044 is used to acquire the input cost information of the input sequence corresponding to the association candidate input by the user; and determine the recommendation benefit information corresponding to the association candidate according to the input cost information of the input sequence corresponding to the association candidate input by the user.

[0119] In an optional embodiment of the present invention, the recommendation module 406 includes:

[0120] The first candidate recommendation submodule 4062 is used to determine whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, the association candidate is displayed; if the recommendation cost information is greater than the recommendation benefit information, the association candidate is not displayed.

[0121] In an optional embodiment of the present invention, the recommendation module 406 includes:

[0122] The second candidate recommendation submodule 4064 is used to determine whether the difference between the recommended benefit information and the recommended cost information is greater than a preset threshold when the recommended benefit information is greater than the recommended cost information; if the difference between the recommended benefit information and the recommended cost information is greater than the preset threshold, the association candidate is displayed; if the difference between the recommended benefit information and the recommended cost information is less than the preset threshold, the association candidate is not displayed.

[0123] In summary, in an embodiment of the present invention, input information can be obtained; then, the association candidates corresponding to the input information are determined, and the recommendation cost information and recommendation benefit information of the association candidates are obtained; then, based on the recommendation benefit information and recommendation cost information corresponding to the association candidates, the association candidates are recommended; and then, by comprehensively considering the degree to which the recommended association candidates improve the user's input efficiency and the degree of interference caused to the user, the association candidates can be recommended to avoid interference to the user caused by recommending unnecessary association candidates, thereby improving input efficiency.

[0124] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0125] Figure 6is a structural block diagram of an electronic device 600 for recommendation according to an exemplary embodiment. For example, the electronic device 600 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0126] Reference Figure 6 , the electronic device 600 may include one or more of the following components: a processing component 602 , a memory 604 , a power component 606 , a multimedia component 608 , an audio component 610 , an input / output (I / O) interface 612 , a sensor component 614 , and a communication component 616 .

[0127] The processing component 602 generally controls the overall operation of the electronic device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 602 may include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0128] The memory 604 is configured to store various types of data to support operations on the electronic device 600. Examples of such data include instructions for any application or method operating on the electronic device 600, contact data, phone book data, messages, pictures, videos, etc. The memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0129] The power component 606 provides power to the various components of the electronic device 600. The power component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 600.

[0130] The multimedia component 608 includes a screen that provides an output interface between the electronic device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the electronic device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0131] The audio component 610 is configured to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC), and when the electronic device 600 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 604 or sent via the communication component 616. In some embodiments, the audio component 610 also includes a speaker for outputting audio signals.

[0132] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0133] The sensor assembly 614 includes one or more sensors for providing various aspects of status assessment for the electronic device 600. For example, the sensor assembly 614 can detect the open / closed state of the electronic device 600, the relative positioning of the components, such as the display and keypad of the electronic device 600, and the sensor assembly 614 can also detect the position change of the electronic device 600 or a component of the electronic device 600, the presence or absence of contact between the user and the electronic device 600, the orientation or acceleration / deceleration of the electronic device 600, and the temperature change of the electronic device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0134] The communication component 616 is configured to facilitate wired or wireless communication between the electronic device 600 and other devices. The electronic device 600 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 614 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 614 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0135] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0136] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, and the instructions can be executed by a processor 620 of an electronic device 600 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0137] A non-temporary computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform a recommendation method, the method comprising: obtaining input information; determining an association candidate corresponding to the input information, and obtaining recommendation cost information and recommendation benefit information of the association candidate; and recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate.

[0138] Optionally, the association candidates include multiple association candidates displayed on the first screen; obtaining the recommendation cost information of the association candidates includes: obtaining the upper screen cost information and probability information respectively corresponding to the multiple association candidates displayed on the first screen; and determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates.

[0139] Optionally, obtaining the upper-screen cost information corresponding to the multiple association candidates displayed on the first screen includes: for an association candidate displayed on the first screen, determining the position of the association candidate displayed on the first screen; and obtaining the upper-screen cost information corresponding to the association candidate based on the position of the association candidate displayed on the first screen.

[0140] Optionally, determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates includes: for an association candidate displayed on the first screen, determining the product of the upper screen cost information and the probability information corresponding to the association candidate to obtain the product value corresponding to the association candidate; determining the recommendation cost information corresponding to the multiple association candidates displayed on the first screen based on the product value corresponding to each association candidate in the multiple association candidates.

[0141] Optionally, obtaining the recommendation benefit information corresponding to the association candidate includes: obtaining input cost information of an input sequence corresponding to the association candidate input by a user; and determining the recommendation benefit information corresponding to the association candidate based on the input cost information of an input sequence corresponding to the association candidate input by the user.

[0142] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: judging whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, displaying the association candidate; if the recommendation cost information is greater than the recommendation benefit information, not displaying the association candidate.

[0143] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: when it is determined that the recommendation benefit information is greater than the recommendation cost information, judging whether the difference between the recommendation benefit information and the recommendation cost information is greater than a preset threshold; if the difference between the recommendation benefit information and the recommendation cost information is greater than the preset threshold, displaying the association candidate; if the difference between the recommendation benefit information and the recommendation cost information is less than the preset threshold, not displaying the association candidate.

[0144] Figure 7: is a structural diagram of an electronic device 700 for recommendation according to another exemplary embodiment of the present invention. The electronic device 700 may be a server, which may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPU) 722 (for example, one or more processors) and a memory 732, and one or more storage media 730 (for example, one or more mass storage devices) storing application programs 742 or data 744. Among them, the memory 732 and the storage medium 730 may be temporary storage or permanent storage. The program stored in the storage medium 730 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the server. Furthermore, the central processor 722 may be configured to communicate with the storage medium 730 to execute a series of instruction operations in the storage medium 730 on the server.

[0145] The server may also include one or more power supplies 726, one or more wired or wireless network interfaces 750, one or more input and output interfaces 758, one or more keyboards 756, and / or one or more operating systems 741, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0146] In an exemplary embodiment, the server is configured to execute one or more programs including instructions for performing the following operations by one or more central processors 722: obtaining input information; determining the association candidates corresponding to the input information, and obtaining the recommendation cost information and recommendation benefit information of the association candidates; and recommending the association candidates based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

[0147] Optionally, the association candidates include multiple association candidates displayed on the first screen; obtaining the recommendation cost information of the association candidates includes: obtaining the upper screen cost information and probability information respectively corresponding to the multiple association candidates displayed on the first screen; and determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates.

[0148] Optionally, obtaining the upper-screen cost information corresponding to the multiple association candidates displayed on the first screen includes: for an association candidate displayed on the first screen, determining the position of the association candidate displayed on the first screen; and obtaining the upper-screen cost information corresponding to the association candidate based on the position of the association candidate displayed on the first screen.

[0149] Optionally, determining the recommendation cost information corresponding to the multiple association candidates on the first screen based on the upper screen cost information and probability information respectively corresponding to the multiple association candidates includes: for an association candidate displayed on the first screen, determining the product of the upper screen cost information and the probability information corresponding to the association candidate to obtain the product value corresponding to the association candidate; determining the recommendation cost information corresponding to the multiple association candidates displayed on the first screen based on the product value corresponding to each association candidate in the multiple association candidates.

[0150] Optionally, obtaining the recommendation benefit information corresponding to the association candidate includes: obtaining input cost information of an input sequence corresponding to the association candidate input by a user; and determining the recommendation benefit information corresponding to the association candidate based on the input cost information of an input sequence corresponding to the association candidate input by the user.

[0151] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: judging whether the recommendation benefit information is greater than the recommendation cost information; if the recommendation benefit information is greater than the recommendation cost information, displaying the association candidate; if the recommendation cost information is greater than the recommendation benefit information, not displaying the association candidate.

[0152] Optionally, the recommending the association candidate based on the recommendation benefit information and recommendation cost information corresponding to the association candidate includes: when it is determined that the recommendation benefit information is greater than the recommendation cost information, judging whether the difference between the recommendation benefit information and the recommendation cost information is greater than a preset threshold; if the difference between the recommendation benefit information and the recommendation cost information is greater than the preset threshold, displaying the association candidate; if the difference between the recommendation benefit information and the recommendation cost information is less than the preset threshold, not displaying the association candidate.

[0153] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0154] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0155] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0156] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0157] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0158] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0159] A recommended method, a recommended device and an electronic device provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A recommendation method, characterized in that: include: Get input information; Determine the association candidate corresponding to the input information, obtain the recommendation benefit information of the association candidate by quantifying the cost spent by the user to obtain the association candidate by inputting the input sequence, and obtain the recommendation cost information of the association candidate by quantifying the cost of the user displaying the association candidate brought by recommending the association candidate; The recommendation benefit information is used to measure the degree to which the recommended association candidates improve the user input efficiency; The recommendation cost information is used to measure the interference degree caused by the recommended association candidates to the user; The association candidates are recommended based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

2. The method according to claim 1, characterized in that The association candidates include multiple association candidates displayed on the first screen; and obtaining the recommendation cost information of the association candidates includes: Obtaining the on-screen cost information corresponding to the multiple association candidates displayed on the first screen and the probability information corresponding to the multiple association candidates; the on-screen cost information is determined according to the duration of the candidate displayed on the first screen position of the target user's screen; According to the upper screen cost information and probability information respectively corresponding to the multiple association candidates, the recommendation cost information corresponding to the multiple association candidates is determined to be recommended on the first screen.

3. The method according to claim 2, characterized in that The obtaining of the upper screen cost information corresponding to the plurality of association candidates displayed on the first screen respectively includes: For an association candidate displayed on the first screen, determining a position of the association candidate displayed on the first screen; According to the position of the association candidate displayed on the first screen, the upper screen cost information corresponding to the association candidate is obtained.

4. The method according to claim 2, characterized in that: The determining, based on the upper screen cost information and probability information respectively corresponding to the plurality of association candidates, of recommending the recommendation cost information corresponding to the plurality of association candidates on the first screen comprises: For an association candidate displayed on the first screen, determine the product of the upper screen cost information and the probability information corresponding to the association candidate to obtain the product value corresponding to the association candidate; According to the product value corresponding to each of the multiple association candidates, it is determined to display the recommendation cost information corresponding to the multiple association candidates on the first screen.

5. The method according to claim 1, characterized in that The obtaining of the recommendation income information corresponding to the association candidate includes: Acquire input cost information of an input sequence corresponding to the association candidate input by the user; the input cost information is determined according to the duration of the input sequence input by the user; Recommendation benefit information corresponding to the association candidate is determined according to input cost information of an input sequence corresponding to the association candidate input by the user.

6. The method according to claim 1, characterized in that The recommending the association candidate based on the recommendation benefit information and the recommendation cost information corresponding to the association candidate includes: Determining whether the recommendation benefit information is greater than the recommendation cost information; If the recommendation benefit information is greater than the recommendation cost information, displaying the association candidate; If the recommendation cost information is greater than the recommendation benefit information, the association candidate is not displayed.

7. The method according to claim 1, characterized in that The recommending the association candidate based on the recommendation benefit information and the recommendation cost information corresponding to the association candidate includes: When it is determined that the recommended benefit information is greater than the recommended cost information, determining whether the difference between the recommended benefit information and the recommended cost information is greater than a preset threshold; If the difference between the recommendation benefit information and the recommendation cost information is greater than a preset threshold, displaying the association candidate; If the difference between the recommendation benefit information and the recommendation cost information is smaller than a preset threshold, the association candidate is not displayed.

8. A recommendation device, characterized in that: include: A first acquisition module, used to acquire input information; The second acquisition module is used to determine the association candidate corresponding to the input information, obtain the recommendation benefit information of the association candidate by quantifying the cost spent by the user to obtain the association candidate by inputting the input sequence, and obtain the recommendation cost information of the association candidate by quantifying the cost of the user displaying the association candidate brought by recommending the association candidate; The recommendation benefit information is used to measure the degree to which the recommended association candidates improve the user input efficiency; The recommendation cost information is used to measure the interference degree caused by the recommended association candidates to the user; The recommendation module is used to recommend the association candidates based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

9. An electronic device, characterized in that: The system comprises a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include instructions for performing the following operations: Get input information; Determine the association candidate corresponding to the input information, obtain the recommendation benefit information of the association candidate by quantifying the cost spent by the user to obtain the association candidate by inputting the input sequence, and obtain the recommendation cost information of the association candidate by quantifying the cost of the user displaying the association candidate brought by recommending the association candidate; The recommendation benefit information is used to measure the degree to which the recommended association candidates improve the user input efficiency; The recommendation cost information is used to measure the interference degree caused by the recommended association candidates to the user; The association candidates are recommended based on the recommendation benefit information and recommendation cost information corresponding to the association candidates.

10. A readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the recommendation method as described in any one of method claims 1-7.

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