A method and system for recommending integrated activities based on GSM network numbers

Abstract

The present invention provides a method and system for recommending converged activities based on G network numbers, which relates to the field of telecommunications operator business support technology, including: querying the converged group to which the user belongs based on the user's G network number; if the converged group exists, querying the user's tag information; filtering the G network target customer group and the converged group respectively according to the user's tag information, and obtaining the policy content and rules respectively; merging the policy content of the G network target customer group and the converged group according to the converged activity recommendation rules and recommending them. The present invention can identify the group members of the converged group to which the user belongs, obtain the corresponding policy content, and recommend to the user by making the recommendation capability of the converged group compatible on the existing user marketing recommendation platform of the G network, thereby opening up the association recommendation and marketing management between the group members and the converged group, expanding the scope of marketing recommendation content for G network users, and increasing user stickiness while helping the development of the converged group business, and reducing the willingness to leave the group / network.

Description

Technical Field

[0001] The present invention relates to the technical field of telecommunication operator business support, and in particular to a method and system for recommending convergence activities based on G network numbers. Background Art

[0002] The marketing recommendation for G network users in the current operator business is already relatively mature, mainly focusing on activities / product recommendations directly related to the current user. When the user belongs to the family circle and the group owner can participate in more favorable activities, the members will have a higher interest in such discounts in the same circle. However, the current system cannot recommend the group owner's preferential activities to other members of the circle at the same time, thereby reducing the optional range and accuracy of marketing recommendations. Summary of the invention

[0003] In response to the above problems, the present invention provides a method and system for recommending integrated activities based on G-network numbers. On the basis of the recommendations of the existing intelligent marketing platform, the method and system add the identification of potential family members, analyze the packages suitable for recommending to potential family members, and then open up the association recommendations and business processing between members and family circles, thereby facilitating the expansion of telecommunications business.

[0004] To achieve the above object, the present invention provides a method for recommending converged activities based on G network numbers, comprising:

[0005] Query the fusion group to which the user belongs based on the user's G network number;

[0006] If the fusion group exists, querying user tag information;

[0007] According to the user tag information, the G network target customer group and the fusion group are filtered respectively to obtain policy content and rules respectively;

[0008] The strategy contents of the G network target customer group and the fusion group are merged and recommended according to the fusion activity recommendation rules.

[0009] As a further improvement of the present invention, after obtaining the policy contents and rules of the G network target customer group and the fusion group, the policy contents and rules of the G network target customer group and the fusion group are prioritized respectively.

[0010] As a further improvement of the present invention, after obtaining the policy content and rules of the G network target customer group and the fusion group, the rules are filtered.

[0011] As a further improvement of the present invention, after filtering the rules, the G network target customer group and the fusion group return different numbers of policy contents and rules respectively.

[0012] As a further improvement of the present invention, if the fusion group does not exist, only the policy content and rules of the G network target customer group are obtained, and the G network policy content is recommended.

[0013] As a further improvement of the present invention, the process of obtaining the policy content and rules of the G network target customer group and recommending the G network policy content includes:

[0014] Filter the G network target customer group according to the tag information respectively;

[0015] Obtain the policy content and rules of the G network target customer group;

[0016] Sort the obtained policy content and rules of the G network target customer group by priority;

[0017] Filter the policy content of the G network target customer group after priority sorting by rules;

[0018] Obtain the available policy content of the G network target customer group;

[0019] Recommend the policy content according to the G network activity recommendation rules.

[0020] As a further improvement of the present invention, preset the fusion activity recommendation rules, including: the total number of fusion activity recommendations;

[0021] The proportion of the number of policy contents of the fusion group and the number of policy contents of the G network;

[0022] When the policy content of the fusion group is insufficient, supplement the G network policy content; when the policy content of the G network is insufficient, do not supplement.

[0023] As a further improvement of the present invention, when merging the policy contents of the G network target customer group and the fusion group, re - sort the policy contents.

[0024] As a further improvement of the present invention, the recommendation priority of the policy content of the fusion group is higher than that of the policy content of the G network, and the policy content of the fusion group is default in the front.

[0025] The present invention also provides a system for recommending fusion activities according to the G network number, including: a fusion group query module, a tag information query module, a policy content acquisition module, and a policy fusion recommendation module;

[0026] The fusion group query module is used for:

[0027] Query the fusion group to which the user belongs according to the user's G network number;

[0028] The tag information query module is used for:

[0029] If the fusion group exists, querying user tag information;

[0030] The policy content acquisition module is used to:

[0031] According to the user tag information, the G network target customer group and the fusion group are filtered respectively to obtain policy content and rules respectively;

[0032] The strategy fusion recommendation module is used to:

[0033] The strategy contents of the G network target customer group and the fusion group are merged and recommended according to the fusion activity recommendation rules.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] By making the recommendation capability of the integrated group compatible with the existing user marketing recommendation platform of the G network, the present invention can identify the group members of the integrated group to which the user belongs, obtain the corresponding policy content, make recommendations for the user, and open up the associated recommendation and marketing management between the group members and the integrated group, thereby expanding the scope of marketing recommendation content for G network users, helping the development of the integrated group business, increasing user stickiness, and reducing the willingness to leave the group / network. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart of a method for recommending converged activities based on G network numbers disclosed in an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a system for recommending converged activities based on G network numbers disclosed in an embodiment of the present invention;

[0038] Figure 3 A detailed flow chart of recommending converged activities based on G network numbers disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0041] like Figure 1 As shown, the present invention provides a method for recommending fusion activities based on G network numbers, including:

[0042] S1. Query the convergence group to which the user belongs according to the user's G network number;

[0043] S2. If the convergence group exists, query the user label information;

[0044] Among them,

[0045] (1) An attribute label "associated convergence group number" is added to the label library of the big data platform to distinguish whether there is a convergence group number;

[0046] (2) If the convergence group does not exist, only obtain the policy content and rules of the G network target customer group and perform G network policy content recommendation. The process includes:

[0047] Filter the G network target customer group according to the label information respectively;

[0048] Obtain the policy content and rules of the G network target customer group;

[0049] Sort the priorities of the obtained policy content and rules of the G network target customer group;

[0050] Filter the rules for the policy content of the G network target customer group after priority sorting;

[0051] Obtain the available policy content of the G network target customer group;

[0052] Recommend the policy content according to the G network activity recommendation rules.

[0053] S3. Filter the G network target customer group and the convergence group according to the user label information respectively, and obtain the policy content and rules respectively;

[0054] Among them,

[0055] After obtaining the policy content and rules of the G network target customer group and the convergence group, it is necessary to sort the priorities of the policy content and rules of the G network target customer group and the convergence group;

[0056] It is necessary to filter the rules;

[0057] The order of priority sorting and rule filtering is not in a specific sequence;

[0058] After filtering the rules, the G network target customer group and the convergence group return different numbers of policy content and rules respectively.

[0059] S4. Merge the policy content of the G network target customer group and the convergence group according to the convergence activity recommendation rules and recommend.

[0060] Among them,

[0061] It is necessary to preset the convergence activity recommendation rules, including: the total number of convergence activity recommendations;

[0062] The proportion of the number of policy contents in the convergence group to the number of policy contents in the G network;

[0063] When the number of policy contents in the convergence group is insufficient, supplement the policy contents of the G network; when the number of policy contents in the G network is insufficient, do not supplement.

[0064] For example:

[0065] Set the proportion of the number of policy contents in the convergence group and the number of policy contents in the G network to 4:6 respectively;

[0066] When the total number of recommended convergence activities is set to 1 to 5 respectively, the number of policy contents in the convergence group and the number of policy contents in the G network are distributed as follows in the table:

[0067] Total number of recommended integration activities Number of policy contents of G network Number of policy contents of integration group 1 0 1 2 Math.round(2*0.6) = 1 Math.round(2*0.4) = 1 3 Math.round(3*0.6) = 2 Math.round(3*0.4) = 1 4 Math.round(4*0.6) = 2 Math.round(4*0.4) = 2 5 Math.round(5*0.6) = 3 Math.round(5*0.4) = 2

[0068] When the G network number is not associated with the convergence group or the convergence group fails to query available policy contents, all matching G network policy contents are returned.

[0069] When the G network number is associated with the convergence group and available policy contents are queried, according to the above table screening conditions:

[0070] When the total number of recommended convergence activities is 1, the policy contents of the convergence group are recommended first, and if not, the policy contents of the G network are recommended.

[0071] When the total number of recommended convergence activities is greater than 1, the policy contents of the convergence group and the G network are selected in a ratio of 4:6. If the number of policy contents in the convergence group is insufficient, supplement and recommend the policy contents of the G network; if the number of policy contents in the G network is insufficient, do not supplement.

[0072] This point is illustrated by examples for specific recommended operation positions as follows:

[0073] If no available policy contents are matched in the convergence group, finally recommend 5 G network policy contents.

[0074] If only 1 available policy content is matched in the convergence group, finally recommend 1 convergence + 4 G networks.

[0075] If 2 available policy contents are matched in the convergence group, recommend 2 convergences + 3 G networks.

[0076] If 3 available policy contents are matched in the convergence group, still recommend 2 convergences + 3 G networks.

[0077] In the present invention, when merging the policy contents of the G network target customer group and the convergence group, the policy contents are reordered.

[0078] Among them,

[0079] The recommendation priority of the policy content of the convergence group is higher than that of the G network, and the policy content of the convergence group is defaulted to be in the front.

[0080] As Figure 2 shown, the present invention also provides a system for implementing steps S1 to S4, including: a convergence group query module, a tag information query module, a policy content acquisition module, and a policy fusion recommendation module;

[0081] The convergence group query module is used for:

[0082] querying the convergence group to which the user belongs according to the user's G network number;

[0083] The tag information query module is used for:

[0084] if the convergence group exists, querying the user's tag information;

[0085] The policy content acquisition module is used for:

[0086] filtering the G network target customer group and the convergence group respectively according to the user's tag information, and respectively obtaining the policy content and rules;

[0087] The policy fusion recommendation module is used for:

[0088] merging the policy content of the G network target customer group and the convergence group according to the convergence activity recommendation rules and making a recommendation.

[0089] Embodiment:

[0090] As Figure 3 shown, it is preset that the total number of convergence activity recommendations of the system policy recommendation module is 5, and the policy content of the convergence group and the G network is selected according to a ratio of 4:6. Specifically:

[0091] Step 1: G network user A, with the number 18873286798, logs in to the online APP system through the number;

[0092] Step 2: User A enters the policy recommendation page to query the available activity content;

[0093] Step 3: The APP system obtains the query request of user A, and queries the convergence group number to which user A belongs according to the number of user A;

[0094] Step 4: It is found that user A has a group number, and at the same time, the available policy content of user A in the G network and the convergence group is obtained, including:

[0095] Step 41: After querying the user's tag information, filter the G network target customer group, and sequentially obtain the policy ID, the policy content ID corresponding to the policy ID, and the rule information related to the policy content;

[0096] According to the obtained policy ID, the policy content ID corresponding to the policy ID, and the rule information related to the policy content, the G network recommendation policy and priority ranking are performed;

[0097] Filter customer recommendation rules;

[0098] Obtained 3 available G network recommended strategies;

[0099] Step 42: After querying the user tag information, filter the fusion group, and obtain the policy ID, the policy content ID corresponding to the policy ID, and the rule information related to the policy content in sequence;

[0100] According to the acquired policy ID, the policy content ID corresponding to the policy ID, and the rule information related to the policy content, the fusion group recommends the policy and prioritizes it;

[0101] Filter customer recommendation rules;

[0102] Obtained 4 available fusion group recommendation strategies;

[0103] Step 5, calculate the fusion recommendation rule: the number of G network policy content recommendations = 5*0.6 = 3; the number of fusion group policy content recommendations = 5*0.4 = 2; then select the top 3 policy contents after priority sorting in the G network, and select the top 2 policy contents after priority sorting in the fusion group;

[0104] Step 6: Rearrange the selected 5 policy contents, and put the 2 policy contents of the fusion group before the 3 policy contents of the G network, and return to the policy recommendation page to display it to user A.

[0105] Advantages of the present invention:

[0106] By integrating the recommendation capability of the integrated group with the existing user marketing recommendation platform of the G network, it is possible to identify the group members of the integrated group to which the user belongs, obtain the corresponding policy content, and make recommendations for the user, thus opening up the association recommendation and marketing management between group members and the integrated group, expanding the scope of marketing recommendation content for G network users, and helping the development of the integrated group business while increasing user stickiness and reducing the willingness to leave the group / network.

[0107] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for recommending integrated activities based on G network numbers, characterized in that, it includes: Query the integrated group to which the user belongs according to the user's G network number; If the integrated group exists, query the user label information; Filter the G network target customer group and the integrated group respectively according to the user label information, and obtain the policy content and rules respectively: prioritize the policy content and rules of the G network target customer group and the integrated group; Filter the rules of the G network target customer group and the integrated group to obtain the available rules of the G network target customer group and the integrated group; the G network target customer group and the integrated group return different numbers of policy content and rules respectively; Merge the policy content of the G network target customer group and the integrated group according to the integrated activity recommendation rules and recommend; If the integrated group does not exist, only obtain the policy content and rules of the G network target customer group and perform G network policy content recommendation; The process of performing G network policy content recommendation includes: filtering the G network target customer group according to the label information respectively; obtaining the policy content and rules of the G network target customer group; prioritizing the policy content and rules of the obtained G network target customer group; filtering the policy content of the G network target customer group after priority sorting; obtaining the available policy content of the G network target customer group; performing the policy content recommendation according to the G network activity recommendation rules; Merge the policy content of the G network target customer group and the integrated group according to the integrated activity recommendation rules and recommend: preset the integrated activity recommendation rules, including: the total number of integrated activity recommendations is 5; the policy content of the integrated group and the policy content of the G network are selected in a ratio of 4:6, select the top 3 policy content after priority sorting in the G network, select the top 2 policy content after priority sorting in the integrated group, re-sort the above 5 selected policy content, and the 2 policy content of the integrated group are ranked in front of the 3 policy content of the G network, and return to the policy recommendation page to display to the user; when the policy content of the integrated group is insufficient, supplement the G network policy content. If no available policy content is matched in the integrated group, finally recommend 5 G network policy content. If only 1 available policy content is matched in the integrated group, finally recommend 1 policy content of the integrated group and 4 G network policy content; when the policy content of the G network is insufficient, no supplement is made.

2. The method according to claim 1, characterized in that: The recommendation priority of the policy content of the integrated group is higher than the recommendation priority of the policy content of the G network, and the policy content of the integrated group is default in the front.

3. A system for implementing the method according to any one of claims 1 to 2, characterized in that, it includes: An integrated group query module, a label information query module, a policy content acquisition module and a policy integration recommendation module; The integrated group query module is used for: Query the integrated group to which the user belongs according to the user's G network number; The label information query module is used for: If the integrated group exists, query the user label information; The policy content acquisition module is used for: Filter the G network target customer group and the integrated group respectively according to the user label information, and obtain the policy content and rules respectively; The policy fusion recommendation module is used for: Merging the policy content of the G network target customer group and the fusion group according to the fusion activity recommendation rules and making recommendations.

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