CN110378798B - Heterogeneous social network construction method, group recommendation method, device and equipment - Google Patents
Heterogeneous social network construction method, group recommendation method, device and equipment Download PDFInfo
- Publication number
- CN110378798B CN110378798B CN201910478639.3A CN201910478639A CN110378798B CN 110378798 B CN110378798 B CN 110378798B CN 201910478639 A CN201910478639 A CN 201910478639A CN 110378798 B CN110378798 B CN 110378798B
- Authority
- CN
- China
- Prior art keywords
- recommendation
- group
- user
- content
- recommended
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 60
- 238000010276 construction Methods 0.000 title abstract description 8
- 230000006399 behavior Effects 0.000 claims abstract description 69
- 238000012163 sequencing technique Methods 0.000 claims description 25
- 238000004590 computer program Methods 0.000 claims description 16
- 238000001914 filtration Methods 0.000 claims description 10
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 14
- 230000006870 function Effects 0.000 description 12
- 230000000694 effects Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000010079 rubber tapping Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000010897 surface acoustic wave method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9536—Search customisation based on social or collaborative filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Marketing (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Computing Systems (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a heterogeneous social network construction method, a heterogeneous social network construction device, a group recommendation method, a group recommendation device, electronic equipment and a computer-readable storage medium. The construction method of the heterogeneous social network comprises the following steps: determining a plurality of social groups corresponding to first recommended behaviors of the seed user on the target content based on the first recommended behaviors, wherein the target content comprises a content tag; determining a target user performing a second recommendation action on the target content in the plurality of social groups; and constructing a heterogeneous social group corresponding to the content tag based on the seed user and the target user. According to the technical scheme of the embodiment of the invention, the simple and easy-to-operate heterogeneous social network can be constructed, and the accurate personalized group recommendation can be carried out on the basis of the heterogeneous social network.
Description
Technical Field
The present invention relates to the field of data mining technologies, and in particular, to a method and an apparatus for constructing a heterogeneous social network, a group recommendation method, a group recommendation apparatus, an electronic device, and a computer-readable storage medium.
Background
Nowadays, in order to improve the user experience, the network provides rich personalized content recommendation for the user, so that the user can find out the content of interest.
In an existing technical scheme, social activity recommendation is performed based on a heterogeneous graph model, and a method for constructing the heterogeneous graph model includes the following steps: the method comprises the steps of judging influence factors, reducing dimension of features, selecting heterogeneous graph nodes, establishing node relation, establishing virtual connection for hanging nodes, directly or indirectly connecting user nodes and active nodes in a graph network after a heterogeneous graph model is established, having higher correlation among the closely connected nodes, and performing descending order arrangement on candidate activities according to the correlation between the user nodes and the active nodes, so that K bits with the highest value are selected to form a user recommendation list. The method for constructing the heterogeneous graph model is complex, and the precision of recommended content needs to be improved.
Disclosure of Invention
Embodiments of the present invention provide a method for constructing a heterogeneous social network, a device for constructing a heterogeneous social network, a group recommendation method, a group recommendation device, an electronic device, and a computer-readable storage medium, so as to construct a simple and easy-to-operate heterogeneous social network, and perform accurate and personalized group recommendation on the basis of the heterogeneous social network.
To solve the above technical problem, the embodiment of the present invention is implemented as follows:
in a first aspect, an embodiment of the present invention provides a method for constructing a heterogeneous social network, where the method includes: determining a plurality of social groups corresponding to first recommended behaviors of the seed user on the target content based on the first recommended behaviors, wherein the target content comprises a content tag; determining a target user performing a second recommendation action on the target content in the plurality of social groups; and constructing a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
In a second aspect, an embodiment of the present invention provides a method for obtaining a historical recommendation list of each user in a heterogeneous social group according to the first aspect; determining a group recommendation list of each user based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user; recommending and sequencing recommended contents in each group recommendation list based on historical recommendation behaviors of each user in the heterogeneous social group; and respectively recommending contents to each user in the heterogeneous social group based on the result of the recommendation sequencing.
In a third aspect, an embodiment of the present invention provides an apparatus for constructing a heterogeneous social network, where the apparatus includes: the social group determination module is used for determining a plurality of social groups corresponding to first recommended behaviors of the seed users on the basis of the first recommended behaviors of the seed users on the target content, wherein the target content comprises a content tag; the target user determination module is used for determining a target user performing a second recommendation action on the target content in the plurality of social groups; and the heterogeneous social group building module is used for building a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
In a fourth aspect, an embodiment of the present invention provides a group recommendation apparatus, where the group recommendation apparatus includes: a history recommendation list obtaining module, configured to obtain a history recommendation list of each user in the heterogeneous social group according to the first aspect; the group recommendation list determining module is used for determining a group recommendation list of each user based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user; the recommendation sequencing determination module is used for performing recommendation sequencing on the recommended contents in each group recommendation list based on the historical recommendation behaviors of each user in the heterogeneous social group; and the single recommendation module is used for recommending contents to each user in the heterogeneous social group based on the recommendation sequencing result.
In a fifth aspect, an embodiment of the present invention provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, implements the method of constructing a heterogeneous social network as described in the first aspect above or the method of group recommendation as described in the second aspect.
In a sixth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for constructing a heterogeneous social network according to the first aspect or the method for recommending a group according to the second aspect.
According to the technical scheme of the embodiment of the invention, on one hand, a plurality of social groups corresponding to the first recommended behaviors are determined based on the first recommended behaviors of the seed user on the target content, and the social groups to which the target content is shared can be obtained; on the other hand, a target user performing a second recommendation action on the target content in the plurality of social groups is determined, and the target user in the plurality of social groups can be obtained; on the other hand, a heterogeneous social group corresponding to the content tag is constructed based on the seed user and the target user, and a simple and easy-to-operate heterogeneous social network can be constructed, so that accurate and personalized group recommendation can be performed on the basis of the heterogeneous social network, and the content recommendation precision is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 illustrates a flow diagram of a method of building a heterogeneous social network provided in accordance with some embodiments of the present invention;
FIG. 2 illustrates a flow diagram of a group recommendation method provided in accordance with some embodiments of the invention;
FIG. 3 illustrates a schematic diagram of an application scenario of a method of building a heterogeneous social network provided in accordance with some embodiments of the present invention;
FIG. 4 illustrates a schematic diagram of an application scenario of a group recommendation method provided in accordance with some embodiments of the present invention;
FIG. 5 illustrates a schematic block diagram of a building apparatus for a heterogeneous social network provided in accordance with some embodiments of the present invention;
FIG. 6 illustrates a schematic block diagram of a group recommendation device provided in accordance with some embodiments of the present invention; and
FIG. 7 illustrates a schematic block diagram of an electronic device provided in accordance with some embodiments of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 illustrates a flow diagram of a method for building a heterogeneous social network, provided in accordance with some embodiments of the present invention. Referring to fig. 1, the method for constructing the heterogeneous social network includes steps S110, S120, and S130. The method for constructing the heterogeneous social network in the exemplary embodiment of fig. 1 is described in detail below.
Referring to fig. 1, in step S110, a plurality of social groups corresponding to a first recommended behavior of a target content based on a first recommended behavior of a seed user are determined, wherein the target content includes a content tag.
In an example embodiment, a seed user carries out a first recommendation action on target content, the target content is recommended to a plurality of social groups where the seed user is located, and according to the first recommendation action of the seed user, which social groups the target content is shared to are determined. The target content may be information, APP, video, audio, or other content such as novel, which is not limited in the present invention. The first recommended behavior comprises a sharing behavior, and can also be other recommended behaviors such as a forwarding behavior. Social groups include, but are not limited to, QQ groups, WeChat groups. The content tag is used to distinguish attributes of different content, e.g. history, NBA. For example, the seed user U1 shares a video a1 including a content tag as history with the QQ group G1, the QQ group G2, and the QQ group G3, and according to the sharing behavior of the seed user U1, the social group corresponding to the sharing behavior may be determined to be the QQ group G1, the QQ group G2, and the QQ group G3.
Next, in step S120, a target user performing a second recommended action on the target content in the plurality of social groups is determined.
In an example embodiment, in a social group of a plurality of recommended target contents, a part of members browse the target contents, and in the part of members, some members do not make evaluation after browsing, and other members do a second recommendation action on the target contents after browsing. And collecting feedback of the members in the social group with the shared target content to the target content, and determining which members perform second recommendation behaviors on the target content, wherein the members are target users. For example, in the target content, i.e., the video a1 whose content tag is history, among the shared QQ group G1, QQ group G2, and QQ group G3, the user U2 in the QQ group G1 browses the video a1 and then shares the video a1 again with another QQ group; after browsing the video A1, a user U3 in the QQ group G2 shares the video A1 with the QQ space of the user U; the user U4 in the QQ group G3 commented and liked the video A1 after browsing the video A1; the other users do not make the second recommended action for video a 1. Collecting the feedback of the video A1 from the members of the three QQ groups can determine that the target users are user U2, user U3 and user U4.
In an example embodiment, the second recommended behavior may be an evaluation behavior, or may be a sharing behavior, for example, sharing the target content to another social group again, or may be another recommended behavior such as a praise behavior.
Finally, in step S130, a heterogeneous social group corresponding to the content tag is constructed based on the seed user and the target user.
In an exemplary embodiment, on the basis of the existing social group, the seed user and the target user determined in step S120 together form a new heterogeneous social network, where each heterogeneous social network represents a heterogeneous social group, and the heterogeneous social group is an interest group interested in the content tag included in the target content, that is, the content tag reflects an interest attribute of the heterogeneous social group.
In an example embodiment, a heterogeneous social group differs from a native social group in that the heterogeneous social group has dual attributes of social relationship and interest. Members belonging to the same heterogeneous social group are friends or friends of friends with each other; in addition, the members belonging to the heterogeneous social group are interested in the attributes corresponding to the content tags corresponding to the heterogeneous social group, and have common preferences. In addition, members of a heterogeneous social group are not physically located in the same social group, but are distributed among multiple native social groups. For example, the seed user U1 makes a first recommended action on the target content A1 that includes the content tag T1; recommending the target content A1 to a social group G1, a social group G2 and a social group G3, wherein a member U2 in the social group G1, a user U3 in the social group G2 and a user U4 in the social group G3 respectively perform a second recommendation action on the target content A1, so that the member U2, the member U3 and the member U4 are determined to be target users; the seed user U1 and the target users U2, U3, U4 are constructed as a heterogeneous social group GA1 corresponding to the content tag T1.
According to the method for constructing the heterogeneous social network in the example embodiment of fig. 1, on one hand, based on a first recommended behavior of a seed user for target content, a plurality of social groups corresponding to the first recommended behavior are determined, and a social group to which the target content is shared can be obtained; on the other hand, a target user performing a second recommendation action on the target content in the plurality of social groups is determined, and the target user in the plurality of social groups can be obtained; on the other hand, a heterogeneous social group corresponding to the content tag is constructed based on the seed user and the target user, and a simple and easy-to-operate heterogeneous social network can be constructed.
Fig. 2 illustrates a flow diagram of a group recommendation method provided in accordance with some embodiments of the present invention. Referring to fig. 2, the group recommendation method includes step S210, step S220, step S230, and step S240. The group recommendation method in the exemplary embodiment of fig. 2 is explained in detail below.
Referring to fig. 2, in step S210, a history recommendation list of each user in the heterogeneous social group is obtained.
In an example embodiment, each member in the heterogeneous social group performs several recommendation actions, and a historical recommendation list of each member is obtained, wherein the list comprises a record of all past recommendation actions of each member, the record of the recommendation actions comprises but is not limited to recommendation content related to the recommendation actions, content tags corresponding to the recommendation content, and information of recommendation time of the recommendation content. The recommended behavior may be a sharing behavior, or recommended behaviors such as praise and forward, and the invention is not limited to this.
Next, in step S220, a group recommendation list of each user is determined based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user.
In an example embodiment, recommended contents appearing in the historical recommendation lists of users in the heterogeneous social group are aggregated into one recommended content list, wherein the repeatedly appearing recommended contents are regarded as the same recommended content. And filtering the recommended content list according to the content tags corresponding to the heterogeneous social groups, and deleting the recommended content which does not comprise the content tags corresponding to the heterogeneous social groups to obtain the group recommended list of each user. The group recommendation lists for each user in the same heterogeneous social group are the same. For example, heterogeneous social group GA1 includes members U1, U2, U3, where the historical recommendation list of user U1 is { A1, A2, A3}, the historical recommendation list of user U2 is { A1}, and the historical recommendation list of user U3 is { A1, A2 }. The contents A1, A2 and A3 appearing in the history recommendation lists of the three users are gathered into a recommendation content list { A1, A2 and A3 }. The recommended content list { A1, A2, A3} is filtered according to the content tag T1 corresponding to the heterogeneous social group GA1, and only the content A1 including the T1 tag and the content A2 including the T1 tag are related, so that the content A3 not including the T1 tag is filtered out, and finally the group recommended list of the heterogeneous social group GA1 is { A1, A2 }.
Continuing to refer to fig. 2, in step S230, recommendation ranking is performed on the recommended content in each group recommendation list based on the historical recommendation behavior of each user in the heterogeneous social group.
In an example embodiment, the number of times and the time at which each recommended content in the group recommendation list is recommended is determined based on historical recommendation behaviors of each user in the heterogeneous social group. A record of the historical recommendation behavior of each user may be obtained in the historical recommendation list of each user in the heterogeneous social group obtained in step S210, where the record includes, but is not limited to, recommended content related to the recommendation behavior, a content tag corresponding to the recommended content, and information of a time when the recommended content is recommended.
In an example embodiment, the recommendation popularity of users of recommended content in a heterogeneous social group is determined based on the number of times the recommended content is recommended. For example, if the statistical result shows that the number of recommended times of the content a1 is 3, the number of recommended times of the content a2 is 2, and the number of recommended times of the content A3 is 1, the user recommendation degree of the content a1 is 3, the user recommendation degree of the content a2 is 2, and the user recommendation degree of the content a1 is 1. The higher the recommendation heat of the user is, the higher the recommendation content corresponding to the recommendation heat of the user is when performing recommendation sorting.
In an example embodiment, a recommendation order of recommended content in a heterogeneous social group is determined based on a time at which the recommended content is recommended. For example, the recommended contents a1, a2 and A3 are recommended only once, the recommended content a1 is recommended at 5-month-20 days, the recommended content a2 is recommended at 5-month-18 days, and the recommended content A3 is recommended at 5-month-15 days, so that the recommended contents are recommended in a heterogeneous social group in the order of { a1, a2 and A3}, the latest recommended content in the recommendation record is ranked in the front, and the earlier the recommended content is, the later the recommendation is.
In an example embodiment, each recommended content in the group recommendation list is subjected to comprehensive sequencing, and statistical analysis is performed according to two parameters of the user recommendation heat and the recommendation sequence to obtain the recommendation sequencing of each recommended content in the group recommendation list. The collaborative filtering algorithm may be used, and other filtering algorithms may also be used, and the present invention is not particularly limited thereto. For example, the recommendation popularity of the content A1 is 3, the recommendation popularity of the content A2 is 2, the recommendation popularity of the content A1 is 1, and the recommendation order of the recommended content in the heterogeneous social group obtained according to the time when the recommended content is recommended is { A1, A2, A3}, so that the final recommendation is ranked as { A1, A2, A3 }.
Finally, in step S240, content recommendation is performed to each user in the heterogeneous social group based on the result of the recommendation ranking.
In the exemplary embodiment, the recommendation ranking result obtained in step S230 is combined with the respective historical recommendation behaviors of the users in the heterogeneous social group, so as to eliminate the recommended content that the user has performed the recommendation behavior once, and recommend the rest of the recommended content to the user, thereby finally realizing that a brand-new and interested personalized content is recommended to each user. For example, the result of the recommendation ranking is { a1, a2, A3}, the user U1 has recommended the contents a1, a2, A3, so no new content is recommended to the user U1; the user U2 has recommended content A1, so content A2 is recommended to the user U2 first, and then content A3 is recommended to the user U2; the user U3 has recommended the content A1, A2, so only the content A3 is recommended to the user U3.
According to the group recommendation method in the example embodiment of fig. 2, on one hand, the historical recommendation list of each user in the heterogeneous social group obtained by the construction method of the heterogeneous social network is obtained, and specific information of the historical recommendation content of each user can be obtained; on the other hand, the group recommendation list of each user is determined based on the content tags corresponding to the heterogeneous social group and the historical recommendation lists of each user, and the group recommendation list corresponding to the heterogeneous social group can be obtained; on the other hand, recommendation sequencing is carried out on recommendation contents in each group recommendation list based on historical recommendation behaviors of each user in the heterogeneous social group, and recommendation sequencing of the group recommendation list can be obtained; in another aspect, content recommendation is performed on each user in the heterogeneous social group based on the recommendation ranking result, and accurate personalized recommendation can be provided for each member in the heterogeneous social group.
Fig. 3 is a schematic diagram illustrating an application scenario of a method for constructing a heterogeneous social network according to some embodiments of the present invention.
Referring to fig. 3, in an example embodiment, in step S310, the seed user U1 shares content a1 with tag T1 into social group G1, social group G2, and social group G3, and several members of social group G1, social group G2, and social group G3 browse content a1, some of which recommend content a 1. In step S320, the seed user U1 and the members recommended for content A1 in step S310 are constructed as a heterogeneous social network GA 1.
Referring to fig. 3, in an example embodiment, similar to the foregoing process, the seed user U1 shares content A3 with tag T3 into social group G1, social group G2, and social group G4, and several members of social group G1, social group G2, and social group G4 browse content A3, some of which recommend content A3. The seed user U1 and the member who made the recommendation for content A3 are constructed as a heterogeneous social network GA 2.
Fig. 4 is a schematic diagram illustrating an application scenario of a group recommendation method according to some embodiments of the present invention.
Referring to FIG. 4, in an example embodiment, heterogeneous social network 410 includes three users U1, U2, and U3. All the content that three users have performed recommendation actions, i.e., the user history recommended content 420, includes content a1, content a2, content A3, and content a 4. Wherein content a1 includes tag T1, content a2 includes tags T1, T3, content A3 includes tags T1, T3, and content a4 includes tag T3. The content tag corresponding to the heterogeneous social network 410 is a tag T1, the user historical recommended content 420 is screened according to the tag T1, the content A4 is excluded, and only the content A1, the content A2 and the content A3 which contain the tag T1 are left, so that a group recommendation list is obtained.
In an example embodiment, the statistically obtained number of times that the content a1 is recommended is 3, the number of times that the content a2 is recommended is 2, and the number of times that the content A3 is recommended is 1, then the user recommendation popularity of the content a1 is 3, the user recommendation popularity of the content a2 is 2, and the user recommendation popularity of the content a1 is 1, and the recommendation ranks are { a1, a2, A3} in combination with the recommendation order obtained from the recommendation time.
In an example embodiment, the user U1 has recommended content A1, A2, A3, so no new content is recommended to the user U1; the user U2 has recommended content A1, so content A2 is recommended to the user U2 first, and then content A3 is recommended to the user U2; the user U3 has recommended the content A1, A2, so only the content A3 is recommended to the user U3.
FIG. 5 illustrates a schematic block diagram of an apparatus for building a heterogeneous social network provided in accordance with some embodiments of the present invention. Referring to fig. 5, the constructing apparatus 500 of the heterogeneous social network includes: a social group determination module 510, a target user determination module 520, and a heterogeneous social group construction module 530. The social group determining module is used for determining a plurality of social groups corresponding to first recommended behaviors of the seed users on the target content based on the first recommended behaviors, wherein the target content comprises a content tag; the target user determination module is used for determining a target user performing a second recommendation action on the target content in the plurality of social groups; the heterogeneous social group building module is used for building a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
In some embodiments of the present invention, based on the above solution, the constructing apparatus of a heterogeneous social network further includes: the recommendation behavior acquisition unit is used for acquiring a first recommendation behavior and a second recommendation behavior, wherein the first recommendation behavior comprises a sharing behavior, and the second recommendation behavior comprises an evaluation behavior.
Fig. 6 illustrates a schematic block diagram of a group recommendation device provided in accordance with some embodiments of the present invention. Referring to fig. 6, the group recommendation apparatus 600 includes: a historical recommendation list acquisition module 610, a group recommendation list determination module 620, a recommendation ranking determination module 630, and a single person recommendation module 640. The history recommendation list acquisition module is used for acquiring a history recommendation list of each user in the heterogeneous social group; the group recommendation list determining module is used for determining a group recommendation list of each user based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user; the recommendation sequencing determination module is used for performing recommendation sequencing on the recommended content in each group recommendation list based on the historical recommendation behaviors of each user in the heterogeneous social group; and the single recommendation module is used for recommending contents to each user in the heterogeneous social group based on the recommendation sequencing result.
In some embodiments of the present invention, based on the above scheme, the recommendation ranking determining module includes: the recommendation time determining unit is used for determining the recommendation times and time of each recommended content in the group recommendation list based on the historical recommendation behaviors of each user in the heterogeneous social group; and the recommended content sequencing unit is used for performing recommendation sequencing on the recommended content in each group recommendation list based on the recommended content recommendation times and time.
In some embodiments of the present invention, based on the above scheme, the recommended content ranking unit includes: the user recommendation heat determining unit is used for determining the user recommendation heat of the recommended content in the heterogeneous social group based on the recommended times of the recommended content; the recommendation sequence determining unit is used for determining the recommendation sequence of the recommended content in the heterogeneous social group based on the recommended time of the recommended content; and the recommendation sequencing determining unit is used for determining the recommendation sequencing of each recommended content in the heterogeneous social group based on the user recommendation heat and the recommendation book sequence.
In some embodiments of the present invention, based on the above scheme, the group recommendation list determining module includes: the history recommendation list filtering unit is used for filtering the history recommendation list of each user in the heterogeneous social group based on the content label corresponding to the heterogeneous social group; and the group recommendation list determining unit is used for determining the group recommendation list of each user based on the filtering result.
Fig. 7 is a schematic block diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 7, the electronic device 700 includes, but is not limited to: a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709, a processor 710, a power supply 711, and the like. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 7 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
The memory 709 stores therein a computer program, and when the computer program is executed by the processor 710, the following process can be implemented: determining a plurality of social groups corresponding to first recommended behaviors of the seed user on the target content based on the first recommended behaviors, wherein the target content comprises a content tag; determining a target user performing a second recommendation action on the target content in the plurality of social groups; and constructing a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
Optionally, when the computer program is executed by the processor 710, the first recommended behavior comprises a sharing behavior and the second recommended behavior comprises an evaluation behavior.
Optionally, the computer program can implement the following procedures when executed by the processor 710: acquiring a historical recommendation list of each user in the heterogeneous social group; determining a group recommendation list of each user based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user; recommending and sequencing recommended contents in each group recommendation list based on historical recommendation behaviors of each user in the heterogeneous social group; and respectively recommending contents to each user in the heterogeneous social group based on the result of the recommendation sequencing.
Optionally, when executed by the processor 710, the computer program performs recommendation ranking on recommended content in each group recommendation list based on historical recommendation behaviors of each user in the heterogeneous social group, including: determining the recommended times and time of each recommended content in the group recommendation list based on the historical recommendation behaviors of each user in the heterogeneous social group; and recommending and sequencing the recommended contents in each group recommendation list based on the recommended content recommending times and time.
Optionally, the computer program, when executed by the processor 710, ranks the recommended contents in the respective group recommendation lists based on the number of times and the time that the recommended contents are recommended, including: determining the user recommendation heat of the recommended content in the heterogeneous social group based on the recommended times of the recommended content; determining a recommendation sequence of the recommended content in the heterogeneous social group based on the time when the recommended content is recommended; and determining the recommendation ranking of each recommended content in the heterogeneous social group based on the recommendation popularity and the recommendation book order of the user.
Optionally, when executed by the processor 710, the computer program determines the group recommendation list of each user based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each user, including: filtering a historical recommendation list of each user in the heterogeneous social group based on the content tags corresponding to the heterogeneous social group; based on the results of the filtering, a group recommendation list for each user is determined.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 701 may be used for receiving and sending signals during a message transmission and reception process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 710; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 701 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 701 may also communicate with a network and other devices through a wireless communication system.
The electronic device provides wireless broadband internet access to the user via the network module 702, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.
The audio output unit 703 may convert audio data received by the radio frequency unit 701 or the network module 702 or stored in the memory 709 into an audio signal and output as sound. Also, the audio output unit 703 may also provide audio output related to a specific function performed by the electronic apparatus 700 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 703 includes a speaker, a buzzer, a receiver, and the like.
The input unit 704 is used to receive audio or video signals. The input Unit 704 may include a Graphics Processing Unit (GPU) 7041 and a microphone 7042, and the Graphics processor 7041 processes image data of a still picture or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 706. The image frames processed by the graphic processor 7041 may be stored in the memory 709 (or other storage medium) or transmitted via the radio unit 701 or the network module 702. The microphone 7042 may receive sounds and may be capable of processing such sounds into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 701 in case of a phone call mode.
The electronic device 700 also includes at least one sensor 705, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 7061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 7061 and/or a backlight when the electronic device 700 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 705 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.
The display unit 706 is used to display information input by the user or information provided to the user. The Display unit 706 may include a Display panel 7061, and the Display panel 7061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 707 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 707 includes a touch panel 7071 and other input devices 7072. The touch panel 7071, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 7071 (e.g., operations by a user on or near the touch panel 7071 using a finger, a stylus, or any other suitable object or attachment). The touch panel 7071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 710, receives a command from the processor 710, and executes the command. In addition, the touch panel 7071 can be implemented by various types such as resistive, capacitive, infrared, and surface acoustic wave. The user input unit 707 may include other input devices 7072 in addition to the touch panel 7071. In particular, the other input devices 7072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described herein again.
Further, the touch panel 7071 may be overlaid on the display panel 7061, and when the touch panel 7071 detects a touch operation on or near the touch panel 7071, the touch operation is transmitted to the processor 710 to determine the type of the touch event, and then the processor 710 provides a corresponding visual output on the display panel 7061 according to the type of the touch event. Although the touch panel 7071 and the display panel 7061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 7071 and the display panel 7061 may be integrated to implement the input and output functions of the electronic device, which is not limited herein.
The interface unit 708 is an interface for connecting an external device to the electronic apparatus 700. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 708 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic apparatus 700 or may be used to transmit data between the electronic apparatus 700 and the external device.
The memory 709 may be used to store software programs as well as various data. The memory 709 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 709 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 710 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 709 and calling data stored in the memory 709, thereby monitoring the whole electronic device. Processor 710 may include one or more processing units; preferably, the processor 710 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 710.
The electronic device 700 may also include a power supply 711 (e.g., a battery) for providing power to the various components, and preferably, the power supply 711 may be logically coupled to the processor 710 via a power management system, such that functions of managing charging, discharging, and power consumption may be performed via the power management system.
In addition, the electronic device 700 includes some functional modules that are not shown, and are not described in detail herein.
The electronic device in the embodiment of the application can implement each process of the aforementioned heterogeneous social network construction method or group recommendation method, and achieve the same effect and function, which are not repeated here.
Further, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program implements each process of the aforementioned method for constructing a heterogeneous social network or the group recommendation method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the above-mentioned embodiment of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A group recommendation method, comprising:
acquiring a historical recommendation list of each user in the heterogeneous social group;
determining a group recommendation list of each user based on the content tags corresponding to the heterogeneous social group and the historical recommendation lists of each user;
recommending and sequencing recommended contents in each group recommendation list based on historical recommendation behaviors of each user in the heterogeneous social group;
based on the result of the recommendation sequencing, respectively recommending content to each user in the heterogeneous social group;
before the obtaining of the historical recommendation list of each user in the heterogeneous social group, the method includes: determining a plurality of social groups corresponding to first recommended behaviors of a seed user on target content based on the first recommended behaviors, wherein the target content comprises a content tag;
determining a target user performing a second recommended action on the target content in the plurality of social groups;
and constructing a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
2. The group recommendation method according to claim 1, wherein the performing recommendation ranking on recommended content in each group recommendation list based on the historical recommendation behavior of each user in the heterogeneous social group comprises:
determining the number of times and time that each recommended content in the group recommendation list is recommended based on the historical recommendation behaviors of each user in the heterogeneous social group;
and recommending and sequencing the recommended contents in each group recommendation list based on the recommended content recommending times and time.
3. The group recommendation method according to claim 2, wherein said recommending and sorting the recommended contents in each of the group recommendation lists based on the recommended contents recommending times and times comprises:
determining a user recommendation popularity of the recommended content in the heterogeneous social group based on the recommended number of times of the recommended content;
determining a recommendation order of the recommended content in the heterogeneous social group based on a time when the recommended content is recommended;
and determining the recommendation ranking of each recommended content in the heterogeneous social group based on the user recommendation heat and the recommendation sequence.
4. The group recommendation method of claim 1, wherein determining the group recommendation list of each of the users based on the content tags corresponding to the heterogeneous social groups and the historical recommendation lists of each of the users comprises:
filtering the historical recommendation list of each user in the heterogeneous social group based on the content tag corresponding to the heterogeneous social group;
based on the results of the filtering, a group recommendation list for each of the users is determined.
5. The group recommendation method according to claim 1, wherein the first recommended behavior comprises a sharing behavior and the second recommended behavior comprises an evaluation behavior.
6. A group recommendation device, comprising:
the history recommendation list acquisition module is used for acquiring a history recommendation list of each user in the heterogeneous social group;
a group recommendation list determining module, configured to determine a group recommendation list of each user based on the content tag corresponding to the heterogeneous social group and the historical recommendation list of each user;
the recommendation sequencing determination module is used for performing recommendation sequencing on the recommended content in each group recommendation list based on the historical recommendation behaviors of the users in the heterogeneous social group;
the single recommendation module is used for recommending contents to each user in the heterogeneous social group based on the recommendation sequencing result;
further comprising:
the social group determination module is used for determining a plurality of social groups corresponding to first recommended behaviors of a seed user on target content based on the first recommended behaviors, wherein the target content comprises a content tag;
the target user determination module is used for determining a target user performing second recommendation behavior on the target content in the plurality of social groups;
and the heterogeneous social group building module is used for building a heterogeneous social group corresponding to the content tag based on the seed user and the target user.
7. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the group recommendation method as claimed in any one of claims 1 to 5.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the group recommendation method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910478639.3A CN110378798B (en) | 2019-06-03 | 2019-06-03 | Heterogeneous social network construction method, group recommendation method, device and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910478639.3A CN110378798B (en) | 2019-06-03 | 2019-06-03 | Heterogeneous social network construction method, group recommendation method, device and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110378798A CN110378798A (en) | 2019-10-25 |
| CN110378798B true CN110378798B (en) | 2022-04-01 |
Family
ID=68249765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910478639.3A Active CN110378798B (en) | 2019-06-03 | 2019-06-03 | Heterogeneous social network construction method, group recommendation method, device and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110378798B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111581488B (en) * | 2020-05-14 | 2023-08-04 | 上海商汤智能科技有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN116484115A (en) * | 2023-05-17 | 2023-07-25 | 北京淘友天下技术有限公司 | Friend-making recommendation system and method with intelligent analysis function |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3987934B2 (en) * | 2003-11-12 | 2007-10-10 | 国立大学法人大阪大学 | Document processing apparatus, method and program for summarizing user evaluation comments using social relationships |
| US7483998B2 (en) * | 2003-11-14 | 2009-01-27 | Alcatel Lucent | Software configurable cluster-based router using heterogeneous nodes as cluster nodes |
| CN104702488B (en) * | 2013-12-10 | 2019-03-05 | 上海掌门科技有限公司 | Friend recommendation system and method |
| CN104660496B (en) * | 2015-01-28 | 2018-09-25 | 腾讯科技（深圳）有限公司 | A kind of information processing method, client and server |
| CN105447170B (en) * | 2015-12-07 | 2019-10-29 | 联想(北京)有限公司 | A kind of information processing method and electronic equipment |
| CN107436816B (en) * | 2016-05-27 | 2020-07-14 | 腾讯科技（深圳）有限公司 | Message delivery control method, system and terminal |
| CN107563898A (en) * | 2017-09-26 | 2018-01-09 | 浪潮软件集团有限公司 | Social circle recommendation method and device |
| CN108446311A (en) * | 2018-02-06 | 2018-08-24 | 微梦创科网络科技（中国）有限公司 | A kind of APP recommendation method and devices based on social networks |
| CN112052404B (en) * | 2020-09-23 | 2023-08-15 | 西安交通大学 | Group discovery method, system, equipment and medium of multi-source heterogeneous relation network |
| CN113515697A (en) * | 2021-05-27 | 2021-10-19 | 武汉理工大学 | Group dynamic tour route recommendation method and system based on multiple intentions of user |
-
2019
- 2019-06-03 CN CN201910478639.3A patent/CN110378798B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110378798A (en) | 2019-10-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108255382B (en) | Method and device for recommending floating menu content | |
| CN111010332A (en) | Group chat method and electronic equipment | |
| CN110458655B (en) | Shop information recommendation method and mobile terminal | |
| CN108616448B (en) | Information sharing path recommendation method and mobile terminal | |
| CN108494665B (en) | Group message display method and mobile terminal | |
| CN108984066B (en) | Application icon display method and mobile terminal | |
| CN110866038A (en) | Information recommendation method and terminal equipment | |
| CN111444425B (en) | Information pushing method, electronic equipment and medium | |
| CN112001741A (en) | Method and device for constructing multitask processing model, electronic equipment and storage medium | |
| CN107765954B (en) | Application icon updating method, mobile terminal and server | |
| CN108540649B (en) | Content display method and mobile terminal | |
| CN111125307A (en) | Chat record query method and electronic equipment | |
| CN108391253B (en) | application program recommendation method and mobile terminal | |
| CN108196781B (en) | Interface display method and mobile terminal | |
| CN107992615B (en) | Website recommendation method, server and terminal | |
| CN110378798B (en) | Heterogeneous social network construction method, group recommendation method, device and equipment | |
| CN111324247A (en) | Information display method and electronic equipment | |
| CN110908751B (en) | Information display and collection method and device, electronic equipment and medium | |
| CN110045892B (en) | Display method and terminal equipment | |
| CN109510897B (en) | Expression picture management method and mobile terminal | |
| CN111026955A (en) | Application program recommendation method and electronic equipment | |
| CN110851042A (en) | Interface display method and electronic equipment | |
| CN107844203B (en) | Input method candidate word recommendation method and mobile terminal | |
| CN111190528A (en) | Brush display method, electronic equipment and storage medium | |
| CN110928616A (en) | Shortcut icon management method and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |