CN111148185A - Method and device for establishing user relationship - Google Patents
Method and device for establishing user relationship Download PDFInfo
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- CN111148185A CN111148185A CN201911269509.5A CN201911269509A CN111148185A CN 111148185 A CN111148185 A CN 111148185A CN 201911269509 A CN201911269509 A CN 201911269509A CN 111148185 A CN111148185 A CN 111148185A
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Abstract
The application relates to a method and a device for establishing a user relationship, wherein the method comprises the following steps: acquiring information of each user device and an information list of network hotspots scanned by each user device; according to the information of each user device and the information list of the network hotspots scanned by each user device, counting to obtain a pairing list of each user device and the scanned network hotspots; determining the similarity of the pairing lists between different user equipment, and determining a first relation between the user equipment according to the similarity. The method and the device are used for fully mining and establishing the user relationship based on ubiquitous network data.
Description
Technical Field
The present application relates to the field of network technologies, and in particular, to a method and an apparatus for establishing a user relationship.
Background
With the development of mobile internet, intelligent devices have become one of essential products in people's lives. However, the intelligent device needs a large amount of traffic to support, and the wireless network becomes a bridge for interconnection of the intelligent device, and with wireless network technologies such as a network hotspot (WiFi), people can communicate with each other through the intelligent device, including family, work partners, friends, and the like. Meanwhile, with the development of technology, wireless network signals have spread throughout most public places and homes in large, medium and small cities.
Relationships among users can be constructed through network interaction so as to realize accurate recommendation of products. Most of the existing accurate recommendation is performed based on a strong user relationship, namely, a certain relationship exists between users is known, and then accurate recommendation is performed according to the distance of the relationship between the users.
However, strong user relationships exist only in some products with social functionality, and strong user relationships do not exist in most products. Moreover, the social relationship between users provided by most products is generally a relationship formed by active actions of the users, for example, the relationship between the users is obtained by active sharing actions of the users.
Therefore, how to fully mine and establish user relationships based on ubiquitous network data is a problem to be solved.
Disclosure of Invention
The application provides a method and a device for establishing a user relationship, which are used for fully mining and establishing the user relationship based on ubiquitous network data.
In a first aspect, an embodiment of the present application provides a method for establishing a user relationship, including:
acquiring information of each user device and an information list of network hotspots scanned by each user device;
according to the information of each user device and the information list of the network hotspots scanned by each user device, counting to obtain a pairing list of each user device and the scanned network hotspots;
determining the similarity of the pairing lists between different user equipment, and determining a first relation between the user equipment according to the similarity.
Optionally, acquiring network data includes:
and acquiring a behavior log of each user device, and extracting information of each user device from the behavior log, wherein each user device scans a physical address list and a scanning time period of each network hotspot.
Optionally, obtaining a pairing list of each user equipment and the scanned network hotspot by statistics according to the information of each user equipment and the information list of the network hotspot scanned by each user equipment, includes:
extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment;
converting the extracted physical address list of each user device into a form of pairing the identifier of the user device and the physical address of the network hotspot to obtain a pairing list of the identifier of the user device and the physical address of the network hotspot.
Optionally, determining similarity of the pairing list between different user equipments includes:
respectively carrying out the following processing on each user equipment: inputting the identifier of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model;
and calculating the similarity between the user equipment according to the vector of each user equipment.
Optionally, calculating a similarity between the user equipments according to the vector of each user equipment includes:
and for any two pieces of user equipment, calculating the Euclidean distance between the two pieces of user equipment according to the vectors of the two pieces of user equipment, and determining the similarity between the two pieces of user equipment according to the Euclidean distance.
Optionally, the first relationship is used to indicate whether two of the user devices are present at the same time and at the same location;
after determining the first relationship between the user equipments according to the similarity, the method further includes:
for any two user equipment, after the two user equipment are determined to be present at the same place at the same time according to the first relation between the two user equipment, the second relation between the two user equipment is determined according to the respective user description information of the two user equipment, and the second relation is the specific interpersonal relation between the two user equipment present at the same place at the same time.
In a second aspect, an embodiment of the present application provides an apparatus for establishing a user relationship, including:
the acquisition module is used for acquiring information of each user device and an information list of network hotspots scanned by each user device;
the statistical module is used for obtaining a pairing list of each user equipment and the scanned network hotspots through statistics according to the information of each user equipment and the information list of the network hotspots scanned by each user equipment;
and the processing module is used for determining the similarity of the pairing lists between different user equipment and determining a first relationship between the user equipment according to the similarity.
Optionally, the obtaining module is specifically configured to:
and acquiring a behavior log of each user device, and extracting information of each user device from the behavior log, wherein each user device scans a physical address list and a scanning time period of each network hotspot.
Optionally, the statistical module is specifically configured to:
extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment;
converting the extracted physical address list of each user device into a form of pairing the identifier of the user device and the physical address of the network hotspot to obtain a pairing list of the identifier of the user device and the physical address of the network hotspot.
Optionally, the processing module is specifically configured to:
respectively carrying out the following processing on each user equipment: inputting the identifier of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model;
and calculating the similarity between the user equipment according to the vector of each user equipment.
Optionally, the processing module is specifically configured to:
and for any two pieces of user equipment, calculating the Euclidean distance between the two pieces of user equipment according to the vectors of the two pieces of user equipment, and determining the similarity between the two pieces of user equipment according to the Euclidean distance.
Optionally, the first relationship is whether the two user equipments are present at the same location at the same time;
the processing module is further configured to:
for any two user equipment, after the two user equipment are determined to be present at the same place at the same time according to the first relation between the two user equipment, the second relation between the two user equipment is determined according to the respective user description information of the two user equipment, and the second relation is the specific interpersonal relation between the two user equipment present at the same place at the same time.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages: according to the method provided by the embodiment of the application, the similarity between the information of the network hotspots corresponding to the user equipment is determined by utilizing the information of the user equipment in the network data and the information list of the network hotspots scanned by the user equipment, and the first relation between the user equipment is determined according to the similarity, so that the user relation can be fully mined and established based on the ubiquitous network data, and accurate recommendation service can be provided according to the mined user relation.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic flow chart illustrating a method for establishing a user relationship in an embodiment of the present application;
FIG. 2 is a schematic structural diagram of an apparatus for establishing a user relationship in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
The embodiment of the application provides a method for establishing a user relationship, and the method can be applied to any electronic equipment. The main idea is as follows: if two pieces of user equipment are connected to the physical (mac) address of the same network hotspot at the same time, an association relationship necessarily exists between the two pieces of user equipment, for example, the user equipment a and the user equipment B are connected to the physical address of the same network hotspot often in working hours, and according to the user description information of the user equipment a and the user description information of the user equipment B, the two users can be judged to be in a co-worker relationship, so that the weak user relationship is improved to be the strong user relationship.
As shown in fig. 1, the specific process of establishing the user relationship is as follows:
In a specific embodiment, a behavior log of each user equipment is obtained, and network data is extracted from the behavior log, where the network data includes: the information of each user equipment, the physical address list and the scanning time period of each network hotspot scanned by each user equipment.
The network data is obtained mainly by collecting legal behavior logs authorized by users in each application program. For example, the behavior log includes viewing behaviors of the user at each client of a certain video playing platform, data which can collect WiFi information connected by the user, such as stars, comment behaviors, and the like, data coverage time can be from one month to half a year, and the more network data is collected, the more accurate the user relationship is identified subsequently.
In a specific embodiment, because the user behavior logs are more and contain more interference data, after the network data are extracted from the behavior logs, the network data are cleaned to a certain extent, including removing data with an incorrect format, such as null logs, cheating flow logs, abnormal data values and the like, from the network data, and the cleaned network data are output to a specified data storage path according to a given data format.
The information collected by the client is dispersed, so that the behavior data of different clients of the same user can be merged, the data of the low-frequency user and the data of the abnormal user are filtered from the cleaned network data, the users mainly cheat, then a physical address list of the network hotspots scanned by the users in the same time is obtained according to a given data format, and the information such as the signal intensity of the connected network hotspots can be marked in the list.
And step 102, counting to obtain a pairing list of each user equipment and the scanned network hotspots according to the information of each user equipment and the information list of the network hotspots scanned by each user equipment.
In a specific embodiment, the specific process of obtaining the pairing list of each user equipment and the scanned network hotspot by statistics is as follows: extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment; and converting the extracted physical address list corresponding to each user equipment into a form of pairing the identifier of the user equipment and the physical address of the network hotspot to obtain a pairing list of the identifier of the user equipment and the physical address of the network hotspot.
In the physical address list of the network hotspot corresponding to the user equipment, the physical addresses of the network hotspots in the list are sorted according to the strength of the network hotspot signal strength, and the stronger the signal is, the closer the user equipment is to the network hotspot is, the sort in the physical address list of the network hotspot of the user equipment can be used as the distance measurement between the user equipment and the network hotspot. The physical address list of the network hotspot corresponding to the user equipment may be represented as:
identification # mac1 of user equipment: mac 2: mac 3: mac 4: mac5.
When the network address list of the user equipment is converted, inserting the identification of the user equipment into the physical address list of the network hotspot of the user equipment to obtain a pairing list of the identification of the user equipment and the physical address of the network hotspot. The pairing list may be expressed as:
identity of mac1 user device identity of mac2 user device identity of mac3 user device identity of mac4 user device identity of mac5.
In a specific embodiment, the following processing is performed for each user equipment: inputting the identification of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model; and calculating the similarity between the user equipment according to the vector of each user equipment.
Wherein the first relationship is used to indicate whether two user equipments are present at the same time and at the same location.
Specifically, a vector of the user equipment is obtained by using an open-source vectorization model word2 vec. After the vectorization model word2vec is trained, the vector of the user equipment can be directly output under the condition that the pairing list of the identification of the user equipment and the physical address of the network hotspot is input, so that the similarity between the user equipment can be obtained under the condition of no damage.
According to data in a given format, an open source word2vec is realized by using a distributed big data processing tool spark to train a model. The vector of the user equipment output by the vectorization model is represented as: an identification of a user device [0.83838,0.18998, 0.88383783.... 0.193499,0.9438473 ].
Specifically, the vectorization model outputs a vector of each user equipment, associates the two user equipments together in a vector retrieval mode, and calculates the similarity between the two user equipments, thereby identifying the relationship between the two user equipments.
In order to reduce retrieval time, the physical address of the network hotspot is used as a bucket dividing basis of the device vector, every two obtained buckets are paired, and the similarity of two user devices is calculated. Because the network hotspots have spatial fixity, the number of users which can be accessed by the physical addresses of the same network hotspot (some public network hotspots are removed) is limited, the physical addresses of the network hotspots are used as the bucket dividing basis, and after the bucket dividing processing is carried out on the vector of the user equipment, the vector retrieval range is greatly reduced, and the retrieval time is greatly reduced.
In a specific embodiment, after determining the vector of each ue, for any two ues, the euclidean distance between the two ues is calculated according to the vectors of the two ues, and the similarity between the two ues is determined according to the euclidean distance.
For example, in each retrieval range obtained after the bucket dividing processing, an open source retrieval tool is used, for example, annoy is used for retrieving and calculating the similarity between user equipment, and the relationship between the user equipment which often appears under the physical address of the same network hotspot is identified through the similarity between the user equipment.
In a specific embodiment, after determining the first relationship between the two pieces of user equipment, for any two pieces of user equipment, after determining that the two pieces of user equipment appear at the same place at the same time according to the first relationship between the two pieces of user equipment, determining a second relationship between the two pieces of user equipment according to respective user description information of the two pieces of user equipment, where the second relationship is a specific interpersonal relationship between the two pieces of user equipment appearing at the same place at the same time.
The user description information of the user equipment refers to portrait information of a user using the user equipment, and includes information such as age, sex, home address and the like, and the partial data is key data for determining a specific interpersonal relationship after recognizing that two user equipments appear at the same time and the same place. For example, assuming that home addresses or working places of the user a and the user B are in the same place, if the vectors of the user devices of the user a and the user B with similarity higher than a set value correspond to time periods of off-duty time and off-day time, it can be inferred that the two users have a high probability of being in a family relationship; if the similarity of the vectors of the user devices of the user A and the user B is higher than the set value, the corresponding time period is the working time of the working day, the fact that the two users have a colleague relationship with a high probability can be inferred, and the fact that the two users have a relatively close relation can be inferred as the vectors frequently appear in the physical address coverage range of the same network hotspot.
In the embodiment of the application, the similarity between the information of the network hotspots corresponding to the user equipment is determined by utilizing the information of the user equipment in the network data and the information list of the network hotspots scanned by the user equipment, and the first relation between the user equipment is determined according to the similarity, so that the user relation can be fully mined and established based on the ubiquitous network data, and accurate recommendation service can be provided according to the mined user relation. According to the embodiment of the application, the relation between users can be mined by utilizing the limitation of the physical address space coverage range of the network hotspot and the frequently-accessed network hotspot information reported by the user equipment without active sharing and other actions.
Based on the same concept, an apparatus for establishing a user relationship is provided in the embodiments of the present application, and specific implementation of the apparatus may refer to the description of the method embodiment, and repeated details are not repeated, as shown in fig. 2, the apparatus mainly includes:
an obtaining module 201, configured to obtain information of each user equipment and an information list of network hotspots scanned by each user equipment;
a counting module 202, configured to count to obtain a pairing list between each user equipment and a scanned network hotspot according to information of each user equipment and an information list of each scanned network hotspot of each user equipment;
the processing module 203 is configured to determine similarity of the pairing lists between different user equipments, and determine a first relationship between the user equipments according to the similarity.
Optionally, the obtaining module 201 is specifically configured to:
the method comprises the steps of obtaining a behavior log of each user device, extracting information of each user device from the behavior log, and obtaining a physical address list and a scanning time period of each network hotspot scanned by each user device.
Optionally, the statistics module 202 is specifically configured to:
extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment;
converting the extracted physical address list of each user device into a form of pairing the identifier of the user device and the physical address of the network hotspot to obtain a pairing list of the identifier of the user device and the physical address of the network hotspot.
Optionally, the processing module 203 is specifically configured to:
respectively carrying out the following processing on each user equipment: inputting the identifier of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model;
and calculating the similarity between the user equipment according to the vector of each user equipment.
Optionally, the processing module 203 is specifically configured to:
and for any two pieces of user equipment, calculating the Euclidean distance between the two pieces of user equipment according to the vectors of the two pieces of user equipment, and determining the similarity between the two pieces of user equipment according to the Euclidean distance.
Optionally, the first relationship is used to indicate whether two of the user devices are present at the same time and at the same location;
the processing module 203 is further configured to:
for any two user equipment, after the two user equipment are determined to be present at the same place at the same time according to the first relation between the two user equipment, the second relation between the two user equipment is determined according to the respective user description information of the two user equipment, and the second relation is the specific interpersonal relation between the two user equipment present at the same place at the same time.
Based on the same concept, an embodiment of the present application further provides an electronic device, as shown in fig. 3, the electronic device mainly includes: a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302 and the memory 303 communicate with each other via the communication bus 304. Wherein, the memory 303 stores programs that can be executed by the processor 301, and the processor 301 executes the programs stored in the memory 303, implementing the following steps: acquiring information of each user device and an information list of network hotspots scanned by each user device; according to the information of each user device and the information list of the network hotspots scanned by each user device, counting to obtain a pairing list of each user device and the scanned network hotspots; determining the similarity of the pairing lists between different user equipment, and determining a first relation between the user equipment according to the similarity.
The communication bus 304 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 3, but this does not mean only one bus or one type of bus.
The communication interface 302 is used for communication between the above-described electronic apparatus and other apparatuses.
The Memory 303 may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Alternatively, the memory may be at least one memory device located remotely from the processor 301.
The Processor 301 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like, and may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components.
In yet another embodiment of the present application, a computer-readable storage medium is further provided, in which a computer program is stored, and when the computer program runs on a computer, the computer is caused to execute the method for establishing a user relationship described in the above embodiment.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wirelessly (e.g., infrared, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The available media may be magnetic media (e.g., floppy disks, hard disks, tapes, etc.), optical media (e.g., DVDs), or semiconductor media (e.g., solid state drives), among others.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (12)
1. A method of establishing user relationships, comprising:
acquiring information of each user device and an information list of network hotspots scanned by each user device;
according to the information of each user device and the information list of the network hotspots scanned by each user device, counting to obtain a pairing list of each user device and the scanned network hotspots;
determining the similarity of the pairing lists between different user equipment, and determining a first relation between the user equipment according to the similarity.
2. The method according to claim 1, wherein obtaining information of each user device and an information list of network hotspots scanned by each user device comprises:
and acquiring a behavior log of each user device, and extracting information of each user device from the behavior log, wherein each user device scans a physical address list and a scanning time period of each network hotspot.
3. The method according to claim 2, wherein obtaining a pairing list of each user equipment and the scanned network hotspot by statistics according to information of each user equipment and an information list of each scanned network hotspot of each user equipment comprises:
extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment;
converting the extracted physical address list of each user device into a form of pairing the identifier of the user device and the physical address of the network hotspot to obtain a pairing list of the identifier of the user device and the physical address of the network hotspot.
4. The method of claim 3, wherein determining similarity of the pairing list between different user devices comprises:
respectively carrying out the following processing on each user equipment: inputting the identifier of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model;
and calculating the similarity between the user equipment according to the vector of each user equipment.
5. The method of claim 4, wherein calculating the similarity between the UE according to the vector of each UE comprises:
and for any two pieces of user equipment, calculating the Euclidean distance between the two pieces of user equipment according to the vectors of the two pieces of user equipment, and determining the similarity between the two pieces of user equipment according to the Euclidean distance.
6. The method according to any of claims 1 to 5, wherein the first relationship is used to indicate whether two user equipments are present at the same place at the same time;
after determining the first relationship between the user equipments according to the similarity, the method further includes:
for any two user equipment, after the two user equipment are determined to be present at the same place at the same time according to the first relation between the two user equipment, the second relation between the two user equipment is determined according to the respective user description information of the two user equipment, and the second relation is the specific interpersonal relation between the two user equipment present at the same place at the same time.
7. An apparatus for establishing user relationships, comprising:
the acquisition module is used for acquiring information of each user device and an information list of network hotspots scanned by each user device;
the statistical module is used for obtaining a pairing list of each user equipment and the scanned network hotspots through statistics according to the information of each user equipment and the information list of the network hotspots scanned by each user equipment;
and the processing module is used for determining the similarity of the pairing lists between different user equipment and determining a first relationship between the user equipment according to the similarity.
8. The apparatus for establishing a user relationship according to claim 7, wherein the obtaining module is specifically configured to:
and acquiring a behavior log of each user device, and extracting information of each user device from the behavior log, wherein each user device scans a physical address list and a scanning time period of each network hotspot.
9. The apparatus for establishing a user relationship according to claim 8, wherein the statistics module is specifically configured to:
extracting a physical address list of the network hotspots scanned by each user equipment in the same scanning time period from an information list of the network hotspots scanned by each user equipment;
converting the extracted physical address list of each user device into a form of pairing the identifier of the user device and the physical address of the network hotspot to obtain a pairing list of the identifier of the user device and the physical address of the network hotspot.
10. The apparatus for establishing a user relationship according to claim 9, wherein the processing module is specifically configured to:
respectively carrying out the following processing on each user equipment: inputting the identifier of the user equipment and a pairing list of the physical address of the network hotspot into a vectorization model to obtain a vector of the user equipment output by the vectorization model;
and calculating the similarity between the user equipment according to the vector of each user equipment.
11. The apparatus for establishing a user relationship according to claim 10, wherein the processing module is specifically configured to:
and for any two pieces of user equipment, calculating the Euclidean distance between the two pieces of user equipment according to the vectors of the two pieces of user equipment, and determining the similarity between the two pieces of user equipment according to the Euclidean distance.
12. The apparatus for establishing a user relationship according to any one of claims 7 to 11, wherein the first relationship is used to indicate whether two user equipments are present at the same place at the same time;
the processing module is further configured to:
for any two user equipment, after the two user equipment are determined to be present at the same place at the same time according to the first relation between the two user equipment, the second relation between the two user equipment is determined according to the respective user description information of the two user equipment, and the second relation is the specific interpersonal relation between the two user equipment present at the same place at the same time.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112866910A (en) * | 2021-01-08 | 2021-05-28 | 腾讯科技（深圳）有限公司 | Method, device and system for recommending starting point route and computer storage medium |
| CN113840392A (en) * | 2021-09-17 | 2021-12-24 | 杭州云深科技有限公司 | Method and device for determining user intimacy, computer equipment and storage medium |
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Application publication date: 20200512 |