CN108764951B - User similarity obtaining method and device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a user similarity obtaining method and device based on a user movement track, equipment and a storage medium. The user similarity obtaining method based on the user movement track comprises the following steps: obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information; obtaining time similarity according to each piece of first time information and each piece of second time information; and obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity. By adopting the method and the device, the accuracy of the obtained user similarity can be improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method, a device, equipment and a storage medium for obtaining user similarity.
Background
In the operation process of a telecommunication operator, when a communication number used by a certain user changes, the related records of new and old numbers of the user are often required to be merged. How to identify whether the two numbers belong to the same user, that is, how to judge whether a new network access user and an old network access user are the same user, becomes a core technical problem in the telecommunication operation process.
In the prior art, it is generally determined whether two users are the same user by calculating the similarity between the two users. Specifically, when a new network-accessing user is detected, automatically calculating user similarity between all old network-accessing users in the communication network and the new network-accessing user, and when the user similarity which is larger than a preset threshold value is detected to exist in the calculated user similarity, considering that the old network-accessing user similar to the new network-accessing user exists in the communication network, so that the new network-accessing user is judged to be a re-network-accessing user; and then, judging that the old network access user with the maximum user similarity and the new network access user are the same user, and merging the corresponding related records of the old network access user and the new network access user. The existing method for calculating the user similarity between the new network access user and the old network access user is generally obtained by calculating the similarity of user communication records, and the user similarity is obtained according to a single basis and has low accuracy.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for obtaining user similarity, which can improve the accuracy of the obtained user similarity.
The embodiment of the invention provides a user similarity obtaining method based on a user moving track, which specifically comprises the following steps:
obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information;
obtaining time similarity according to each piece of first time information and each piece of second time information;
and obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity.
Further, the first user movement track comprises at least one first track point; the second user moving track comprises at least one second track point; each piece of first time information and each piece of first track point have one-to-one correspondence; and each piece of second time information and each piece of second track point have one-to-one correspondence.
Further, the obtaining the time similarity according to each piece of the first time information and each piece of the second time information specifically includes:
according to each first time information Ti(u) each of the second time information Tj(v) And a preset time similarity calculation model
Calculating to obtain the time similarity COL; wherein u represents the first user; v represents the second user; n (u) is the total number of first track points in the first user movement track; n (v) is the total number of second track points in the second user moving track; Δ T is a preset time precision; l isi(u) representing an ith first track point in the first user movement track; l isj(v) Representing a jth second track point in the second user movement track; delta (L)i(u),Lj(v) Is the coincidence degree of the ith first track point in the first user moving track and the jth second track point in the second user moving track.
Further, the obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity specifically includes:
calculating a model according to the first user movement track, the second user movement track and the preset track similarity
Calculating to obtain the track similarity DLCSS(ii) a Wherein LCSS (u, v) represents the longest common subsequence between the first user movement trajectory and the second user movement trajectory; len (a)uRepresenting the total number of first track points in the first user moving track; len (a)vRepresenting the total number of second track points in the second user moving track;
according to the track similarity DLCSSAnd obtaining the user similarity according to the time similarity.
Further, the similarity D according to the trackLCSSAnd the time similarity, obtaining the user similarity, specifically comprising:
according to the track similarity DLCSSThe time similarity COL and a user similarity calculation model sim (u, v) ═ DLCSS*CAnd OL, calculating to obtain the user similarity sim (u, v).
Further, the first time information is time information when the first user arrives at the corresponding first track point; and the second time information is the time information when the second user arrives at the corresponding second track point.
Further, after obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity, the method further includes:
judging whether the user similarity is greater than a preset threshold value or not;
if yes, the first user and the second user are judged to be the same user;
if not, determining that the first user and the second user are not the same user.
Correspondingly, the embodiment of the present invention further provides a device for obtaining user similarity based on a user movement track, which specifically includes:
the user movement track obtaining module is used for obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information;
a time similarity obtaining module, configured to obtain a time similarity according to each piece of the first time information and each piece of the second time information; and the number of the first and second groups,
and the user similarity obtaining module is used for obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity.
An embodiment of the present invention further provides an apparatus, which specifically includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the user similarity obtaining method based on the user movement trajectory when executing the computer program.
The embodiment of the present invention further provides a computer-readable storage medium, which specifically includes a stored computer program, where when the computer program runs, a device where the computer-readable storage medium is located is controlled to execute the user similarity obtaining method based on the user movement trajectory.
The embodiment of the invention has the following beneficial effects:
according to the method, the device, the equipment and the storage medium for obtaining the user similarity, the similarity between the first user and the second user is obtained by calculating the similarity between the first user moving track and the second user moving track, so that the user similarity obtained by calculation is high in conformity with the actual situation, in addition, the time similarity is introduced in the process of calculating the user similarity, the basis for obtaining the user similarity can be diversified, and the accuracy of the obtained user similarity is improved.
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FIG. 1 is a flowchart illustrating a method for obtaining user similarity based on a user movement trajectory according to a preferred embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a user similarity obtaining apparatus according to a preferred embodiment of the present invention;
fig. 3 is a schematic structural diagram of a preferred embodiment of the apparatus provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
As shown in fig. 1, a flowchart illustrating a preferred embodiment of the method for obtaining user similarity based on a user movement trajectory according to the present invention includes steps S11 to S13, which are as follows:
s11: obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information.
It should be noted that the embodiment of the present invention is executed by a system. Wherein the system may be a system in a telecommunication operator server.
A telecommunication operator sets a plurality of base stations everywhere, and the system obtains the user movement track of the user by obtaining the communication data of the user. Specifically, the system monitors the first user in real time, acquires communication data such as WeChat, short message and QQ of the first user, analyzes the communication data to judge base stations which the first user passes through in the period of time, and records the base stations to obtain the movement track of the first user. In the same way, the movement track of the second user can be obtained.
Further, the first user movement track comprises at least one first track point; the second user moving track comprises at least one second track point; each piece of first time information and each piece of first track point have one-to-one correspondence; and each piece of second time information and each piece of second track point have one-to-one correspondence.
More preferably, the first time information is time information when the first user arrives at the corresponding first track point; and the second time information is the time information when the second user arrives at the corresponding second track point.
It should be noted that, in this embodiment, each time it is detected that the first user moves to a position near one base station, the base station is recorded as one track point, and the time information when the first user arrives at the base station is recorded, and the movement track of the first user can be obtained by recording the base stations that the first user passes through within the preset time period and the time information when the first user arrives at each base station. In the same way, the second user movement track can be obtained.
S12: and obtaining time similarity according to each piece of first time information and each piece of second time information.
It should be noted that, according to each piece of first time information and each piece of second time information, the time similarity (i.e., the probability that the first user and the second user appear at the same geographic location in the same time period) of the first user and the second user is obtained, so as to obtain the time similarity.
S13: and obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity.
It should be noted that, in this embodiment, the similarity between the first user movement track and the second user movement track is calculated by combining the time similarity, so as to obtain the user similarity between the first user and the second user.
In addition, by introducing the time similarity in the process of calculating the user similarity, the basis for obtaining the user similarity can be diversified, and the accuracy of the obtained user similarity can be improved.
In another preferred embodiment, the step S12 further includes a step S1201, which is as follows:
s1201: according to each first time information Ti(u) each of the second time information Tj(v) And a preset time similarity calculation model
Calculating to obtain the time similarity COL; wherein u represents the first user; v represents the second user; n (u) is the total number of first track points in the first user movement track; n (v) is the total number of second track points in the second user moving track; Δ T is a preset time precision; l isi(u) represents the first userMoving the ith first track point in the track; l isj(v) Representing a jth second track point in the second user movement track; delta (L)i(u),Lj(v) Is the coincidence degree of the ith first track point in the first user moving track and the jth second track point in the second user moving track.
Note that, more preferably, the value of Δ T is set to 1 hour. When the ith first track point in the first user moving track is superposed with the jth second track point in the second user moving track, delta (L)i(u),Lj(v) 1, otherwise, δ (L)i(u),Lj(v))＝0。
In another preferred embodiment, the step S13 further includes steps S1301 to S1302, which are as follows:
s1301: calculating a model according to the first user movement track, the second user movement track and the preset track similarity
Calculating to obtain the track similarity DLCSS(ii) a Wherein LCSS (u, v) represents the longest common subsequence between the first user movement trajectory and the second user movement trajectory; len (a)uRepresenting the total number of first track points in the first user moving track; len (a)vAnd the total number of second track points in the second user moving track is represented.
It should be noted that, in the following description,
wherein u isiRepresenting the ith first track point in the first user moving track; v. ofjRepresenting a jth second track point in the second user moving track; gamma is a preset similarity threshold; dist (u)i,vj) Is the Euclidean distance between the first user movement track and the second user movement track.
S1302: according to the track similarity DLCSSAnd obtaining the user similarity according to the time similarity.
Further, the step S1302 further includes a step S1302_1, which is as follows:
s1302_ 1: according to the track similarity DLCSSThe time similarity COL and a user similarity calculation model sim (u, v) ═ DLCSSCOL, calculating to obtain the user similarity sim (u, v).
In another preferred embodiment, after the step S13, the method further includes steps S14 to S16, which are as follows:
s14: and judging whether the user similarity is greater than a preset threshold value, if so, jumping to S15, and if not, jumping to S16.
S15: and judging that the first user and the second user are the same user.
S16: and determining that the first user and the second user are not the same user.
It should be noted that, in this embodiment, the similarity between the first user and the second user is determined by calculating the similarity between the movement track of the first user and the movement track of the second user, so that it can be determined whether the user newly accessing the network is a re-accessing user in the telecommunication operation process. For example, assume that the number used before a subscriber a is 159 x and is deactivated after 2 months of use, and that a subscriber b has opened a new number 186 x after 2 months in the same telecommunications carrier. At this time, the telecom operator analyzes the communication data of the user A and the user B to respectively obtain the user movement track of the user A and the user movement track of the user B, then, the similarity between the user movement track of the user A and the user movement track of the user B is calculated to obtain the user similarity between the user A and the user B, if the user similarity is greater than a certain preset threshold value, the user A and the user B can be considered as the same person, and the user B is judged to be a re-network access user; if the similarity of the user is smaller than or equal to a certain preset threshold value, the user A and the user B are considered to be not the same person, and the user B is judged to be a new network access user. In this embodiment, since the accuracy of the user similarity obtained according to the above embodiment is high, the accuracy of the determination of the re-accessing user can be improved.
It should be further noted that the above step numbers are only used for indicating different steps, and do not limit the execution sequence between the steps.
According to the user similarity obtaining method based on the user movement track provided by the embodiment of the invention, the user similarity between the first user and the second user is obtained by calculating the similarity between the first user movement track and the second user movement track, so that the user similarity obtained by calculation is high in conformity with the actual situation.
Correspondingly, the invention also provides a user similarity obtaining device based on the user movement track, which can realize all the processes of the user similarity obtaining method based on the user movement track in the embodiment.
As shown in fig. 2, a schematic structural diagram of a preferred embodiment of the apparatus for obtaining user similarity based on a user movement track provided by the present invention is as follows:
a user movement track obtaining module 21, configured to obtain a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information;
a time similarity obtaining module 22, configured to obtain a time similarity according to each piece of the first time information and each piece of the second time information; and the number of the first and second groups,
a user similarity obtaining module 23, configured to obtain a user similarity between the first user and the second user according to the first user movement track, the second user movement track, and the time similarity.
Further, the first user movement track comprises at least one first track point; the second user moving track comprises at least one second track point; each piece of first time information and each piece of first track point have one-to-one correspondence; and each piece of second time information and each piece of second track point have one-to-one correspondence.
Further, the time similarity obtaining module specifically includes:
a time similarity calculation unit for calculating a time similarity according to each of the first time information Ti(u) each of the second time information Tj(v) And a preset time similarity calculation model
Calculating to obtain the time similarity COL; wherein u represents the first user; v represents the second user; n (u) is the total number of first track points in the first user movement track; n (v) is the total number of second track points in the second user moving track; Δ T is a preset time precision; l isi(u) representing an ith first track point in the first user movement track; l isj(v) Representing a jth second track point in the second user movement track; delta (L)i(u),Lj(v) Is the coincidence degree of the ith first track point in the first user moving track and the jth second track point in the second user moving track.
Further, the user similarity obtaining module specifically includes:
a track similarity calculation unit for calculating a model according to the first user movement track, the second user movement track and a preset track similarity
Calculating to obtain the track similarity DLCSS(ii) a Wherein LCSS (u, v) represents the longest common subsequence between the first user movement trajectory and the second user movement trajectory; len (a)uRepresenting the total number of first track points in the first user moving track; len (a)vRepresenting the total number of second track points in the second user moving track; and，
a user similarity calculation unit for calculating the similarity D of the trajectoryLCSSAnd obtaining the user similarity according to the time similarity.
Further, the user similarity calculation unit specifically includes;
a user similarity calculation subunit for calculating the trajectory similarity DLCSSThe time similarity COL and a user similarity calculation model sim (u, v) ═ DLCSSCOL, calculating to obtain the user similarity sim (u, v).
Further, the first time information is time information when the first user arrives at the corresponding first track point; and the second time information is the time information when the second user arrives at the corresponding second track point.
Further, the apparatus for obtaining user similarity based on user movement trajectory further includes:
the user similarity judging module is used for judging whether the user similarity is greater than a preset threshold value or not; and the number of the first and second groups,
the first processing module is used for judging that the first user and the second user are the same user when the user similarity is judged to be larger than a preset threshold value; or,
and the second processing module is used for judging that the first user and the second user are not the same user when judging that the similarity of the users is not larger than a preset threshold value.
The user similarity obtaining device based on the user movement track provided by the embodiment of the invention obtains the user similarity between the first user and the second user by calculating the similarity between the first user movement track and the second user movement track, so that the user similarity obtained by calculation is high in conformity with the actual situation.
The invention also provides equipment.
As shown in fig. 3, a schematic structural diagram of a preferred embodiment of the apparatus provided by the present invention includes a processor 31, a memory 32, and a computer program stored in the memory 32 and configured to be executed by the processor 31, where the processor 31 implements the user similarity obtaining method based on the user movement trajectory according to any one of the above embodiments when executing the computer program.
It should be noted that fig. 3 only illustrates an example in which one memory and one processor in the apparatus are connected, and in some specific embodiments, the apparatus may further include a plurality of memories and/or a plurality of processors, and the specific number and the connection mode thereof may be set and adapted according to actual needs.
The device provided by the embodiment of the invention obtains the user similarity between the first user and the second user by calculating the similarity between the first user movement track and the second user movement track, so that the user similarity obtained by calculation is high in conformity with the actual situation.
The present invention further provides a computer-readable storage medium, which specifically includes a stored computer program, where when the computer program runs, a device where the computer-readable storage medium is located is controlled to execute the user similarity obtaining method based on the user movement trajectory according to any one of the above embodiments.
It should be noted that, all or part of the flow in the method according to the above embodiments of the present invention may also be implemented by a computer program instructing related hardware, where the computer program may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above embodiments of the method may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be further noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The computer-readable storage medium provided by the embodiment of the invention obtains the user similarity between the first user and the second user by calculating the similarity between the first user movement track and the second user movement track, so that the user similarity obtained by calculation is high in conformity with the actual situation.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (8)
1. A user similarity obtaining method based on a user movement track is characterized by comprising the following steps:
obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information; the first user moving track comprises at least one first track point; the second user moving track comprises at least one second track point; each piece of first time information and each piece of first track point have one-to-one correspondence; each piece of second time information and each piece of second track point have one-to-one correspondence;
obtaining time similarity according to each piece of first time information and each piece of second time information;
according to the first user movement track, the second user movement track and the time similarity, obtaining the user similarity between the first user and the second user;
wherein, the obtaining the time similarity according to each piece of the first time information and each piece of the second time information specifically includes:
according to each first time information Ti(u) each of the second time information Tj(v) And a preset time similarity calculation model
Calculating to obtain the time similarity COL; wherein u represents the first user; v represents the second user; n (u) is the total number of first track points in the first user movement track; n (v) is the total number of second track points in the second user moving track; Δ T is a preset time precision; l isi(u) representing an ith first track point in the first user movement track; l isj(v) Representing a jth second track point in the second user movement track; delta (L)i(u),Lj(v) Is the coincidence degree of the ith first track point in the first user moving track and the jth second track point in the second user moving track.
2. The method for obtaining user similarity based on user movement trajectory according to claim 1, wherein obtaining the user similarity between the first user and the second user according to the first user movement trajectory, the second user movement trajectory and the time similarity specifically includes:
calculating a model according to the first user movement track, the second user movement track and the preset track similarity
Calculating to obtain the track similarity DLCSS(ii) a Wherein LCSS (u, v) represents the longest common subsequence between the first user movement trajectory and the second user movement trajectory; len (a)uRepresenting the total number of first track points in the first user moving track; len (a)vRepresenting the total number of second track points in the second user moving track;
according to the track similarity DLCSSAnd obtaining the user similarity according to the time similarity.
3. The method as claimed in claim 2, wherein the user similarity obtaining method based on the user movement track is characterized in that the user similarity obtaining method is based on the track similarity DLCSSAnd the time similarity, obtaining the user similarity, specifically comprising:
according to the track similarity DLCSSThe time similarity COL and a user similarity calculation model sim (u, v) ═ DLCSSCOL, calculating to obtain the user similarity sim (u, v).
4. The user similarity obtaining method based on the user moving track according to any one of claims 1 to 3, wherein the first time information is time information when the first user arrives at the corresponding first track point; and the second time information is the time information when the second user arrives at the corresponding second track point.
5. The method as claimed in claim 1, wherein after obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity, the method further comprises:
judging whether the user similarity is greater than a preset threshold value or not;
if yes, the first user and the second user are judged to be the same user;
if not, determining that the first user and the second user are not the same user.
6. A user similarity obtaining apparatus based on a user movement trajectory, comprising:
the user movement track obtaining module is used for obtaining a first user movement track and a second user movement track; the first user movement track comprises at least one piece of first time information; the second user movement track comprises at least one piece of second time information;
a time similarity obtaining module, configured to obtain a time similarity according to each piece of the first time information and each piece of the second time information;
the time similarity obtaining module specifically includes:
a time similarity calculation unit for calculating a time similarity according to each of the first time information Ti(u) each of the second time information Tj(v) And a preset time similarity calculation model
Calculating to obtain the time similarity COL; wherein u represents the first user; v represents the second user; n (u) is the total number of first track points in the first user movement track; n (v) is the total number of second track points in the second user moving track; Δ T is a preset time precision; l isi(u) representing an ith first track point in the first user movement track; l isj(v) Representing a jth second track point in the second user movement track; delta (L)i(u),Lj(v) The coincidence degree of the ith first track point in the first user moving track and the jth second track point in the second user moving track is obtained;
and the number of the first and second groups,
and the user similarity obtaining module is used for obtaining the user similarity between the first user and the second user according to the first user movement track, the second user movement track and the time similarity.
7. An apparatus comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the user similarity obtaining method based on a user movement trajectory according to any one of claims 1 to 5 when executing the computer program.
8. A computer-readable storage medium, comprising a stored computer program, wherein when the computer program runs, the computer-readable storage medium is controlled to execute the method for obtaining user similarity based on user movement trajectory according to any one of claims 1 to 5.
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