JP2009301478A - Similar play list retrieving method, program and apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a similar play list retrieving method, program and apparatus capable of easily retrieving a similar play list from play lists of musical pieces. <P>SOLUTION: In the method for retrieving the similar play list, a similar play list retrieving apparatus 1 provided with a storage part 20 for storing a play list DB 22 wherein the play list including the musical piece ID of the musical piece selected by a user and a play list ID are made to correspond executes the OR retrieval of other play lists stored in the play list DB 22 including the musical piece ID in the prescribed play list for the prescribed play list stored in the play list DB 22, and calculates a similarity degree for the prescribed play list for each of the other pertinent play lists. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a method, a program, and an apparatus for searching a playlist similar to a playlist of songs.

  Conventionally, when a user listens to music on the Internet or the like, there is a need to stock (record) favorite music and easily reproduce it later. For this purpose, a mechanism is provided in which a user can create a playlist that includes favorite songs. A playlist is a list in which songs to be played are selected from a large number of songs. By preparing a playlist, the user can easily listen to favorite songs in the order of the list.

Regarding such a playlist, there has been disclosed a playlist search device that selects and presents a playlist that suits the user's preference from among a plurality of playlists (for example, Patent Document 1).
JP 2007-287256 A

  The playlist search device described in Patent Literature 1 searches for a playlist associated with similar story information using story information in which related information of songs is arranged in the order of reproduction for a plurality of songs included in the playlist. To select. This selects the user's preference regarding the playback order of the playlist based on the story information. However, since playlists are often used for stocking favorite songs, there are users who are not particular about the order of playback. In addition, there is a problem that a stage for creating story information is necessary, and the system is burdened accordingly.

  On the other hand, in a virtual concert performed on the Internet, for example, there is a need to invite users with common sensibilities in order to gather users with common sensibilities. However, it is difficult to find a user having a common sensibility from among a large number of users on the Internet.

  Therefore, an object of the present invention is to provide a similar playlist search method, program, and apparatus that can easily search for a similar playlist from a playlist of songs. It is another object of the present invention to provide a method for easily searching for users having common sensibilities based on the searched similar playlist.

  The inventor has found a mechanism for finding out users having a common sensibility from a playlist of songs, and has completed the present invention. Specifically, the present invention provides the following.

(1) A server including a storage unit that stores a playlist database that associates a playlist including a song ID of a song selected by a user with a playlist ID that identifies the playlist, A search method,
For the predetermined playlist stored in the playlist database, the server performs an OR search on another playlist stored in the playlist database including the song ID in the predetermined playlist, and the corresponding playlist is stored. A calculation step of calculating a similarity to the predetermined playlist for each of the other playlists;
Similar playlist search method.

  According to such a configuration of the present invention, the other playlist is OR-searched from the song ID of the predetermined playlist stored in the playlist database, and the similarity with the predetermined playlist with respect to the other playlist is determined. It can be shown numerically as the similarity. Further, since a predetermined playlist can be used without creating other information, the similarity can be calculated by a simple method.

(2) The calculation step includes a ratio of the number of songs matching the number of songs included in the other playlist to the total number of songs of the predetermined playlist, and the predetermined number of songs for the number of songs of the other playlist. Multiply by the ratio of the number of songs that match the songs included in the playlist to calculate the similarity,
The similar playlist search method according to (1).

  According to such a configuration of the present invention, the ratio of the number of songs matching the number of songs included in another playlist to the total number of songs in the predetermined playlist, and the number of songs included in the predetermined playlist relative to the total number of songs in the other playlist. By calculating the similarity by multiplying by the ratio of the number of songs that match, the similarity can be calculated from the content ratio of the common songs in the predetermined playlist and other playlists.

(3) The storage unit stores a song database in which the song ID is associated with a popularity degree that is a degree according to the number of times the song is played.
In the calculation step, the similarity is calculated for the song ID having the degree of popularity that is higher than a predetermined threshold.
The similar playlist search method according to (1) or (2).

  According to such a configuration of the present invention, the degree of similarity is calculated from a predetermined playlist for a song having a degree of popularity higher than a predetermined threshold using the degree of popularity of the song. The popularity is defined by, for example, the number of reproductions in a predetermined period. Therefore, the similarity can be calculated for popular songs that are often listened to in the world.

(4) The storage unit stores a song database that associates the song ID, a similar song ID that identifies a song similar to the song, and the similarity of the song ID and the similar song ID. And
In the calculating step, the similarity is calculated using the similar song ID corresponding to the song ID in the predetermined playlist and the similarity of the song.
The similar playlist search method according to any one of (1) to (3).

  According to such a configuration of the present invention, the similarity is calculated not only for matching with the song ID in the predetermined playlist, but also including similar songs. By doing so, a more precise similarity degree can be calculated.

(5) including an output step of outputting the other playlists in descending order of the degree of similarity searched in the calculation step;
The similar playlist search method according to any one of (1) to (4).

  According to such a configuration of the present invention, other playlists are output in descending order of the degree of similarity. Therefore, it is possible to output in descending order of a predetermined playlist as a search source.

(6) The storage unit stores a user database in which the playlist ID is associated with a user ID that identifies an owner of the playlist.
In the output step, the user ID corresponding to the playlist ID of the other playlist is output.
The similar playlist search method according to (5).

  According to such a configuration of the present invention, since the user IDs of the other playlists are output in descending order of the degree of similarity, it is possible to know users who are more sensitive.

(7) an accepting step for accepting designation of the playlist ID;
Acquiring the predetermined playlist corresponding to the playlist ID received in the receiving step from the playlist database,
The similar playlist search method according to any one of (1) to (6).

  According to such a configuration of the present invention, designation of a playlist ID is accepted, and the similarity between the playlist and another playlist is indicated by a numerical value as a similarity from the song ID of the acquired playlist. Can do. Therefore, the similarity with other playlists can be calculated by specifying the playlist ID.

  (8) A similar playlist search program for causing a computer to execute the steps of the method according to any one of (1) to (7).

(9) a storage unit that stores a playlist database in which a playlist including a song ID of a song selected by a user and a playlist ID that identifies the playlist are associated with each other;
For the predetermined playlist stored in the playlist database, the other playlist stored in the playlist database including the song ID in the predetermined playlist is OR-searched, and the corresponding other playlist A similarity calculation unit that calculates the similarity to the predetermined playlist for each of
A similar playlist search device comprising:

  According to the present invention, a similar playlist can be easily searched from a playlist of songs. In addition, a user having a common sensitivity can be found from the search result.

  Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings. This is merely an example, and the technical scope of the present invention is not limited to this.

(First embodiment)
[Overall Configuration of Similar Playlist Search System and Functional Configuration of Similar Playlist Search Device]
FIG. 1 is a diagram illustrating an overall configuration of a similar playlist search system 100 and a functional configuration of the similar playlist search device 1 according to the first embodiment.

  The similar playlist search system 100 includes a similar playlist search device 1, a communication network 3, and a terminal 5. As shown in FIG. 1, a similar playlist search device 1 and a terminal 5 are communicably connected via a communication network 3 typified by a communication line such as the Internet.

  The similar playlist search device 1 includes a control unit 10 and a storage unit 20. The control unit 10 includes a playlist ID reception unit 11, a playlist acquisition unit 12, a similarity calculation unit 13, and another playlist output unit 14. In addition, the storage unit 20 includes a playlist database (hereinafter, the database is also referred to as a DB) 22, a song DB 24, and a user DB 26. The contents of each DB will be described later.

  The similar playlist search device 1 is, for example, a server, and the number of hardware is not limited, and may be configured with one or a plurality of hardware as necessary. In the case of a plurality of hardware, each hardware may be connected via the communication network 3. For example, the functions of the first embodiment may be realized by using a separate server (apparatus) for each function described later, and by linking the servers by transmitting and receiving signals between the servers.

  The playlist ID reception unit 11 receives from the terminal 5 designation of a playlist ID for the similar playlist search device 1. The method of specifying the playlist ID by the terminal 5 is, for example, a screen in which the playlist ID may be transmitted from the terminal 5 by directly inputting the playlist ID in the terminal 5 or a screen on which a plurality of playlists are displayed. The playlist ID corresponding to the playlist selected from the terminal 5 may be transmitted by the user selecting one playlist.

  The playlist acquisition unit 12 acquires a corresponding playlist from the playlist DB 22 based on the playlist ID received from the terminal 5. The similarity calculation unit 13 calculates the similarity between the acquired playlist and another playlist stored in the playlist DB 22. A specific calculation method will be described later. The other playlist output unit 14 outputs other playlists in descending order of the degree of similarity based on the calculated similarity.

  The terminal 5 is, for example, a personal computer (PC) including an input unit for a user to input a playlist ID to be searched and a display unit for displaying a search result. Using the terminal 5, the user can participate in a concert on the Internet or listen to a song.

[Hardware configuration diagram of similar playlist search device 1]
FIG. 2 is a diagram illustrating a hardware configuration of the similar playlist search device 1 according to the first embodiment. The server in which the present invention is implemented may be a standard server, and an example of the configuration is shown below.

  The similar playlist search device 1 includes a central processing unit (CPU) 1010 (a plurality of CPUs such as a CPU 1012 may be added in a multiprocessor configuration), a bus line 1005, a communication I / F (I / F). F: Interface) 1040, main memory 1050, BIOS (Basic Input Output System) 1060, display device 1022, I / O controller 1070, input device 1100 such as keyboard and mouse, hard disk 1074, optical disk drive 1076, and semiconductor memory 1078 Prepare. The hard disk 1074, the optical disk drive 1076, and the semiconductor memory 1078 are collectively referred to as the storage unit 20.

  The control unit 10 is a part that controls the similar playlist search device 1 in an integrated manner. By appropriately reading and executing various programs stored in the hard disk 1074, the control unit 10 cooperates with the hardware described above, and Various functions are realized.

  The communication I / F 1040 is a network adapter when the similar playlist search device 1 transmits / receives information to / from the terminal 5 (FIG. 1) via the communication network 3 (FIG. 1). The communication I / F 1040 may include a modem, a cable modem, and an Ethernet (registered trademark) adapter.

  The BIOS 1060 records a boot program executed by the CPU 1010 when the similar playlist search device 1 is started, a program depending on the hardware of the similar playlist search device 1, and the like.

  The display device 1022 includes a display device such as a cathode ray tube display device (CRT) or a liquid crystal display device (LCD).

  The I / O controller 1070 can be connected to a storage unit 20 that is a storage device such as a hard disk 1074, an optical disk drive 1076, and a semiconductor memory 1078.

  The input device 1100 is for accepting input by the administrator of the similar playlist search device 1.

  The hard disk 1074 stores various programs for causing the hardware to function as the similar playlist search device 1, programs for executing the functions of the invention, and DB tables and records to be described later. Note that the similar playlist search device 1 can also use a hard disk (not shown) separately provided as an external storage device.

  As the optical disc drive 1076, for example, a DVD-ROM drive, a CD-ROM drive, a DVD-RAM drive, or a CD-RAM drive can be used. In this case, the optical disk 1077 corresponding to each drive is used. A program or data can be read from the optical disk 1077 by the optical disk drive 1076 and provided to the main memory 1050 or the hard disk 1074 via the I / O controller 1070.

  The computer in the present invention refers to an information processing device including a storage device, a control unit, and the like, and the similar playlist search device 1 is configured by an information processing device including the storage unit 20, the control unit 10, and the like. This information processing apparatus is included in the concept of the computer of the present invention.

[Hardware configuration of terminal 5]
The terminal 5 has the same configuration as that of the similar playlist search device 1 described above. In the above-described example, an example realized by a so-called computer has been described. Furthermore, as long as the principle of the present invention is applicable, the present invention may be realized by various terminals such as a mobile phone and a PDA (Personal Data Assistant).

[Database stored in the storage unit 20]
FIG. 3 is a diagram illustrating each database stored in the storage unit 20 according to the first embodiment.

  FIG. 3A shows an example of the playlist DB 22. The playlist DB 22 is a database that associates song IDs that specify songs constituting the playlist with playlist IDs as key information.

  The playlist DB 22 has a playlist ID 22a and a song ID 22b. As described above, the playlist ID 22a stores a symbol that uniquely indicates the playlist. This symbol may be appropriately given by the control unit of the device when creating the playlist. Further, as described above, the music ID 22b stores a symbol that uniquely indicates the music. A plurality of song IDs may be associated with one playlist ID.

  FIG. 3B shows an example of the music DB 24. The song DB 24 is a database that associates various types of information related to the song with the song ID as key information.

  The music DB 24 has a music ID 24a, a popularity 24b, a similar music ID 24c, and a music similarity 24d. Similar to the song ID 22b of the playlist DB 22, the song ID 24a stores a symbol uniquely indicating the song. The popularity 24b is a numerical value representing the popularity of a song uniquely identified by the song ID 24a. The popularity is, for example, a numerical value calculated from the number of times the song is played on the Internet, and may be a ratio with 100 as the maximum value.

  The similar music ID 24c stores a symbol that is similar to the music uniquely specified by the music ID 24a and that uniquely represents the similar music. The song stored in the similar song ID is, for example, a cover song in which a certain song is covered by another singer or performer, or a song with a different recording location or instrument used. A song with a different rhythm. The similarity between the song indicated by the song ID stored in the song ID 24a and the song indicated by the similar song ID stored in the similar song ID 24c is stored in the song similarity 24d. The numerical value stored in the similarity of music is calculated based on, for example, the music feature, music title, and music attributes. And the ratio which made 100 the maximum value may be sufficient. The sound source data of the song specified by the song ID may be stored in the song DB 24 or in another DB. The song specified by the song ID may include moving image content such as a music video.

  FIG. 3C shows an example of the user DB 26. The user DB 26 is a database that associates a playlist ID with a user ID as key information.

  The user DB 26 has a user ID 26a and a playlist ID 26b. As described above, the user ID 26a stores a symbol that uniquely indicates the user. The playlist ID 26b stores a symbol that uniquely indicates the playlist, similarly to the playlist ID 22a of the playlist DB 22. A plurality of playlist IDs may be associated with one user ID.

[Similar playlist search processing flowchart]
FIG. 4 is a flowchart of the similar playlist search process according to the first embodiment.

  S1: The playlist ID reception unit 11 of the similar playlist search device 1 receives and receives a specification of a playlist ID from the terminal 5.

  S2: The playlist acquisition unit 12 of the similar playlist search device 1 acquires a playlist corresponding to the received playlist ID from the playlist DB 22.

  S3: The similarity calculation unit 13 of the similar playlist search device 1 performs a similarity calculation process described later.

  S4: The other playlist output unit 14 of the similar playlist search device 1 selects user IDs corresponding to playlist IDs of other playlists in descending order of the degree of similarity based on the playlist DB 22 and the user DB 26. Extract and output.

  S5: The control unit 10 of the similar playlist search device 1 transmits the output user ID information to the terminal 5.

  Therefore, the specification of the playlist ID is accepted, and the degree of similarity is high for the user ID of another playlist similar to the playlist that has been designated for the other playlist from the song ID of the acquired playlist. Since it outputs in order from the thing, it can output in order from the user with more common sensitivity. Therefore, by using this user ID, it is possible to know users with common sensibilities.

  In addition, you may output another playlist in an order from the thing similar by the playlist which received designation | designated as a search source.

[Flowchart of similarity calculation processing]
FIG. 5 is a flowchart of similarity calculation processing according to the first embodiment.

  S11: The similarity calculation unit 13 selects one song ID in order from the playlist.

  S12: The similarity calculation unit 13 extracts another playlist including the selected song ID from the playlist DB 22 by performing an OR search.

  S13: The similarity calculation unit 13 determines whether or not extraction processing has been performed for the song IDs of all the songs included in the playlist. When the extraction process is performed for the song IDs of all the songs included in the playlist (S13: YES), the similarity calculation unit 13 moves the process to step S14. On the other hand, when the extraction process is not performed for the song IDs of all the songs included in the playlist (S13: NO), the similarity calculation unit 13 moves the process to step S11 and performs the extraction process for all the songs. By doing so, the processing from step S11 to step S13 is repeated.

  S14: The similarity calculation unit 13 calculates the similarity for each of the other extracted playlists. Thereafter, the similarity calculation unit 13 returns the process to the similar playlist search process (FIG. 4).

  Here, the method for calculating the similarity will be described in more detail. 6 and 7 are diagrams for explaining a similarity calculation method according to the first embodiment.

  FIG. 6 is a diagram illustrating a calculation method for calculating the similarity of another playlist having a matching song ID included in the search source playlist. FIG. 6 shows a playlist that is a search source, a playlist 30 that is a received playlist, and a playlist that is a search target that is extracted when at least one playlist ID and song ID match. A playlist 40, which is one of the other playlists, is shown. The playlist 30 and the playlist 40 are stored in the playlist DB 22.

  In the playlist 30, the playlist ID stored in the playlist ID 22a is “XY1”, and a total of ten song IDs with song IDs 22b ranging from “AAA” to “JJJ” are associated with this playlist. On the other hand, in the playlist 40, the playlist stored in the playlist ID 22a is “ZA3”, and a total of eight song IDs with song IDs 22b ranging from “XXX” to “HHH” are associated with this playlist. . In the case of this example, the playlist 30 and the playlist 40 have a total of four songs whose song IDs are “CCC”, “EEE”, “HHH”, and “JJJ”.

で表す。また、含有率を、

で表す。 Here, the similarity is

Represented by In addition, the content rate

Represented by

  In the case of FIG. 6, the total number of songs in the playlist 30 that is the search source playlist is “10”, and the number of matching songs between the playlist 30 and the playlist 40 is “4”. The rate is “4/10”. Similarly, since the total number of songs in the playlist 40 that is the search target playlist is “8” and the number of matching songs is also “4”, the content rate of the playlist 40 is “4/8”. . Therefore, the similarity can be calculated as “(4/10) × (4/8) = 1/5”.

  In this way, the ratio of the number of songs matching the songs included in the other playlist to the total number of songs in the acquired playlist, and the ratio of the number of songs matching the songs included in the playlist to the total number of songs of the other playlist extracted By multiplying and calculating the similarity, the similarity can be calculated based on the content ratio of the common music in the playlist and other playlists.

  FIG. 7 is a diagram illustrating a calculation method for calculating the similarity of other playlists whose song IDs included in the search source playlist match after narrowing down popular songs. FIG. 7 shows a playlist 30 and a playlist 40 stored in the playlist DB 22 as in FIG. FIG. 7 also shows a song DB 24 that stores the song IDs included in the playlist 30 and the playlist 40 and their popularity. Here, the similarity is calculated by setting the threshold value to “20”. Referring to the song DB 24, five song IDs “BBB”, “FFF”, “JJJ”, “YYY”, and “OOO”, which are song IDs whose popularity is less than “20”, are subject to similarity calculation. It is outside. For this reason, the playlist 30 and the playlist 40 having the above-mentioned music IDs are shaded as excluded.

  The similarity is calculated using the mathematical formula shown in FIG. The playlist 30 has “7 (= 10−3)” as the number of songs for which the degree of similarity is calculated, and the number of matching songs between the playlist 30 and the playlist 40 is “3” among the targeted song IDs. is there. Therefore, the content rate of the playlist 30 is “3/7”. Similarly, in the playlist 40, the total number of songs for which the degree of similarity is to be calculated is “5 (= 8-3)”, and among the target song IDs, the number of matching songs is also “3”. Therefore, the content rate of the playlist 40 is “3/5”. Therefore, the similarity can be calculated as “(3/7) × (3/5) = 9/35”.

  In this way, the designation of the playlist ID is accepted, and another playlist is OR-searched from the song ID of the acquired playlist, and the similarity with the playlist that has been designated with respect to the other playlist is determined as the similarity. And the similarity can be calculated by a simple method.

  In addition, by calculating the similarity by using the content ratio of the songs included in the search source playlist and the songs included in the search target playlist, the higher the similarity, the higher the similarity of the search source playlist. It can be determined that the playlist includes many of the same songs as the songs included in, and is a playlist of users having common sensibilities. Therefore, by calculating the similarity, it is possible to find a playlist with more sensitivity.

  Furthermore, since the degree of similarity is calculated from a playlist for songs with a degree of popularity higher than a predetermined threshold using the degree of popularity of the song, for popular songs that are often heard in the world, Similarity can be calculated.

(Second Embodiment)
In the first embodiment, a description has been given of calculating the similarity based on the content rate of the song IDs of other playlists that match the song IDs included in the search source playlist. In the second embodiment, not only those whose similarity matches the song ID included in the search source playlist, but also songs in other playlists including songs similar to the song ID included in the search source playlist. It is calculated based on the content rate of ID.

  Note that, in the following description, the same functions as those in the first embodiment described above are denoted by the same reference numerals or the same reference numerals at the end, and repeated descriptions are omitted as appropriate.

[Flowchart of similarity calculation processing]
FIG. 8 is a flowchart of similarity calculation processing according to the second embodiment. In addition, FIG. 8 changes from step S3 of FIG. 4 demonstrated in 1st Embodiment.

  S21: The similarity calculation unit 13 selects one song ID in order from the playlist.

  S22: If there is a similar song ID corresponding to the selected song ID, the similarity calculation unit 13 extracts the similar song ID from the song DB 24.

  S23: The similarity calculation unit 13 extracts another playlist including the selected song ID or the extracted similar song ID from the playlist DB 22.

  S24: The similarity calculation unit 13 determines whether or not extraction processing has been performed for the song IDs of all the songs included in the playlist. When the extraction process is performed for the song IDs of all the songs included in the playlist (S24: YES), the similarity calculation unit 13 moves the process to step S25. On the other hand, when the extraction process is not performed for all the song IDs included in the playlist (S24: NO), the similarity calculation unit 13 moves the process to step S21 and performs the extraction process for all the songs. By doing so, the processing from step S21 to step S24 is repeated.

  S25: The similarity calculation unit 13 calculates the similarity for each of the other extracted playlists. Thereafter, the similarity calculation unit 13 returns the process to the similar playlist search process (FIG. 4).

  Here, the method for calculating the similarity will be described in more detail. FIG. 9 is a diagram for explaining a similarity calculation method according to the second embodiment. In FIG. 9, a calculation method for calculating the similarity of other playlists including not only the song IDs included in the search source playlist that match but also those that match the similar song ID corresponding to the song ID. explain.

  FIG. 9 shows a playlist that is a search source, a playlist that is a search target that is extracted when the playlist 30 that is the accepted playlist matches with at least one song ID or similar song ID. A playlist 50 that is one of the playlists is shown. The playlist 30 and the playlist 50 are stored in the playlist DB 22.

  In the playlist 30, the playlist ID stored in the playlist ID 22a is “XY1”, and a total of ten song IDs with song IDs 22b ranging from “AAA” to “JJJ” are associated with this playlist. On the other hand, in the playlist 50, the playlist ID stored in the playlist ID 22a is “CJ5”, and a total of eight song IDs are associated with this playlist from the song ID 22b from “HHH” to “ZZZ”. Yes. In this example, in the playlist 30 and the playlist 50, a total of two songs with the song IDs “CCC” and “HHH” match.

  FIG. 9 shows a song DB 24 in which the similar song ID stored in the similar song ID 24 c among the song IDs included in the playlist 30 is included in the song ID of the playlist 50. For example, the uppermost record in the song DB 24 is similar to the song whose song ID is “EEE” stored in the song ID 24a, the similar song ID 24c is “EGF”, and the song stored in the song similarity 24d. The similarity is “50”. In this example, in the playlist 30 and the playlist 50, a song similar to the song whose song ID is “EEE” in the playlist 30 is a song whose song ID is “EGF” in the playlist 50. The music similar to the music with the music ID of “JJJ” 30 is the music with the music ID of “JJH” in the playlist 50, and a total of two music is similar.

と算出できる。 Here, when calculating the similarity, the similarity of music is considered. In this case, the number of matching songs between the playlist 30 and the playlist 50 can be calculated as “1 + 1 + 50/100 + 90/100”. The total number of songs in the playlist 30 that is the search source playlist is “10”, and the total number of songs in the playlist 40 that is the search target playlist is “8”. Therefore, the similarity is

And can be calculated.

  According to the second embodiment, the degree of similarity is defined as a content ratio that includes not only songs that are included in the search source playlist and songs that are included in the search target playlist but also similar songs. By calculating, the target song can be expanded. And it can be judged that it is a play list of a user who has many sensibilities, and is a play list containing many the same music as the music included in the play list of search origin, so that similarity is high. Therefore, when calculating the degree of similarity, it is possible to find a playlist with more sensitivity by including similar music.

  As mentioned above, although embodiment of this invention was described, this invention is not restricted to embodiment mentioned above. The effects described in the embodiments of the present invention are only the most preferable effects resulting from the present invention, and the effects of the present invention are limited to those described in the embodiments of the present invention. is not.

(Deformation)
In the first and second embodiments, the user ID corresponding to the playlist is output and transmitted to the terminal in descending order of the degree of similarity, but the playlist itself may be transmitted to the terminal. Good. By doing so, it is possible to know what kind of music is registered as a playlist by a user with similar sensibility, and it is possible to provide an opportunity to know a music that matches the sensitivity of a new user. Moreover, it can use for various systems, such as inviting to the concert on the internet using the user ID transmitted to the terminal.

  In the first embodiment, the method of calculating the similarity using the popularity is described. In the second embodiment, the method of calculating the similarity using the similarity of the music is described. Of course, the similarity may be calculated using the similarity of music.

It is a figure which shows the whole structure of the similar playlist search system which concerns on 1st Embodiment, and the function structure of a similar playlist search apparatus. It is a figure which shows the hardware constitutions of the similar playlist search apparatus which concerns on 1st Embodiment. It is a figure which shows each database stored in the memory | storage part which concerns on 1st Embodiment. It is a flowchart of a similar playlist search process according to the first embodiment. It is a flowchart of the similarity calculation process which concerns on 1st Embodiment. It is a figure for demonstrating the calculation method of the similarity degree which concerns on 1st Embodiment. It is a figure for demonstrating the calculation method of the similarity degree which concerns on 1st Embodiment. It is a flowchart of the similarity calculation process which concerns on 2nd Embodiment. It is a figure for demonstrating the calculation method of the similarity degree which concerns on 2nd Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Similar playlist search apparatus 5 Terminal 10 Control part 11 Playlist ID reception part 12 Playlist acquisition part 13 Similarity calculation part 14 Other playlist output part 20 Storage part 22 Playlist DB
24 songs DB
26 User DB
30, 40, 50 playlist 100 similar playlist search system

Claims (9)

A method in which a server including a storage unit that stores a playlist database in which a playlist including a song ID of a song selected by a user is associated with a playlist ID that identifies the playlist is searched for a similar playlist. Because
For the predetermined playlist stored in the playlist database, the server performs an OR search on another playlist stored in the playlist database including the song ID in the predetermined playlist, and the corresponding playlist is stored. A calculation step of calculating a similarity to the predetermined playlist for each of the other playlists;
Similar playlist search method. In the calculation step, the ratio of the number of songs matching the number of songs included in the other playlist to the total number of songs of the predetermined playlist, and the predetermined playlist for the number of songs of the other playlist. Multiply by the ratio of the number of songs that match the song to include, the similarity is calculated,
The similar playlist search method according to claim 1. The storage unit stores a song database in which the song ID is associated with a popularity degree that is a degree according to the number of times the song is played.
In the calculation step, the similarity is calculated for the song ID having the degree of popularity that is higher than a predetermined threshold.
The similar playlist search method according to claim 1 or 2. The storage unit stores a song database that associates the song ID, a similar song ID that specifies a song similar to the song, and the similarity of the song ID and the similar song ID.
In the calculating step, the similarity is calculated using the similar song ID corresponding to the song ID in the predetermined playlist and the similarity of the song.
The similar playlist search method according to any one of claims 1 to 3. Including the output step of outputting the other playlist in order from the highest degree of similarity searched in the calculating step;
The similar playlist search method according to any one of claims 1 to 4. The storage unit stores a user database in which the playlist ID is associated with a user ID that identifies an owner of the playlist.
In the output step, the user ID corresponding to the playlist ID of the other playlist is output.
The similar playlist search method according to claim 5. An accepting step for accepting designation of the playlist ID;
Acquiring the predetermined playlist corresponding to the playlist ID received in the receiving step from the playlist database,
The similar playlist search method according to any one of claims 1 to 6.   The similar playlist search program for making a computer perform the step of the method of any one of Claims 1-7. A storage unit that stores a playlist database in which a playlist including a song ID of a song selected by a user and a playlist ID that identifies the playlist are associated with each other;
For the predetermined playlist stored in the playlist database, the other playlist stored in the playlist database including the song ID in the predetermined playlist is OR-searched, and the corresponding other playlist A similarity calculation unit that calculates the similarity to the predetermined playlist for each of
A similar playlist search device comprising:

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