JP2009516240A - Method and system for selecting media - Google Patents

Abstract

A system and method for selecting media. In one embodiment, the media is selected based on the desired degree of relationship, user input, relationship data, and media file identity. In another embodiment, the method and system are implemented in a portable device, car audio system, consumer electronic device, mobile phone, or software program running on a personal computer that can play media files and some other device. The
[Selection] Figure 1

Description

  The present disclosure relates to a media device, such as a portable media player, and a method for selecting media that identifies and selects a media file (such as a recording for playback on the device). The method is implemented in a car audio system, a consumer electronic device, a mobile phone, a software program running on a personal computer, or any other device capable of playing media files.

  Digital audio compression technology such as MP3 has emerged, combined with an inexpensive device capable of storing ever-increasing amounts of data, a revolutionary new way to manage and access music collections and media files Opened. Pioneered by Musicmatch, Real Networks, Yahoo! and others, digital media players or media jukeboxes allow users to copy music collections from compact discs and record albums to a compressed digital audio format stored on a computer hard drive. I made it.

  Once stored in this format, the jukebox software allows users to catalog and organize their media files and music collections. More importantly, as software evolves, users will have unprecedented control over playback of recordings. The tracks can be played back in any order with virtually no delay in searching for the tracks. “Random access” across the entire music collection allows users to create an ordered list of tracks before playback, skip the playlist order during playback, pause, replay, shuffle, or edit It became so. The introduction of inexpensive computer memory (RAM) has led to the creation of relatively low-capacity portable music players with the same performance.

  Recently, the introduction of a cheaper, smaller and relatively robust mass storage device has led to a new generation of portable devices with a storage capacity of thousands of songs. The entire music collection now enters the pocket, wallet or car audio system.

  However, portable media devices often have limited user interface resources. Since the device itself is small, the display is generally small. Input devices such as button controllers and selection devices are simple. Pointing devices and keyboards are rare or impractical. A portable device must choose a simple user interface to ensure that the device is portable, cost effective, easy to use, and robust enough to withstand use in its intended environment. Portable media players are designed to operate in an environment that not only imposes difficulties on the ability of the device to operate, but also imposes difficulties on the user operating the device. Portable media players are increasingly used in automobiles. People jogging and manipulating exercise equipment also use portable devices.

  The task of manipulating the playlist and selecting an artist, album, or track from hundreds or thousands of choices is cumbersome due to limited display and user input capabilities. When it comes to car media player equipment, the task of selecting the next audio recording when the user is driving a car is very dangerous. The user is forced to become passive and only listen to pre-programmed or random playlists.

  Personal computer-based media players have experienced a transitional period that puts users in similar circumstances. Personal computer-based media players currently often drive home entertainment systems consisting of component audio amplifiers and speakers. In such an environment, the listening environment is in a different room than the personal computer.

  “Media Center” personal computers use a simplified user interface that is displayed on a large format display device, such as a television screen.

  Such a simplified user interface designed to be viewed from a distance is often referred to as a “10 foot UI” which refers to the user's typical distance from the display. Being portable, the ability to manipulate playlists and interact with music based on atmosphere or context is reduced and users tend to be passive.

  The “living room” listening environment also makes users reluctant to interact with the music selection process. If the personal computer is far away, the user must walk to another room to access the interface. If the personal computer is a media center personal computer, the display must be turned on, switched appropriately, and the interface device (wireless remote, mouse, keyboard) accessible.

  The present disclosure addresses these issues, where the limitations of the media player interface and the complexity of the listening environment prevent users from interacting with music recording selections.

  The present disclosure particularly enables a user interface to a media device to be easily interacted with the media device in such a way that a music program is tailored to the user when the user's operating environment is not complicated device interaction. Describes the method and system.

  In some embodiments, the media device includes a plurality of media files, a user interface, and data indicating a degree of relationship between the first, second, and third elements. The first element receives user input indicating a desired degree of relationship and a desire to identify the second media file. The second element specifies the first media file. The third element identifies the second media file according to the desired degree of relationship and the identity of the first media file.

  In another embodiment, a portable media player for interactively playing media files includes a storage device and software. The storage device is a storage device for data indicating media files and relationships between the media files. The software receives an event that triggers a skip having a certain size and selects the next media file to play based on the skip size, with the skip size and the current media file The association between the alternative media files that can be selected affects the likelihood of selecting one of the alternative media files as the next media file. The portable player further includes a database system that contains information used to identify the relationship between the media file and the media file, and a communication unit for connecting to one or more computing devices. . The relationship between media files is transferred from one or more computer devices to a portable media player.

  In another embodiment, a method of selecting media includes user input indicating identifying an identity of a first media file among a plurality of media files, a desired degree of relationship, and a desire to select a second media file. Receiving relation data indicating the degree of relationship between media files; selecting a second media file according to a desired degree of relation, user input, relational data, and identity of the first media file; , Including. The media file is a recording for playback, wherein the first media file is the current recording and the second media file is the new recording.

  In another embodiment, the system, when executed by one or more computer devices, has one or more computer readable media having computer readable instructions for performing the method, and one or more A computer device embodying a computer readable medium is included.

  Yet another embodiment includes a method for creating a sequence of recordings, selecting media files using a skip command, and selecting media files for playback. Although this disclosure describes media files, all types of files that can be read by automated means and provide a perceptible experience to the user, including but not limited to files such as video and audio. Are considered to be within the scope of this disclosure.

  The accompanying drawings, which form a part of this application, illustrate embodiments of the invention and are not intended to limit the scope of the invention, which is covered by the appended claims. Based on the scope of

  Several exemplary embodiments of the present disclosure will be discussed with reference to the accompanying drawings, wherein like reference numerals refer to like elements.

  In general, this disclosure relates to methods, media devices, systems, and user interfaces for selecting media. In one embodiment, the media is selected based on the desired degree of relationship, user input, relationship data, and the identity of the device media file. Such devices include, but are not limited to, portable media devices, personal computer-based media players, media devices, streaming media devices, satellite radio or video receivers, cell phones, and / or stored. Other appliances or hardware / software configurations suitable for converting information into a perceivable user-user experience are included. Thus, each device is supported by a specific system configuration or architecture that allows easy media selection.

  In another embodiment of the method for selecting media, the method includes recognizing a value of at least one attribute of a media file in a plurality of media files, a desired degree of relationship, and the plurality of media files. Receiving relational data indicating a degree of relationship between receiving a user input indicating a desire to select a second media file in the plurality of media files and a value of at least one attribute of the media files in the plurality of media files Selecting the second attribute value according to the desired degree of relationship, the user input, the relationship data, and the first attribute value; and selecting a second media file according to the selected second attribute value. Selecting.

  In one embodiment, the attribute is the basic recording artist of the media file. In another embodiment, the attribute is the genre of the media file or recording. In one embodiment, the media file is a recording.

  In another embodiment, the method further includes biasing the selection of the second media file based on the additional attribute. In one embodiment, the additional attribute is the popularity of the media file. In another embodiment, the additional attribute indicates an explicit rating of the media file. In another embodiment, the additional attributes are user behaviors tracked and observed by one or more components of the system (eg, user track selection, track selection frequency, standard skip to avoid tracks) Implicit ratings for media files based on track deletion from playlists, etc.).

  In another embodiment, each device is supported by a particular system configuration or architecture to facilitate the creation of data that also indicates the degree of relationship between media files.

  In one embodiment, when the device stores data indicating the degree of relationship between multiple media files, the user can perform several playback functions on multiple media files. These interactive playback functions will be described in more detail later.

Exemplary Embodiments of Portable Media Device In one embodiment, as shown in FIGS. 1 and 2, the portable media device or portable media player may have a desired degree of relationship, user input, relationship data, and media file identity. Based on the ability to select media files. Such portable media player devices include, but are not limited to, the MP3 player known by the trade names APPLE IPOD, CREATIVE LABS ZEN MICRO, DELL DJ, IRIVER H10, RIO CARBON, or such functions. Mobile phones or similar devices that can store and / or play media files. FIG. 1 illustrates an exemplary method for creating relationship data and loading the relationship data into a portable media device. FIG. 2 illustrates an exemplary system architecture or configuration for creating relationship data and loading it into a portable media device. FIG. 2 shows a portable music player 205 connected to a personal computer 210, which is connected to a centralized music information server 215. The portable music player 205 includes at least one user input icon such as a button 206, an optional display 207, a selection engine 209, an audio rendering function 203, a synchronization manager 208, an artist, a genre, an album or some other The relationship graph 201 based on the category of the type and the audio recording 202 are provided. The personal computer 210 includes music management software 212, a portable device manager 204, and an audio library 211. The centralized music information server 215 includes a server interface adapter 213, a relational database 214, and an identification database 216.

  In addition, FIG. 1 illustrates an exemplary method for creating and loading relationship data into a portable media device. 1, a connection is established between a portable media device, a personal computer, and a centralized music information server 100. In one embodiment, the portable media device, personal computer, and centralized music information server There are multiple connections in between. Such communication connections may be wired or wireless, LAN, WAN, WiFi, cellular, satellite, or other means of establishing communications that are now known or become known. In one exemplary embodiment, there is one type of connection between the personal computer and the portable media device, and another type of connection between the personal computer and the centralized music information server. In this way, various types of combinations, components, and configurations for connecting portable media devices, PCs, and centralized music information servers are possible. For example, in FIG. 2, the personal computer 210 interfaces with the centralized music information server 215 through the music management software 212 and the server interface adapter 213. In addition, the personal computer 210 interfaces with the portable music player 205 through the synchronization manager 208 and the portable device manager 204. In one embodiment, the function of the mobile device manager 204 is to synchronize all user media libraries 212 located on the personal computer 210 with media files located on the mobile device 205. In one embodiment, synchronization is achieved by transferring some or all of the media files located on the personal computer to the mobile device.

  1, after the connection is established 100, the playlist data is synchronized between the portable media device and the personal computer 105. In one embodiment, as shown in FIG. The manager 208 manages the transfer of media files from the personal computer 210 to the portable device 205. In addition, the synchronization manager 208 stores the transferred media file. In this way, synchronization manager 208 and portable device manager 204 work together to transfer all media files to portable device 205 and create a list.

  A list of files to be transferred to the mobile device is created 110. That is, a “target list” is created 110. In FIG. 2, the portable device manager 204 and the synchronization manager 208 work in concert with an artist (album, genre, or any of the media files that will be stored on the portable device 205 when the synchronization process is complete. Create a list of other categories).

  1, a list of all artists or media files (target list) is created 110 and the list is transferred from the PC to a centralized music information server 115. In one embodiment, centralized music information. The server is arranged on the Internet or a network. In one embodiment, the server interface adapter processes a request that includes a target list. For example, the name of the artist is specified using an identification database as necessary. In one embodiment, each artist's name is assigned a unique identifier corresponding to that particular artist. Note that referring to relationships based on artist is an example, and many other types of relationships can be used. In another embodiment, each media file may be associated with an album name and / or genre name, or other type of category, in addition to or in addition to the artist's name. For example, in other embodiments, the relationship between one or more media files is based on album, track, rating, user ID, genre, and / or age. Of course, depending on the metadata associated with the file type, the relationship may be formed using other metadata associated with the media file. For example, if the media file is a text article, the metadata includes the author, title, subject, or summary.

  1, the centralized music information server builds relation data between media files in the target list 120. In one embodiment, the relation data is a graph and is stored in a master relation database. Built on the basis. In one embodiment, the graph has a vertex for each unique artist ID (or some other type of ID) and an edge between the associated artists. An edge contains a value called "weight" that encodes the strength of the relationship between the two artists. A set of relationship data can be similarly constructed in other ways as long as the information about the correlation is stored, interpreted and accessed according to the teachings described herein.

  In embodiments that use artist-based relationships, the graph and the mapping of artist names to IDs are transferred in a way that is forwarded over the network and sent to the music management software in response to the original request. Encoded (eg, ordered).

  In another embodiment, relationship data between one or more media files is established on the mobile device itself without using a remote network server or other connected component device. In one embodiment, this is accomplished by forming the relevant data based on the analysis of the media file on the mobile device and then the device itself digitally processes the signal. In another embodiment, the portable device hosts a keep or media file related master database and hosts methods and means for mapping recordings or media files loaded on the portable device against this database. It is clear that there are many possible ways to distribute the processing described in the method of the present disclosure.

  Returning to FIG. 1, a relationship set is constructed 120 (either graphs and maps or any other type) and relationship data is sent 125 to a personal computer. For example, in FIG. 2, the related data is sent from the centralized music information server 215 to the personal computer 210 by interfacing with the server interface adapter 213 and the music management software 212.

  Next, returning to FIG. 1, the server sends the relationship data to the personal computer, which sends the relationship data to the portable device 130. For example, in FIG. 2, the personal computer 210 sends 210 a relational data set to the portable device 205 by interfacing with the portable device manager 204 and the synchronization manager 204. At this time 135, the portable device or portable media player contains a relational data set, and a media file can be selected based on the desired degree of relation, user input, relational data, and media file identity. In one embodiment, the user can select a media file based on the desired degree of relationship, user input, and relationship data as well as the identity of the media file. In one embodiment, the media file is the media file currently playing. In another embodiment, the media file is a media file that is currently paused. In one embodiment, the user can initiate selection and / or playback of these media files on the mobile device using existing user interface buttons or other types of media device input elements or icons. These playback functions are described in more detail below.

  Throughout the disclosure described herein, the functions and methods specified may be performed in hardware, software, firmware, or combinations thereof, and the various described features and functions may be distributed among multiple processors as a matter of choice. It should be understood that they can be integrated into a single device. Thus, features or functions described as being operable on the device may be performed on a personal computer, or the portable device may communicate directly with the server without the personal computer, or may require a server. Instead, the server function may be executed by a personal computer. Further, as will be described in detail below, a self-supporting device capable of autonomously generating relational data performs the features or functions described as being capable of operating with any device. In one aspect, the device receives and / or retrieves relevant processing power and relationship data, invokes a playback function, and selects a media file based on a desired degree of relationship, user input, relationship data, and media file identity. And the ability to select.

Exemplary Embodiments of a Personal Computer-Based Media Device A method for selecting a media file based on a desired degree of relationship, user input, relationship data, and media file identity in a personal computer-based music management system; Another exemplary embodiment of the apparatus and system configuration is shown in FIGS. Examples of personal computer-based music management systems include, but are not limited to, systems sold under the trade names YAHOO! MUSIC ENGINE, MUSICMATCH JUKEBOXWINDOWS® MEDIA PLAYER, APPLE ITUNES, and REAL JUKEBOX. . FIG. 5 illustrates an exemplary method for creating relationship data and loading the relationship data into a personal computer. Further, FIG. 4 illustrates an exemplary system architecture or configuration for creating relationship data and loading it into a personal computer. As shown in FIG. 5, a connection is established 505 between a centralized music information server, a personal computer, at least one audio rendering device, and at least one remote or local input device. In yet another embodiment, a streaming server is connected in the system. In FIG. 4, the system configuration includes a personal computer 210, a centralized music information server 215, a streaming server 440, at least one remote or local input device 430, and at least one or more remote or local audio rendering devices 425. Yes. Specifically, the personal computer 210 includes a media management software user interface 212, an audio rendering function 420, a selection engine 415, and an artist relationship graph 405 (based on some kind of category), an audio library 211, and a streaming library inventory 410. Contains. The centralized music information server 215 further includes a server interface adapter 213, a streaming inventory database 435, a relational database 214, and an identification database 216. It should be noted that the distribution of loads and functions across multiple servers is a convention in a server environment, so that the functions exhibited by a centralized music information server are performed by one or more servers. For example, in FIG. 4, the personal computer 210 is connected to the centralized music information server 215 by interfacing with the media management software 212 of the personal computer-based music management system 212 and the server interface adapter 213. The personal computer 210 is further connected to the streaming server 440 via the media management software 212. In addition, the personal computer 210 is connected to at least one remote or local input device 430 via media management software 212. The personal computer 210 is connected to at least one local or remote input device 430 that provides input events to the media management software 212. Media management software 212 renders audio using the device. Accordingly, the media management software 212 located on the personal computer 210 serves to integrate the components used to play digital audio or media files.

  Returning now to FIG. 5, after an appropriate connection is made 505, the personal computer builds 510 a list of media files, also called a target list. For example, in FIG. 4, the personal computer 210 builds a list of media files via the media management software 212. The media management software 212 then sends a list of artists (or other types of media file related) to the centralized music information server 215 through the server interface adapter 213. In one embodiment, the list consists of artists associated with media files stored locally from the user's library.

  In FIG. 5, the centralized music information server builds 520 a relational data set between the media file and the target list.

  After the relationship data is built 520, the relationship data is sent 525 to the personal computer. For example, in FIG. 4, the centralized music information server 215 sends the relevant data set to the personal computer 210 through the server interface adapter 213 and the media management software 212. Thus, in one embodiment, the centralized music information server can build a relational data set between media files and target lists, assigning this relational data an identifier to each media file and based on that relation. The graph is constructed and sent to the personal computer 210 by sending the artist or media file name and ID graph and map back to the media management software located on the personal computer.

  In another embodiment, if the media management software supports streaming media files and the user accesses streaming content through either a subscription or other access mode, the server may store the user's local library. Although not stored, the relationship with an artist or media file available through a streaming service can be supplemented. This optional stage 530 is also shown in FIG. In one embodiment, based on user-managed settings, the selection engine can choose to select a track or media file from a local library or a track or media file from an available streaming library. . Part or the entire inventory of the streaming library is transferred from the music information server database to the personal computer so that the selection engine can use it. In one embodiment, software located on the PC integrates the selection engine and interactively selects a track or media file for playback based on the data stored in the relationship graph. In one embodiment, the selection engine is located on the user's personal computer. In an alternative embodiment, the selection engine is located at a remote server.

  Returning to the method shown in FIG. 5, the server then sends 525 relevant data to the personal computer, and then regardless of whether the personal computer accesses the media file from a streaming service or from a personal media library. The user engages a personal computer 535 to select a media file based on the desired degree of relationship, user input, relationship data, and media file identity. For example, a user can utilize a playback function based on an artist and / or media file that is currently playing or paused. These playback functions will be described in more detail below.

Exemplary Embodiment of Media Apparatus Another exemplary embodiment of a system configuration and method for loading and / or creating related data into a media apparatus and / or component audio device is shown in FIGS. . FIG. 6 illustrates an exemplary method for creating relationship data and then loading it into a media device. FIG. 6 illustrates a system architecture or configuration 600 of a system for loading and / or creating related data using media equipment and / or component audio device 610. Such media appliances or component audio devices include, but are not limited to, networked component audio devices (digital multimedia receivers) marketed under the trade names such as NETGEAR MP101 and LINKSYS WMSL11.

  FIG. 7 illustrates a 700 connection established between a centralized music information server, a personal computer, and at least one media appliance and / or component audio device. In another embodiment, the component audio device or media device is connected to at least one remote or local input device and at least one external display. As shown in FIG. 6, the exemplary embodiment system configuration 600 includes a personal computer 210, a centralized music information server 215, a component audio device or media device 610, at least one remote or local input device 430, and at least one. Two external displays 605 are provided. As can be seen in FIG. 6, the personal computer 210 further includes music management software 212, a UPNP adapter 650, an audio library 211, and a component audio device gateway 655. The centralized music information server 215 includes a server interface adapter 213, a relational database 214, and an identification database 216. In addition, component audio device 610 includes user input elements or icons such as input buttons 620, display 615, selection engine 625, audio rendering 630, universal plug and play (UPNP) adapter 635, artist relationship graph 640, and audio library inventory. 645.

  In one embodiment, the external display 605 connected to the component audio device 610 or media instrument includes, but is not limited to, a TV, CRT, plasma screen, LCD, or other possible display instrument or Includes methods. In one embodiment, the remote input device 430 or the local input device includes a remote control. For example, as shown in FIG. 6, a component audio device or media device 610 is connected to a personal computer 210 via a universal plug and play (UPNP) adapter 650. In this embodiment, the UPNP adapter 650 obtains a list of media files and forwards the media files to the audio rendering device 630 as needed. Further, the component audio device gateway 655 located on the personal computer 210 interfaces with the centralized music information server 215 and the selection engine 625 located on the component audio device or media device 610.

  Returning to FIG. 7, the personal computer builds 705 a list of media files (target list). As discussed above, in one embodiment, the personal computer builds a target list and synchronizes with the server. The target list is then transferred from the personal computer to the centralized music information server. The server then builds 715 relationship data between the media file and the target list 715. In one embodiment, the relationship data first corresponds to each artist's name or media file to the artist or media file. Constructed by associating with a unique identifier. In one embodiment, this is accomplished using an identification database. Next, a graph is constructed based on the master relationship database. The graph has a vertex between each unique artist or media file ID and the associated artist or media file. An edge contains a value called a “weight” that encodes the strength of the relationship between two artists or media files. The mapping of the graph and artist name to ID is encoded (ordered) so that it can be transferred over the network and sent to the media management software in response to the original request.

  After constructing 715 the relationship data, the server sends 720 the relationship data set to the personal computer, or sends the relationship data directly to the media appliance 730. In one embodiment, the server sends the relationship data set to the personal computer. Send to the media device through the installed gateway program. For example, in FIG. 6, using component audio device gateway 655, server 215 can send the relevant data to component audio device 610. If the server does not send the relationship data directly to the media device or component audio device 730, it sends the relationship data to the personal computer 720, which then sends 725 the relationship data set to the media device.

  Once the relational data set is created and loaded into the component audio device or media device, 725/730, the user can enter the component audio device or device media file into the desired degree of relationship, user input, relationship data, and media file. A selection 735 can be made based on the identity. In one embodiment, as shown in FIG. 6, the media device 610 typically has at least one remote or local input device 430 and an external display 605 so that a user can view media file options. Take the interface.

Streaming Media Appliance Embodiment Another exemplary embodiment of a system and method for selecting media files using a streaming media appliance is shown in FIGS. FIG. 9 illustrates an exemplary method for creating relationship data and loading the relationship data into a personal computer or other type of streaming media device. FIG. 8 illustrates the architecture or configuration of a system for selecting media files using a personal computer or other streaming device 805. Such streaming equipment includes, but is not limited to, items marketed under a trade name such as PHILIPS STREAMIUM. PC-based streaming applications include services such as those sold under the trade names PEAL RHAPSODY, YAHOO! UNLIMITED, and MUSICMATCH ON DEMAND '.

  As shown in FIG. 9a, a connection is established 900 between at least a centralized music information server, a personal computer or streaming device, a streaming server, an input device, and / or an audio rendering device.

  Next, the user invokes 905 a playback function. The personal computer or streaming device then processes 910 the playback function as a request and sends this request to the centralized music information server. As shown in FIG. 8, the system configuration of the exemplary embodiment includes a personal computer or streaming device 805, a centralized music information server 215, a remote or local input device 430, and optionally a remote audio o-rendering device 425. I have. Such remote or local input devices 430 include, but are not limited to, a keyboard, mouse, and / or remote control. Such remote audio rendering device 425 includes, but is not limited to, a home stereo component that is wirelessly connected to a personal computer or streaming device 805. Audio rendering can also be done through directly attached amplifiers and speakers. As can be seen in FIG. 8, the personal computer or streaming device 805 comprises a streaming / interactive radio user interface 810, an audio rendering function 820, and at least one streaming client 815. In this embodiment, audio is streamed from remote server 440. The streaming client component 815 receives the audio stream from the remote server 440 and the rendering component renders the audio 820 to a local or remote amplifier and speaker. The centralized music information server 215 includes at least one server interface adapter 213, a relational database 214, a selection engine 830, and a streaming inventory database 825. For example, in FIG. 8, a personal computer or streaming device 805 facilitates this communication with the centralized music information server 215 through the streaming / interactive radio user interface 810 and the server interface adapter 213.

  Returning now to FIG. 9, the centralized music information server selects the next media file and returns 915 the streaming identifier / instruction to the personal computer or streaming appliance. Next, the personal computer or streaming device uses the identifier / instruction to initiate 920 streaming of the next media file from the streaming server. In this manner, the personal computer or streaming device communicates with the streaming media media server 925. In one embodiment, the streaming is streaming client 815 located on the personal computer or streaming device 805, as shown in FIG. And started by the streaming server 440.

  Returning now to Figure 9, the personal computer or streaming instrument renders 930. In one embodiment, the personal computer or streaming instrument 850 connects to the remote audio rendering device 425, as shown in Figure 8. The audio is rendered through its audio rendering function 820.

  In another exemplary embodiment, the relationship data is created autonomously by a stand-alone device (not shown). In one aspect, the device has appropriate processing capabilities and the ability to receive and / or derive data and playback functions used to create and implement the relevant data. In one exemplary embodiment, the stand-alone device has all the capabilities of the above-described embodiments and needs to be connected to a server and / or connected to another audio rendering device. And / or require a separate display device.

  Regardless of the specific system architecture, configuration, or apparatus described in the exemplary embodiments above, in some embodiments, the method and system for selecting media files is based on relationship data. In another embodiment, the method and system for selecting a media file is based on related data and attributes associated with the media file. Furthermore, provided with the appropriate set of relevant data, those skilled in the art will be aware of various media that are now known or will become known, whether hardware or software, wired or wireless, terrestrial or satellite based. The present invention could be recreated to suit the type and system configuration.

  One aspect of the relationship data is to indicate the degree of relationship. For example, the similarity between one media file and another media file. Thus, one relationship can handle media file A and media file B, and the relationship is defined as the possibility that media file B directly follows media file A, which is the selected media file. In one embodiment, the relationship data is a statistics of these possibilities and other similarities established or determined by analyzing explicit and / or implicit user playlist data among a population of users. Based on. The population may be more or less, from one user to many users, and indeed may include the entire user population of the music service provider. For example, the relationship data is based on recording and analyzing explicit and / or implicit user behavior in on-demand streaming media services. Community sites that encourage users to publish and share playlists are another source of data used to extract relevant data. Media players that report the order of songs played, or playlists created by end users, are another source of this data. E-commerce that sells media, a peer-to-peer application that observes a file that a user requests or downloads, or a music recognition service that observes at least a portion of the contents of a user's media library through a recognition request An application is another possible data source that can be used to generate relational data.

  In one embodiment, the degree of relationship is based on a particular similarity between one or more media files. In one embodiment, the similarity between at least two media files is based on whether the two media files are related to the same or similar genre. In another embodiment, the similarity between at least two media files can be determined by comparing the two media files to playlists, documents, purchasing behavior, explicit user preferences, and / or the user's website or It is based on whether or not it is related by a statistical co-occurrence measure in the dialogue with the service. In another embodiment, the degree of similarity between at least two media files is determined by whether the two media files are playlists, documents, purchasing behavior, explicit user preferences, or observed user websites or services. It is based on whether or not it is related to the artists related by the statistical co-occurrence scale in the dialogue. In another embodiment, the degree of similarity between at least two media files is determined by whether the two media files are playlists, documents, purchasing behavior, explicit user preferences, or observed user websites or services. Based on whether or not it is related to the albums related by the statistical co-occurrence scale in the dialogue. In another embodiment, the similarity between the at least two media files is based on whether the media file is identified as similar by an expert or a careful viewer. In another embodiment, the similarity between at least two media files is based on whether the media file has a similarity attribute understood by the viewer. For example, tempo, mood, and / or rhythmic power or intensity, and / or volume. In another embodiment, the similarity between at least two media files is based on whether the media file has a similarity attribute extracted by an algorithm that analyzes the recording waveform.

  Once the relationship data has been created and loaded into the device, the user can perform playback functions based on the artist and / or media file currently being played. These playback functions allow the user to select media based on the desired degree of relationship, user input, relationship data, and media file identity. Such playback functions include, but are not limited to, a “next” playback function, a “small skip” playback function, and a “large skip” playback function. Furthermore, although playlists are mentioned here, it is not necessary to select a particular playlist or a subset of media files, and the entire available media area may be used as a playlist, part or subset. Good.

  Each of these playback functions or functionality is invoked by user input and is implemented between one or more media files based on either artist, genre, album, track, rating, another user, or chronology The degree of relationship. Accordingly, the playback function called by user input can be correlated with the similarity between media files. Invoking the play function allows the user to select a media file based on the desired degree of relationship, user input, relationship data, and media file identity.

  For example, in one embodiment, the “Next” playback function represents a high degree of similarity between the media file currently playing or paused and the next media file to be played. Yes. Thus, if the user wants the next media file to be very similar to the media file currently playing or paused, the user invokes the “Next” playback function. The method for calling the playback function will be described in more detail below. Furthermore, the “Small Skip” playback function indicates that the similarity between the media file currently being played or paused and the media file to be played next is medium. Thus, if the user wants the next media file to be somewhat similar to the media file currently playing or paused, the user invokes the small skip playback function. Again, the method for calling the playback function will be described in more detail below. Thus, the “Large Skip” playback function indicates that the level of similarity between the currently playing or paused media file and the next played media file is low, ie not similar. Yes. Thus, if the user desires that the next media file is not similar to the media file currently being played, the user invokes the large skip playback function. Again, the method for calling the playback function will be described in more detail below. Of course, there may be many types of playback functions that are related to a particular similarity or based on any kind of relationship built between one or more media files. For example, the device may present the user with a row of knobs or input elements that represent the genre, age, tempo, and artist similarity. Therefore, for example, when the knob is turned a little, the next track similar to the previous track is selected based on the degree. If you turn the knob too much, you will select a track that is not similar to the previous track. In another embodiment, there are multiple skip controls for genre, artist, tempo, etc., making it easier to skip large in the genre while skipping small in the genre. Combinations with other control combinations can also be performed in accordance with the teachings of this specification.

  In one exemplary embodiment, relationship data is created using artist relationships and loaded into the media or device. Of course, any type of relationship may be used, such as genre, album, track, or any other type of category.

  An exemplary state machine for this embodiment is shown in FIG. As can be seen in FIG. 14, the portable media player can be in a playing 1405, paused 1415, or stopped 1410 state. The user selects a media file by playing, stopping, or pausing in the playlist, and performs a playback function such as “Back” 1430, “Next” 1440, “Small Skip” 1435, or “Large Skip” 1445. be able to.

  In one embodiment, the user manually selects 1425 the first media file or track. In an alternative embodiment, the first media file or track is randomly selected 1425.

  In one embodiment, playback state 1405 indicates that the system is playing a media file. From this playback state 1405, the user calls one of the playback functions to select a media file. If the user selects one of the playback functions (Back 1430, Next 1440, Small Skip 1435, or Large Skip 1445), a new media file is selected and the media device will play the new media file. Start. In one embodiment, the audio rendering engine begins playing the media file. In another embodiment, if the user selects play during play state 1405, the system “repositions” the current track and “currently the playlist center”. For example, in an artist-based embodiment, if the system is centered on artist A and playing the artist B with which the system is playing, the system will play the user when artist B is playing. When the button is pressed, the artist B is repositioned around the center, which means that the artist B becomes the current or “center” (center of the playlist). In one embodiment, this means that if the user does not perform the playback function, a certain percentage of tracks from the “center” artist in the playlist is selected and the remaining percentage is “center”. It means that the artist is selected from similar artists.

  In one embodiment, the stop state 1410 is similar to the start state, meaning that no media file is being played. Therefore, a playback event is necessary to start playback of the media file. In one embodiment, the “back” playback function 1430 selects the current track to play again from the beginning, or if the current track has not yet started (or is very close to the start) Play tracks. Further, the “return” playback function 1430 resets the center of the playlist to the artist associated with the selected track.

  As can be seen in FIG. 14, when the media file is playing 1405, the current track ends or the user calls the “next” playback function 1440 and the next playback function logic (FIGS. 16 and 17) is executed and the next track is selected and played 1405.

  Furthermore, when the media file is playing 1405, the user invokes the “Small Skip” playback function 1435 and the small skip playback function logic (FIGS. 16 and 17) is executed to select and play the next track. 1405.

  Therefore, as shown in FIG. 14, when the media file is playing 1405, the user invokes the “large skip” playback function 1445, and the large skip playback function logic (FIGS. 12 and 13) is executed. Are selected and played back 1405. Further, in one embodiment, when the media player transitions from the stopped state 1410 to the play state 1405, the media file history, which is the history that the algorithm prevents the media file from being repeated, is cleared 1450.

  In one embodiment, the system selects the next media file based on the artist at the center of the playlist. In another embodiment, the center of the playlist is the album, genre, track, and era.

  16 and 17 illustrate an exemplary embodiment of logic that supports the following playback functions when the relationship data is based on artist relationships. Specifically, in an embodiment in which the relationship data is created from the artist relationship when the next playback function is selected, the system is the center of the artist's playlist (shown in FIG. 16) as shown in FIG. Select the next artist based on the current artist). Next, as shown in FIG. 17, when the next artist is determined, the system determines which track or media file to select and play from that artist.

  As shown in FIG. 16, the next playback function logic is activated when the user selects the “Next” playback function. As mentioned earlier, the following playback functions are correlated with specific user interface buttons. Alternatively, the “Next” playback function correlates to and is invoked by a specific pattern of pressing a user interface button. For example, the “Next” playback function correlates with pressing the fast-forward button on the user interface of the device or pressing the fast-forward button twice twice or in another pattern. Furthermore, the “Next” playback function is preferably associated with a media file that is very similar to the media file at the center of the current playlist. In FIG. 16, relationships and similarities are based on how artists are related to each other and how similar one artist is to the other.

  First, the user invokes 1600 a “Next” playback function by pressing a designated button or dial, key pattern, or associated key on the device user interface or some other type of input element. In another embodiment, the “Next” playback function is invoked by user input, which may further include a voice activated command. In one embodiment, the “Next” playback function is also automatically invoked on behalf of the user when the currently playing track ends.

  Next, the system determines 1601 whether the current artist is marked empty, i.e., whether the current artist has a track that has not been played. If the current artist is not marked empty, the system creates a random number between 0 and 100 and compares this number to the focus position 1602. This comparison 1602 determines whether the media file should be selected from the current artist or the related artist.

  If the current artist is selected 1608, the system attempts 1700 to select the artist's track and determines 1610 whether the track can be selected. If a track cannot be selected, the artist is marked 1612 as empty, meaning that the artist has no unplayed tracks. Otherwise, a track for playback from the artist is selected 1611.

  If the artist is empty 1612, the system selects 1603 the next related artist for the current artist 1603. Further, if the system determines that the next artist to be selected is the relevant artist and not the current artist, the system reaches 1603 at this stage.

  If a track is selected from related artists, all artists related to the current artist are scored 1606. In one embodiment, the score is generated based on the strength of the relationship with the current artist. (The stronger the relationship, the higher the score) 1606, biased by the recently played history. For example, a related artist played in the last five (and any number of) tracks will score 0.0. In one aspect, this bias ensures that high-scoring artists that have been played in the last five times are not selected again.

  In one embodiment, the weight of the artist relationship graph indicates the rank of the related artist. For example, the most similar artist gets a rank of 1.0, the second most relevant artist gets a rank of 2.0, the next most relevant artist gets a rank of 3.0, etc. To do. In the present embodiment, the reciprocal number (1.0 / rank) is used as the basic score for selecting related artists. Of course, many alternative schemes are possible and considered as configuration or tuning parameters.

  After the relevant artist is scored 1606, the relevant artist and its associated score are added 1607 to the selection list. The process of scoring 1607 artists and adding each score to the selector list 1607 is repeated until all relevant artists have been scored. When the selection list is empty 1612, the system returns a response 1621 indicating that there are no tracks. Once all relevant artists are scored, a random number is generated and applied to the list 1615 so that the probability of selection of an element is proportional to its score relative to other elements in the list. One such technique is to ensure that all scores in the list are not negative. A random number is made between 0.0 and the sum of all scores in the list. The list is repeated until the total score of the repetitive elements is equal to or greater than a random number. The final element of the iteration is selected. One skilled in the art could easily implement this technique or a similar technique that produces the same result.

  Once an artist is determined, the artist's track is selected 1700. When there are no more tracks to select from the artist, the artist is marked 1619 as empty and the artist is removed 1620 from the selection list. FIG. 17 illustrates one exemplary embodiment of track selection logic for an artist-based relationship embodiment.

  17, each track or media file associated with the selected artist is scored 1703. In one embodiment, the track or media file is scored against their popularity attribute. Therefore, the position of the popularity setting determines how the popularity attribute affects the selection probability of a track or media file. The location of popularity is discussed in more detail below.

  Using logic similar to that described with respect to selecting related artists, each track or media file is scored 1703 based on track selection criteria and added 1704 to the selection or selector list. This process (1701-1704) is repeated until all media files or tracks for that particular artist have been scored 1703 and added to the selection list 1704. Next, a weighted random selector selects 1707 the appropriate track. When the artist's last track is selected 1708, the artist is marked as empty 1709 and the track history is updated.

  The selected track or media file and its associated artist are added to the history table 1710, 1711. In one embodiment, the media file or track history table repeats the same media file or track in one session. To prevent it. In another embodiment, the artist history table ensures that various related artists are played. Thus, the history table is used to prevent repetition with the selected media file. In one embodiment, the history table is used for scoring 1703 or artist scoring 1606 for selection. In another embodiment, songs or other attributes of the media file are added to the table to prevent every other playback of the same media file from appearing.

  In another embodiment, a list of the last five sets (or other numbers) of artists played is also maintained. When selecting a relevant artist, if that artist is associated with one of the five most recently played tracks, the artist's score is penalized with 0.0.

  In addition, in one embodiment, a set of all artists played in a session is retained. Specifically, the edges of all artists in the set used are retained. When the next artist is selected, if the relationship candidate is already used, a penalty is added and the selection probability of the repeated edge is lowered. The penalty coefficient for repeated edges is a parameter for the system and is applied to the relationship score as a doubling coefficient. The penalty coefficient of the repetitive edge is 0.0 (maximum penalty) to 1.0 (no penalty). Therefore, when the user calls the playback function, an artist or media file that has already been played is not selected. In one embodiment, when transitioning from stop to playback state, the history is cleared and a new “session” is created.

  In another exemplary embodiment, the logic supporting the “Small Skip” playback function is shown in FIGS. 16 and 17 except that a new artist is always selected and this new artist is the center of the playlist. It is the same as the “Next” playback function logic. As previously mentioned, in embodiments where relationship data is created from artist relationships, when the “Small Skip” playback function is selected, the system will select the next artist based on the center / current artist in the playlist. select. Thereafter, when the next artist is determined (FIG. 16), the system determines which track or media file is selected and played from that artist (FIG. 17), and the selected artist is the new current artist. It becomes.

  In one embodiment, when a user invokes multiple “small skip” playback functions, the user can move through multiple media files in small increments where each step is related to the previous step. Thus, the history mechanism generally prevents the artist from repeating, so the system will cycle through the user's media library or set of media files. Although each track is related to the previous track, the current track will be far away from the starting track after multiple skips.

  In one embodiment, in contrast to the “small skip” playback function, the purpose of the “large skip” playback function is to select a track or media file that is irrelevant or not similar to the track currently playing. is there. In one embodiment, the relationship data score used to determine all items related to all other items is reversed from the logic of the “next” playback function. Therefore, the logic of the large skip is the same as that shown in FIGS. 16 and 17 except that the relationship score (1606 in FIG. 16) is reversed. In this way, tracks are selected according to dissimilar artists.

  In one embodiment, if the relationship data is incomplete, that is, each artist in the relationship graph is only directly connected to a subset of all artists in the graph, the traversal algorithm of the “shortest path” graph is , Used to calculate the distance between any two artists. For example, the Dijkstra shortest path algorithm is well known to those skilled in the art and can be used for this purpose. Often, however, the Dijkstra algorithm is extremely weak in the relationship between the second and third ranks compared to the relationship in the first rank. In one embodiment, the solution is to store only the above N relationships for each artist and create a relationship graph that includes a uniform weight (eg, 1.0). In this embodiment, the shortest path algorithm calculates the number of playback functions that are called to obtain artist B from artist A. This is the basis for the score used to select the appropriate artist for the “big skip” playback function.

  In another embodiment, an alternative to the “big skip” playback function is to use a “genre-based” playback function. The “genre based” playback function uses the same relationship / graph based algorithm discussed in the above embodiment. In one aspect, a genre is a label placed on a set of artists, albums, or tracks with which the theme is related. The genre is determined by grouping elements constituting the genre. Usually, however, human experts create genres by categorizing based on style, roots, peers, and influence.

  In one exemplary embodiment, the genre consists of a label and an artist rating set. The rating of the artist in the genre is determined by the “fitness” of the artist to the genre.

  In addition, artists within a genre are rated by looking at the artist's relationships and scores based on how many of the artists involved are in the set defined by the genre.

  Alternative embodiments of the present disclosure define genres in terms of albums, tracks, or other set of records. For example, other types of media, such as the television domain, use the channel as a genre for programs that appear on the channel. In one embodiment, the relationship graph is constructed for a set of genres. In the case of music and artist-based genres, the strength of the relationship is defined by the number of common artists. In another embodiment, genres are rated by the number of common artists, and that rating becomes the weight of the relationship graph.

  In yet another alternative embodiment, subgenres and supergenres are also used to define relationships and relationship data. In this embodiment, the sub-genre is classified under the super genre. Where hierarchical classification of content can be used, different sized skips or moves from one media file to another media file up one or more levels of the tree as shown in FIG. This is realized by going to, moving in the horizontal direction and going down again. The hierarchy (tree) organization of the genre 1100 is as shown in FIG. In this tree 1100, a number of playback functions such as “small skip”, “medium skip”, and “large skip” are executed. Further, the sub genre is represented by items such as 1118, 1111, 1113, 1105, and 1122, and the super genre is represented by items such as 1112, 1119, and 1121, and the root of the genre tree. Is represented by item 1120. FIG. 11 shows an example of how these playback functions allow the user to select media files based in part on genre relationships.

  Specifically, in FIG. 11, the “small skip” playback function is indicated by a thick solid line 1107. As shown in FIG. 11, when the user invokes the “small skip” playback function within the genre-based hierarchy, the thick solid line 1107 goes up to the parent node and goes down to different artists in the same sub-genre. In one embodiment, the “small skip” playback function represents a medium level of similarity between the media file currently playing and the next media file to be played. For example, in FIG. 11, in consideration of the artist Mandy Moore 1106 that is currently being played, calling the “Skip small” playback function selects Britney Spears 1109 as the next media file. As can be seen in FIG. 11, a thick solid line 1107 representing the “small skip” playback function 1107 begins at artist Mandy Moore 1106, moves to parent node Teen Pop 1118, and then descends to a different artist Britney Spears 1109.

  Similarly, in FIG. 11, the middle skip playback function is indicated by a dotted line 1115. As shown in FIG. 11, when the user invokes the “medium skip” playback function in the genre-based hierarchy, the dotted line 1115 goes up two levels (subgenre and certain genre) in the tree, and then goes down two levels. To another artist. In one embodiment, the “medium skip” playback function is a medium level similarity between the currently playing media file and the next played media file (the “small skip” described in this embodiment). (Compared to “large skip”). For example, in FIG. 11, considering the currently playing Kilie Minogue 1110, calling the “medium skip” playback function will select Abba 1114 as the next artist file. As can be seen in FIG. 11, the dotted line 1115 representing the “medium skip” playback function begins with the artist Kylie Minogue 1110 and moves to the two parent nodes Dance Pop 1111 and Pop 1112, and then different from the two different nodes, Euro Pop 1113. Go down to artist Abba1109.

  Further, in FIG. 11, the “large skip” playback function is indicated by a broken line 1117. As shown in FIG. 11, when the user invokes the “Large Skip” playback function within the genre-based hierarchy, the dashed line 1117 goes up three levels in the tree and then goes down three levels to another artist.

  In one embodiment, the “big skip” playback function is a low level of similarity or dissimilarity between the currently playing or paused media file and the next selected media file (described in this embodiment). Compared to “small skip” and “medium skip”. For example, considering artist Aweosmith 1116 currently playing in FIG. 11, Diana Krall 1123 is selected as the next media file when the “Large Skip” playback function is called. As can be seen in FIG. 11, the dashed line 1117 representing the “Large Skip” playback function 1117 begins with the artist Aerosmith 1116 and climbs the three parent nodes Album Rock 1105, Rock 1119, and All Genres 1120, after which two different nodes Jazz 1121 and Swing 1122 are added. Go down to the different artist Diana Krall 1123.

  An exemplary embodiment of logic that supports a “big skip” playback function using a genre-based relationship is shown in FIG. First, the logic of the “Large Skip” playback function is invoked 1200 by the user via the existing user interface of the device. Next, the currently playing artist is mapped 1201 to the genre, hi one embodiment, the currently playing artist is mapped to the genre using an artist-to-genre map. For example, artist-to-genre mapping comes from the central music database and is stored as part of the artist relationship graph. Therefore, the genre is also stored for each artist in the graph. The genre of the current artist is called the current genre.

  For each genre, a score is calculated based on the strength of the relationship between itself and the current genre. Once the genre score is calculated 1205, the genre / score pair is added 1206 to the selection list. This process (1202-1206) continues until all genres are scored and added to the selection list. Thus, the algorithm loops through all genres related to the current genre. In one embodiment, genre relationships are obtained along with artist relationships from a centralized music information server relationship database.

  In one embodiment, a score of 9 is associated with the reciprocal of the strength of the relationship for the “Large Skip” playback function. That is, the same genre has a small score and a low selection probability. Such a score is scored as a rating of the relationship or 1000 if there is no relationship between genres. You can calculate your score in many other ways. In another embodiment, for genre-based “medium skip” playback functions, the options are strongly biased towards the genre concerned. That is, the reciprocal of the “Large Skip” scoring method, 1.0 / relational rating, can be used.

  All genres are scored 1205 and added to the selection list 1206, and the genre is selected from the selection list 1209 with the selection probability divided by the total of all the genre scores added to the selector. . If there are no eligible genres, the selection list is empty 1207 and a “no track” status is returned 1208.

  A genre is selected 1209 and an artist and track are selected 1210 from the genre. An exemplary embodiment 1210 of selecting genre artists and tracks is shown in more detail in FIG. If an artist / track cannot be selected for a genre 1211, the genre is marked as empty 1213 and removed 1214 from the selection list. Genre selection is rejected until a track is found 1212 or all genres are empty.

  FIG. 13 illustrates an exemplary embodiment for selecting artists and tracks when a genre is selected as shown in FIG. Specifically, FIG. 13 illustrates exemplary logic for supporting artist and track selection with the “big skip” playback function using a genre-based relationship.

  In one embodiment, each artist is scored 1304 based on each artist's “fitness” for the current genre, In one embodiment, the “fitness” is the set of artists in the genre, and Based on the common size of a set of artists that are related to a given artist. In an alternative embodiment, the score is based on the artist's popularity as measured by the “fitness” distance.

  The artist's score is calculated 1304 and the artist / score pair is added 1305 to the selection list. This process (1301-1305) continues until all artists have been scored and added to the selector list. That is, the algorithm loops over all artists associated with the selected genre.

  All eligible artists are scored 1304 and added 1305 to the selector list, and the selection probability is the artist's score divided by the sum of all the artists added to the selector list. Is selected 1307.

  An artist is selected 1307 and the artist's track is selected 1700, as described above and shown in FIG. If there is no eligible track for that artist, 1309, the artist is marked as empty 1310, removed from the selector or selection list 1311, and a new artist is selected. If all eligible artists are empty 1306, a “no track” status is returned 1313.

  Thus, in one embodiment, a user can select a media file by invoking a series of playback functions and combinations of playback functions as described above. That is, when the user invokes a number of playback functions through user input, the user can select a media based on the first media file and the playback function that represents the degree of relationship between the first media file and the selected media file. A file is selected. In this way, the user can move a plurality of media files in designated increments, with each stage related to the previous stage, depending on the playback function invoked.

  FIG. 3 illustrates an exemplary embodiment of a selection engine interface showing the navigation path of a session constrained to the contents of a local library of approximately 2000 media files. The artist base relationship is used for small skips as shown in FIGS. 16-17. The genre-based relationship is used for the middle skip and the large skip shown in FIGS. As previously mentioned, in one embodiment, the device keeps track that has been played and skipped, avoiding repeated tracks. As can be seen in FIG. 3, a tab 310 with a large window frame 300 has a text box 305 showing a starting artist 315, a button 313 with the term “random”, a “back” button 380, and a “play”. A button 390, a “next” button 303, a “stop” button 309, a “small skip” button 385, a “medium skip” button 395, and a “large skip” button 307 are displayed. . In FIG. 3, the window pane 300 includes a list of artists and associated tracks (items 315-375). In this list, the playback function is shown in parentheses before each artist entry. In this way, the list of artists in the window pane includes not only the artist name and media file title for the starting artist 315, but also the associated playback function that was invoked by the user prior to the selection of that media file. Show. Therefore, the window frame 300 shows the navigation route of a specific session. The order and selection of playback functions invoked by the user and the media file selected in a particular session.

  For example, in FIG. 3, Clash is the starting artist 315. As can be seen in window pane 300, Clash is listed 315, before which the term “Play” appears in parentheses, and Clash activates the playback function or user input session by the user pressing the “Play” button. Indicates the first artist selected when starting. The next playback function called by the user is the “Large Skip” playback function 307, which selected artist M.C.Hammer and the track “Pray320”. That is, the user selects the “Big Skip” playback function, which means that the user wants the artist of the next media file not to be similar to the artist Clash 315 currently playing. . Therefore, as can be seen in FIG. 3, M.C.Hammer 320, an artist not similar to Clash 315, was selected.

  The user then invoked a series of “Big Skip” playback functions 320-355, each rendering a media file with an artist that was not similar to the previous media file. In another example, Diana Krall “Deed I Do” 355 was a currently playing artist and track. Next, the user calls the “Small Skip” playback function and the artist Charlie Christian and the track “I found a new baby” 360 are selected. Thus, by calling the “Small Skip” playback function, the user was able to move from one artist to a somewhat similar artist.

  Similarly, FIG. 10 shows session navigation when constrained by a large streaming service catalog containing hundreds of thousands of tracks. In one embodiment, artist-based relationships are used for the small skips shown in FIGS. 16-17, and genre-based relationships are used for the medium and large skips shown in FIGS. 12-13.

  As can be seen in FIG. 10, the tab 1000 having a large window frame 1003 includes a text box 1001 indicating a start artist 1010, a “back” button 1004, a “play” button 1006, a “next” button 1008, A “stop” button 1027, a “small skip” button 1005, a “medium skip” button 1007, and a “large skip” button 1009 are displayed.

  In FIG. 10, the window pane 1003 includes a list of artists in the session and associated tracks (items with numbers 1011-1026). As can be seen in FIG. 10, the session begins with Rage against the machine 1010, the starting artist. The user then called the “Large Skip” playback function and selected the track media files for artists Bezerra Da Silva and Malandragem Daum Tempo 1012. That is, as can be seen from the navigation list in the window frame 1003, the artist currently playing is Rage against the machine 1010, and then the user wants a genre that is not similar, so the “big skip” playback function And a genre artist and track that is not similar to the artist currently playing is selected (using the logic shown in FIGS. 12-13). Specifically, since the media file 1011 currently being played was a heavy metal genre, the “large skip” playback function selected a media file Salsa 1012 of a genre that was not similar. As can be seen in FIG. 10, the user continues to select a media file using the “Large Skip”, “Medium Skip” and “Small Skip” playback functions, and for the media file currently playing or paused The next media file was selected based on the genre-based similarity level. For example, in one embodiment, the media file currently being played by the media files in the bop genre, Miles Davis, Blue in Green 1017, and then the user calls the “medium skip” playback function to create a smooth jazz genre. Boney James, Ain't No Sunchine 1018 belonging to Thus, by invoking the “middle skip” playback function, the user was able to move from the Bop category to smooth jazz with a somewhat similar category.

  Thus, the user can move and focus on a particular media file using a series of playback functions and combinations of playback functions. The user does not need to know in advance which specific file he wants, and uses the play function to request and select a media file, very similar to the media file currently playing or paused. A media file can be selected that is similar, somewhat similar, or dissimilar. In one embodiment, the user can select a media file with a simple interface.

  However, in another embodiment, the feedback is essentially audible. Thus, the present disclosure is well suited for use in automobiles. Further, with such settings, the user can select a media file and invoke the playback function via the remote control or fob.

  In another embodiment, the user can further format or customize the relationship data through one or more settings. In one embodiment, the user can set these settings before creating the relationship data and / or loading the relationship data into the device. Thus, the settings are applied during the creation and loading of the relationship data. In another embodiment, these settings have default criteria.

  In one embodiment, the user is available on the device user interface as a software plug-in tool or some other graphical user interface that allows the user to select and specify one or more settings. You can specify these settings through various property sheets.

  One exemplary embodiment of the setting is a focus setting. For example, the focus setting is displayed on the user interface as a visual representation of a slider or series of radio buttons, dials, drop-down menus, or some other setting. In one aspect, the focus setting biases the selection of the media file relative to the media file currently being played. For example, the focus slider biases the selection of media files for the artist, album, or track that is currently playing. That is, the focus setting determines the general likelihood that the next media file is the item most closely associated with the artist, album, or track currently being played. For example, the focus setting range is 0 to 100. A setting of 100 indicates that media files are generally selected in the order of their relationship to the media file currently being played. For example, if the artist currently playing is Rolling Stones and the focus setting is set to 100, only media files from Rolling Stones are selected.

  Similarly, setting 0 indicates that a media file related to (but not identical to) the media file currently being played is selected. For example, here too, if the artist currently playing is Rolling Stones and the focus setting is set to 0, only the media files of the artists related to Rolling Stones are selected.

  Another exemplary setting embodiment is a popularity setting. Again, through the user interface, the popularity setting can take many forms such as, but not limited to, a slider, a dial, a series of radio buttons, and / or a drop-down menu. In one embodiment, the popularity setting biases the selection of the media file relative to the media file that is currently playing or paused. A setting of 100 indicates that the most popular track is selected for the media file currently being played. Also, in one embodiment, the media file choices for the media file currently being played include a set of relationships based on artist relationships, album relationships, genres, and / or age relationships.

  In one embodiment, the popularity is based on relationship or similarity data between media files. In one embodiment where media file selection is based on artist relationships, the popularity setting determines the track or media selection associated with a particular artist.

  The popularity attribute of a particular track or media file is based on several sources, such as implicit and explicit user behavior or ratings, and / or implicit and explicit data collected from a large group of users Is being collected. One example of implicit user behavior or input is the frequency of playback for a particular media file by the user. Therefore, the frequency of playback is used to determine the popularity attribute. One example of explicit user data is a rating that a user assigns to a track or media file. For example, the rating system is based on 1 to 5 stars, where 1 star indicates a low or unfavorable rating, 3 stars indicates an intermediate or favorable rating, 5 stars is high or It may be something that shows a very favorable rating. In one embodiment, when data is collected from a large group of users, the total popularity data is normalized to a 1 to 5 star rating. Tracks are rated relative to each other. For example, the top 10% media files are media files rated at 5 stars. The next 15% of media files have a 4 star rating. The middle 50% is a 3 star rating. The next 15% of media files are rated 2 stars, and the bottom 10% of media files are rated 1 star.

In one embodiment, the system uses the available data to determine the popularity attribute from hierarchical processing. One exemplary process for determining the popularity attribute of each media file is shown in FIG. This process ensures that each media file is assigned a popularity rating. In FIG. 15, the system determines 1505 whether an explicit user rating is available for a particular media file. An explicit user rating can be consciously assigned to the media file by the user. If an explicit user rating is available, the system assigns 1510 this rating to a particular media file. If an explicit user rating is not available, the system determines 1515 whether the total popularity collected from multiple users is available 1515. In one embodiment, "multiple users" are on-demand, Refers to users of a streaming music service or similar online community. If the total popularity attribute is available, the system assigns 1520 this attribute or rating to the media file. If total popularity data from a large number of users is not available, the system determines 1525 whether a popularity attribute based on the user's playback frequency is available. If this data is available, the system assigns 1530 this popularity attribute or rating to the media file. If the frequency of the playback popularity attribute is not available, the system assigns 1535 a default popularity attribute or rating to the media file. For example, the default popularity attribute is an average rating such as 3.0 with a rating point of 1 to 5 stars. When the popularity attribute is assigned to all media files, the setting position of the popularity setting is used to determine an appropriate scoring function. For example, Table 1 below shows an exemplary table associating popularity settings with scoring functions. In this table, the probability assumes that 10% of the population is 5 stars, 15% is 4 stars, 15% is 2 stars and 10% is 1 star. It is shown.
Table 1

  Similarly, a setting of 0 indicates that the least popular track is selected. This allows the user to play media files that are generally less well known from the central area (artist, album, track, genre, and / or age) of a particular playlist.

  Thus, the focus and popularity settings have choices ranging from 0 to 100. For example, in an artist-based embodiment, if the focus setting is set to 75, the system will select a media file from the artist currently playing for 75% of the time, Select the media file from the related artists (for the artist who is).

  Further, in one embodiment, the user selects a setting with both a focus and popularity setting. This allows the user to format or customize the media files available for selection based on a specified level of popularity and dissimilarity with respect to the media file currently being played.

  As previously mentioned, once the relevant data has been created and / or loaded into the device, the user can invoke any number of playback functions. In general, the user invokes these playback functions by user input or using the existing user interface of the device. For example, in one embodiment, each playback function is associated with a key pattern on a button, key, dial, switch, touch screen, or device user interface. For example, FIG. 18 illustrates a user interface of one exemplary embodiment. As can be seen in FIG. 18, the user interface consists of a wheel or dial 1805 with a fast forward icon 1810, a rewind icon 1820, and a pause, play or stop icon 1815. FIG. 19 illustrates another wheel or dial user interface 1805 of another exemplary embodiment with similar icons.

  In another example, most media rendering devices include a fast forward icon, a rewind icon, and a play or pause icon. FIG. 20 illustrates one exemplary embodiment of icons used to invoke the playback function. As can be seen in FIG. 20, FIG. 20a shows a rewind icon, FIG. 20b shows a fast forward icon, and FIG. 20c shows a pause or play icon. Thus, in one example, the “Next” playback function is invoked by pressing the fast forward button (FIG. 20b), and the “Small Skip” playback function is invoked by quickly double-clicking the fast forward (FIG. 20b) button. The “Large Skip” playback function is invoked by pressing and releasing the fast forward button (FIG. 20b) for at least one second. In this way, once the relationship is created and / or loaded into the device, the user can use the device's existing user interface based on the desired degree of relationship, user input, relationship data, and media file identity. Media files can be selected.

  It is important to note that this disclosure does not rely on a specific implementation of user interface elements to skip and invoke playback functions. It does not depend on the two skips described as small skip and large skip. For example, if the portable device has a wheel or dial-based scroll mechanism, a suitable implementation of the present disclosure is to map the speed or distance traveled by the wheel or dial scroll to the magnitude of the skip performed. One exemplary embodiment of a dial-based user interface is shown in FIGS. That is, the user can use the “Next”, “Small Skip” and “Large Skip” playback functions, and these interactive functions for the track or media file currently playing or paused, to the specific rotation of the wheel or dial. Or by correlating with the rotational speed. For example, if the user moves the wheel or dial 45 degrees in a direction, it is correlated with the “Next” playback function. Thus, when the user moves the dial 45 degrees, the user is transmitting that he wants to play a track or media file that is closely related to the media file currently being played. .

  Furthermore, the 90 degree rotation of the dial correlates with the “small skip” playback function. Thus, when the user rotates the scroll-based dial 90 degrees, the user wants to select an artist that is somewhat related to the artist that is currently playing or paused. Notifying or sending. Finally, if the user wishes to invoke the “Large Skip” playback function, the user rotates the scroll-based dial 180 degrees. It will send when the user wants to select something that is very different from or not exactly the same as the currently playing artist.

  Of course, the specific keys, buttons, icons, or dials associated with each playback function will depend on the specific device. In fact, a device with a single user input or icon element can be used, for example a device whose entire user interface is a skip button or icon.

  As described above, a method, apparatus, and system for selecting a media file based on a desired degree of relationship, user input, relationship data, and media file identity of an external device include a portable music player and a media file. As well as video, DVDR, satellite or on-demand programming and other types of devices capable of playing media. Thus, in one embodiment, it also applies to television programming, and the effect is that pressing a certain button on the remote control changes the next channel or program so that the user can Based on this relationship, the next channel or program can be selected. For example, in one exemplary embodiment applied to TV programming and video files, the list of programs is synchronized with a personal computer, which sends it to the server. Again, the server activates a list of relationships or relationships between these programs. Those relationships listed may be based on genre, playback date, playback time, similar performer, similar channel, rating. When the server creates this list as relational data between media programs, it sends it back to the personal computer, which is loaded into the on-demand video programming service. The user then invokes the playback function by pressing a particular button on the remote control or some other user input. For example, if a user is watching a media program and hits a button that invokes a “next” playback function, the channel will change to a television program very similar to the previous television program. Again, these playback functions are invoked by a button such as a fast forward button on the remote control, a button such as an UP / DOWN button, or any button located on an existing interface for a television program or on-demand program device.

  In another embodiment, this relationship data may be stored on a minimal display or essentially a device with no display, or a CD in an MP3 player or car if it is not practical for the user to select a media file through the display. It is considered to be loaded into a device such as a player. In this way, once loaded into these types of devices, media file control and selection can be done with playback functions such as “next”, “small skip” or “large skip”, or “yes” “no” Can be facilitated through voice commands, remote control, fob that will have different keys corresponding to other types of playback functions such as “but close to it” and “no, not close” ing. For example, in a key fob with at least one button, a possible mapping is to call the play function or stop function if the button is pressed and held and the playlist is currently playing. When the button is pressed once, the “next” playback function is called, when the button is pressed twice, the “small skip” playback function is called, and when the third floor is pressed, the “large skip” playback function is called.

  In another example, such as a device with an iPOD or similar key / button arrangement, where the buttons point to the north, east, south, and west directions, each direction is correlated to a particular playback function. Or is mapped to a specific playback function or calls a specific playback function. For example, pressing the north direction invokes the “Large” playback function. Pressing the south direction invokes the “Small Skip” playback function. Press east to call the “Next” playback function. When the west direction is pressed, the “return” playback function is called. Furthermore, when the center is pressed, the playlist is called and the current track is reset to the center.

  The method and system can be applied to a wide range of media devices, such as car audio systems, consumer electronic devices, mobile phones, software programs running on personal computers, and any other device that can play media files. it can. The method and system are particularly applicable to portable media players.

  As will be appreciated by those skilled in the art, the method and system of the present invention can be implemented in many ways, such as, but not limited to, the exemplary embodiments and examples described above. it can. In other words, the functional elements are executed in various combinations of hardware and software by one or more individual elements, and the individual functions are distributed among the software applications at either the client or server level. Can do. In this regard, any number of features of the different embodiments described herein may be combined into one embodiment, or, as an alternative embodiment, fewer than all the features described herein. There can be many things. Functionality may also be distributed, in whole or in part, among multiple components in a manner that is now known or becomes known. Thus, innumerable software / hardware / firmware combinations are possible in realizing the functions, features, interfaces, and preferences described herein. Further, as will be appreciated by those skilled in the art, the scope of the present invention encompasses conventionally known features, and changes and modifications thereof, through the system components described herein.

6 is a flowchart illustrating an exemplary method for creating and / or loading relationship data into a mobile device. Fig. 2 illustrates an exemplary system configuration or architecture for creating and / or loading related data into a mobile device. Fig. 4 illustrates a navigation path of an exemplary embodiment. 1 illustrates an exemplary system configuration or architecture for creating and / or loading relationship data into a personal computer based media device. 6 is a flowchart illustrating an exemplary method for creating and / or loading relationship data into a personal computer based media device. FIG. 4 illustrates an example system configuration or architecture for creating and / or loading related data into a media device. 6 is a flowchart illustrating an exemplary method for creating and / or loading relationship data into a media device. 1 illustrates an exemplary system configuration or architecture for creating and / or loading related data into a streaming media device. 6 is a flowchart illustrating an exemplary method for creating and / or loading relationship data into a streaming media device. Fig. 4 illustrates a navigation path of an exemplary embodiment. It shows an organized tree created in a genre-based relationship. FIG. 6 illustrates an exemplary embodiment of artist selection logic that supports large skip playback functionality using genre-based relationships. 6 is a flowchart illustrating an exemplary embodiment of track selection logic that supports large skip playback functionality using genre-based relationships. 1 illustrates a state machine of one exemplary embodiment. 6 is a flow chart for illustrating popularity attribute determination in an exemplary embodiment. Fig. 4 illustrates an exemplary embodiment of artist selection logic that supports playback functionality using artist-based relationships. 6 is a flow chart illustrating an exemplary embodiment of track selection logic that supports playback functionality using artist-based relationships. 2 illustrates a user interface of an exemplary embodiment. 2 illustrates a user interface of an exemplary embodiment. Fig. 3 illustrates an icon of an exemplary embodiment.

Claims (72)

In the media device,
Data indicating the degree of relationship between multiple media files;
A user interface with user input elements;
A first element operative to receive user input indicating a desired degree of relationship and a desire to identify a second media file of the plurality of media files;
A second element that serves to identify a first media file of the plurality of media files;
And a third element that serves to identify the second media file according to the desired degree of relationship and the identity of the first media file.   The media device according to claim 1, wherein the data is autonomously created by the media device.   The media device of claim 1, wherein the data is received from at least one of a remote database and a remote media device.   The media device of claim 1, further comprising a fourth element operative to play the second media file.   The media device of claim 1, further comprising a communication element for communicating with a remote database.   6. The media device of claim 5, wherein the communication is for synchronizing the data between the media device and the remote database.   The media device of claim 1, wherein the data is based on a statistical co-occurrence measure of a particular set of media files of the plurality of media files. The data is
A user's playback history of the plurality of media files;
The media device of claim 1, wherein the media device is established by analyzing at least one of a playlist constructed by a user of the plurality of media files.   The media device of claim 1, wherein the data is based on at least one of an explicit user preference and an observed user behavior.   The media device of claim 1, wherein the media file is represented by a geometric vector and the data is based on a geometric comparison of the vectors.   The media device according to claim 10, wherein the geometric comparison is an inner product operation.   The media device of claim 10, wherein the geometric comparison is a calculation of a distance between the vectors.   The media device of claim 1, wherein the data is stored as a graph in which the media files are related to vertices of a graph and the edges of the graph indicate relationships between the media files.   The media device according to claim 13, wherein the edge includes a weight corresponding to the strength of the relationship. The data is
Waveforms of the plurality of media files;
The media device of claim 1, established by analyzing at least one of a statistical co-occurrence measure of the plurality of media files of a published document.   The media device of claim 1, wherein the data is established by similarity of attributes associated with the plurality of media files.   The media device of claim 1, wherein the media device is characterized as a portable media player, a personal computer based media player, a mobile phone, or a streaming device.   The media apparatus according to claim 1, wherein the degree of relation correlates with a degree of similarity, and is a medium degree of similarity, a high degree of similarity, or a low degree of similarity.   The media device of claim 1, wherein the user input comprises a selection of at least one component of the input element.   The media device according to claim 19, wherein the component is a key, a button, or a dial.   The media device of claim 1, wherein the user input element is configured to receive a voice command.   The media device of claim 1, wherein at least one of the first media file and the second media file is an audio file.   The media device of claim 1, wherein at least one of the first media file and the second media file is a video file.   The user interface includes a user-interactable indicia representing a file-specific operation from the plurality of media files, wherein the specification is a selection of a next media file that the user will experience when interacting with the indicia. Is associated with the indicia to signal a program that causes the program to be based on the desired degree of relationship between the first media file and the other files of the plurality of media files. The media device according to claim 1, wherein the selection is performed.   The media device of claim 24, wherein the indicia includes a skip icon.   The media device of claim 24, wherein the indicia includes a key, button, or dial. The media device is characterized as a media player;
The user interface is a user interface for instructing the media player to stop a currently playing media file and to receive a skip command for playing an alternative media file selected from the plurality of media files. The skip command is based on the degree of relationship,
The media device further comprises:
A storage device for holding the data;
The media device of claim 1, comprising: software responsive to the user interface element to select the alternative media file in accordance with the degree of relationship, the media file currently being played, and the skip command. In a portable media player for interactive playback of media files,
A storage device for media files and data indicating the relationship between the media files;
Receiving an event for starting a skip having a certain size, and selecting software for selecting a next media file to play based on the skip size;
A player in which the size of the skip and the relationship between the current media file and a selectable alternative media file affect the likelihood of selecting one of the alternative media files as the next media file. A database system containing information used to identify media files and relationships between media files;
A communication unit for connecting to one or more computer devices,
29. The player of claim 28, wherein relationships between media files are transferred from one or more of the computing devices to the portable media player.   30. The player of claim 29, wherein the player allows a connected computing device to manage the media file stored on the device.   A software module for facilitating connection to the remote database system so that the media player is connected to the remote database system such that related data is transferred from the remote database system to the computing device. 30. The player of claim 29. In the method of selecting media,
Recognizing the identity of a first media file of the plurality of media files;
Receiving user input indicating a desired degree of relationship and a desire to select a second media file of the plurality of media files;
Accessing relationship data indicating a degree of relationship between media files of the plurality of media files;
Selecting the second media file according to the desired degree of relationship, the user input, the relationship data, and the identity of the first media file.   The method of claim 32, wherein the relationship data is created autonomously by a media device.   The method of claim 32, wherein the relationship data is communicated from a remote database system. Recognizing the identity of the second media file;
Receiving user input indicating a desired degree of relationship and a desire to select a third media file of the plurality of media files;
The method of claim 32, further comprising selecting the third media file according to the desired degree of relationship and the identity of the second media file.   33. The method of claim 32, wherein the identity of the first media file includes at least one of an artist name associated with the media file and a genre associated with the media file.   35. The method of claim 32, wherein the relationship data is based on a statistical co-occurrence measure of media files within a particular set of media files of the plurality of media files.   38. The method of claim 37, wherein the set of media files is characterized as a playlist or a media library. The relationship data is
A user's playback history of the plurality of media files;
A playlist constructed by users of the plurality of media files;
Waveforms of the plurality of media files;
35. The method of claim 32, established by analyzing at least one of a statistical co-occurrence measure of the plurality of media files of a published document.   The method of claim 32, wherein the relationship data is established by similarity of attributes associated with the plurality of media files.   35. The method of claim 32, wherein the relationship data is based on at least one of explicit user preferences and observed user behavior.   The method of claim 32, wherein the degree of relationship is correlated with a degree of similarity between the first media file and at least one other media file of the plurality of media files.   35. The method of claim 32, wherein the relationship data between one or more media files of the plurality of media files is established by human determination.   44. The method of claim 43, wherein the human judgment includes a classification of the media file.   The method of claim 32, wherein the media file is represented by a geometric vector and the degree of relationship is determined by a geometric comparison of the vectors.   46. The method of claim 45, wherein the geometric comparison is an inner product operation.   46. The method of claim 45, wherein the geometric comparison is a calculation of a distance between the vectors.   The method of claim 32, wherein the relationship data is stored as a graph in which the media files are related to vertices of a graph and edges indicate relationships between the media files.   49. The method of claim 48, wherein the edge includes a weight corresponding to the strength of the relationship.   35. The method of claim 32, wherein the user input is received via an input element that is a skip icon located on a device user interface.   51. The method of claim 50, wherein the input element is selectable by a user once touching the user interface of the device.   The method of claim 32, wherein the user input includes at least one user interaction with an input element.   The method of claim 32, wherein the input element is activated by voice. The media file is characterized as a recording for playback, and a set of relationships associates the recording with
The first media file is characterized as a current recording;
The second media file is characterized as a new recording;
The receiving step further comprises receiving an event that triggers the selection of the new recording for playback, the event being related to magnitude,
The selecting step further includes selecting the new recording for playback based on the size and the set of relationships, the size being selectable with the current recording. 35. The method of claim 32, combined with relationships between different recordings, to influence the possibility of selection.   55. The method of claim 54, wherein the recording is a digital audio file.   55. The method of claim 54, wherein the set of relationships is defined in terms of similarity of the recordings. The similarity of the recordings is
A user's playback history of the recording,
Playlists built by users,
The waveform of the recording,
57. The method of claim 56, established by analyzing at least one of the recorded document co-occurrence of a published document. The similarity of the recordings is
The similarity of the recordings associated with the artist,
Human judgment,
57. The method of claim 56, established by at least one of attribute similarities associated with the recording.   55. The method of claim 54, wherein the recording is represented by a geometric vector and the strength of the relationship is determined by a geometric comparison of the vectors.   60. The method of claim 59, wherein the geometric comparison is an inner product operation.   60. The method of claim 59, wherein the geometric comparison is a calculation of a distance between the vectors.   55. The method of claim 54, wherein the relationship is stored as a graph in which recordings are related to vertices of the graph and edges represent the set of relationships between recordings.   64. The method of claim 62, wherein the edge includes a weight corresponding to the strength of the relationship. Recognizing a value of a first attribute of the first media file;
Selecting a second attribute value according to the desired degree of relationship, the user input, the relationship data, and the first attribute value;
The accessing step further includes accessing relation data indicating a degree of relation between values of the first attribute of the media file in the plurality of media files;
36. The method of claim 32, wherein the step of selecting the second media file is performed according to the selected second attribute value.   65. The method of claim 64, further comprising biasing the selection of the second media file based on additional attributes.   66. The method of claim 65, wherein the additional attribute represents the popularity of the media file.   66. The method of claim 65, wherein the additional attribute represents an explicit rating of the media file.   66. The method of claim 65, wherein the additional attribute represents an implicit rating of the media file based on observed user behavior. One or more computer-readable media having computer-readable instructions for performing the method of claim 32 when executed by one or more computer devices;
And a computer device embodying the one or more computer-readable media. In a method for creating a sequence of recordings that a set of relationships relate to,
Selecting a starting recording, and
The next skip size is received and used as an input, and the next recording is used as a result of the skip size and the relationship between the current recording and the selectable recording. Selecting a recording for each subsequent playback based on the previous recording by selecting to effect. In selecting a media file using the skip command,
Recognizing the identity of a first media file of the plurality of media files;
Recognizing user input indicating a skip command associated with a desired degree of relationship between the first media file and the second media file of the plurality of media files;
Identifying the second media file according to the skip command. In the method of selecting a media file for playback,
Receiving an event that activates a playback function associated with a particular similarity between the first media file and the plurality of media files the user is experiencing, wherein the particular similarity is the Receiving an event based on data associated with the first and other media files;
Selecting a next media file to be experienced by the user, the selection being based on at least a playback function activated and the data associated with the first media file; Selecting a media file;
Playing the media file.

Images