BACKGROUND OF THE INVENTION

The present invention relates to providing services to a user based on analysis of the user's preferences and behaviors. In particular, the present invention relates to providing and recommending services to a user based on analysis of information collected from the user's media assets (e.g., photograph, music and video collections), on-line, and social media activities.

With the proliferation of portable networked devices (e.g., smart phones, tablets, laptops, and connected digital cameras), the costs associated with recording and storing multimedia assets are insignificant. Consequently, users are accumulating vast collections of still images and video clips. The amount of a user's personal multimedia assets makes it difficult to identify and locate the more important ones. Also, because of a desire to document, recognize, and memorialize every day and important life events, many users record images and videos as everyday events unfold. Typically, such multimedia content are first captured in the internal memory of a device, which is then transferred to a hard drive of a personal computer, a networked storage device, a portable hard drive, a solid state memory, or remote cloud-based storage. Very often, the best multimedia content recorded at an individual's important event is recorded by another attending the event, but who has neglected to share this content with the other attendees, despite being a close personal friend or a family member to the individual. Therefore, a convenient and systematic way for locating, sharing, and using assets from multiple multimedia content collections can be very valuable.

Many users store personal content, such as images, in cloud-based storage services (e.g., DROPBOX™, GOOGLE® PHOTOS, AMAZON® CLOUD DRIVE), the actual capture device (e.g., a smartphone), a portable hard drive, a personal computer, or on a social network (e.g., FACEBOOK®), or a combinations of these approaches. However, as mentioned above, all too often when a user wishes to retrieve a specific image, to share an image with a friend or family member, or to use an image in a personal media-centric gift (e.g., a photo greeting card, photo calendar, photo album, or a digital movie or slideshow), he or she is unable to locate the image in a timely and efficient manner.

Analysis of a user's media assets, such as photographs, or music and video collections, enables various commercial or social applications. Such applications are disclosed, for example, in (a) U.S. Pat. No. 7,836,093, entitled “IMAGE RECORD TREND IDENTIFICATION FOR USER PROFILES” to Gobeyn et al.; (b) U.S. Pat. No. 8,910,071, entitled “IMAGE DISPLAY TABS FOR ACCESSING SOCIAL INFORMATION” to McIntyre et al., (c) U.S. Pat. No. 8,028,246 entitled “CONCIERGE—SHOPPING ASSISTANT” also to McIntyre et al., (d) U.S. Patent Application Publication 2009/0132264, entitled “MEDIA ASSET EVALUATION BASED ON SOCIAL RELATIONSHIPS” by Wood et al.; (e) U.S. Pat. No. 8,832,023, entitled “SYSTEM FOR MANAGING DISTRIBUTED ASSETS AND METADATA” to Blomstedt et al.; and (f) U.S. Pat. No. 8,934,717, entitled “AUTOMATIC STORY CREATION USING SEMANTIC CLASSIFIERS FOR DIGITAL ASSETS AND ASSOCIATED METADATA” to Newell et al.

In data mining, transaction histories (e.g., purchases, online activities, social network interactions) have been used to derive useful information about individual and group behaviors. A transaction record is typically identified by a transaction identifier and records a set of items involved the transaction. This record format is called “market basket” style data, as it is similar to a listing of the contents of a supermarket shopping cart of an individual shopper. A transactions database contains a large set of transaction records. Data mining tools have been developed for extracting frequently occurring groups of items (“itemsets”) from conventional transactions databases. There has been some work in using data mining techniques in the image collection domain. For example, see U.S. Patent Application Publication 2011/0072047 to Wang et al., entitled “INTEREST LEARNING FROM AN IMAGE COLLECTION FOR ADVERTISING;” see U.S. Pat. No. 6,598,054, entitled “SYSTEM AND METHOD FOR CLUSTERING DATA OBJECTS IN A COLLECTION,” to Schuetze et al.; and see U.S. Patent Application Publication 2008/0275861 to Baluja et al., entitled “INFERRING USER INTERESTS.”

SUMMARY OF THE INVENTION

According to one embodiment of the present invention, a predictive curator analyzes a user's media assets, transaction data, calendar entries, trends, behavioral patterns to predict and pre-emptively build digital media-centric products using the user's collections of images, with minimal or no active participation by the user. The user's collections of media assets may be retrieved from files on the user's device, cloud-based photo library, or other libraries shared among other individuals and grouped into thematic products. Based on analysis of the user's collections and on-line behaviors, the predictive curator may estimate types and volumes of potential media-centric products, and the resources needed for producing and distributing such media-centric products for a projected period of time.

According to one embodiment of the present invention, the “virtual curator” may take the form of a graphical or animated persona for augmenting and managing interactions between the user and the system managing the user's stored media assets. The virtual curator can assume one of many personas, as appropriate, with each user. For example, the virtual curator can be presented as an avatar-animated character in an icon, or as an icon that floats around the screen. The virtual curator can also interact with the user via text messaging, or audio messaging.

According to one embodiment of the present invention, the curator performs co-occurrence tagging to facilitate searching of the media assets. To provide seed terms for tagging, the curator can take advantage of knowledge embedded in social network comments, and individuals and predominate objects recognized in the media assets themselves. The curator can also take advantage of co-occurrence terms in associated users' collections for matching and correlation.

The present invention is better understood upon consideration of the detailed description below in conjunction with the accompanying drawings.

