Abstract:
According to some example embodiments, a method includes calculating learning values associated with a plurality of listings, at least one of said learning values associated with one of said listings representing a value based, at least in part, on a probability distribution of selections of said listing. The method further includes applying said learning values to ranking scores associated with said listings to provide an updated ranking, and electronically auctioning advertising inventory to purchasers associated with said listings based, at least in part, on said updated ranking.
Abstract:
An approach is provided for acquiring images with camera-enabled mobile devices using objects of interest recognition. A mobile device is configured to acquire an image represented by image data and process the image data to identify a plurality of candidate objects of interest in the image. The plurality of candidate objects of interest may be identified based upon a plurality of low level features or “cues” in the image data. Example cues include, without limitation, color contrast, edge density and superpixel straddling. A particular candidate object of interest is selected from the plurality of candidate objects of interest and a graphical symbol is displayed on a screen of the mobile device to identify the particular candidate object of interest. The particular candidate object of interest may be located anywhere on the image. Passive auto focusing is performed at the location of the particular candidate object of interest.
Abstract:
Systems and methods are provided for mobile campaign optimization without knowing user identity. The system includes circuitry configured to obtain mobile application data about a mobile application from at least one mobile device. The system includes circuitry configured to generate a mobile application profile for the mobile application using the mobile application data. The system further includes circuitry configured to select at least one mobile application to show a mobile advertisement in the at least one mobile application at least partially using the mobile application profile.
Abstract:
A method includes accessing a number of cards from a database. The cards are ranked in the database based on a test conducted on a number of users. The cards are associated with one or more rule states. The one or more rule states provide binary outcomes of one or more rules. Each rule is identified using a code. The test is conducted by presenting different random sequences of the cards to different users and receiving inputs from the number of users. The method further includes receiving a request for a presentation area from a client device operated by a user. The presentation area is used for displaying the number of cards in an order, which is determined based on the test. The method includes providing the number of cards for display in the order within the presentation area on the client device of the user in response to the request.
Abstract:
The present disclosure relates to computer systems implementing methods for online content recommendation. The computer systems may be configured to receive a training sample from a first client device corresponding to a predefined feedback interacting with online content displayed on the first client device; update a preexisting training database in real-time based on the received training sample to generate an updated training sample, wherein prior to being updated based on the training sample received from the first client, the training database includes a set of historical training samples; conduct a regression training to a computer learning model in real-time, using the updated training sample, to produce a set of trained parameters for an online content recommendation model; call the set of trained parameters in real-time to determine recommend online content for a second user with the online content recommendation model; and send the recommended online content to a second client device of the second user.
Abstract:
Information is presented to a user of a user device by a method including: collecting data relating to communications sent to or from the user, including to or from a first person, each communication including a link of a plurality of links; generating personal profiles from the collected data, the profiles comprising a first personal profile of the first person and including a first link of the plurality of links; and presenting the first personal profile to the user, comprising displaying the first link in a user interface on the user device.
Abstract:
In one example, an apparatus and method are provided for summarizing (or selecting a representative subset from) a collection of media objects. A method includes selecting a subset of media objects from a collection of geographically-referenced (e.g., via GPS coordinates) media objects based on a pattern of the media objects within a spatial region. The media objects may further be selected based on (or be biased by) various social aspects, temporal aspects, spatial aspects, or combinations thereof relating to the media objects and/or a user. Another method includes clustering a collection of media objects in a cluster structure having a plurality of subclusters, ranking the media objects of the plurality of subclusters, and selection logic for selecting a subset of the media objects based on the ranking of the media objects.
Abstract:
Briefly, methods and/or systems of processing a content table prior to entropy encoding are described. An example may comprise determining upper and lower equivalent byte values for the content. The content may be transformed and reordered based, at least in part, on the upper and lower equivalent byte values and compressed using, for example, delta compression.