摘要:
A computer that comprises a monitor, a CPU, memory coupled to the CPU, and an instruction storage medium coupled to the CPU. The instruction storage medium provides instructions executable by the CPU, whereby the computer logs consumer activities, creates a local consumer profile based on said consumer activities, and displays an advertisement on the monitor if a target profile of said targeted ad matches the local consumer profile.
摘要:
Systems and methods of advertising are presented herein. In some embodiments, a method may comprise collecting data on a consumer computer, receiving a signal having advertisement information and target criteria, and comparing said target criteria with the data. If the target criteria matches with the data, the method further comprises interfacing the advertisement information in a message format compatible with a message presentation client executed by the consumer computer.
摘要:
A method performed by a processing system includes receiving a recommendation from a source user in response to performing an action corresponding to an action context of the recommendation, determining whether the source user appears in social network information of a target user, and distinguishing a presentation of the recommendation to the target user in response to the source user appearing in the social network information of the target user.
摘要:
In a method for managing a plurality of data entities, data pertaining to transactions by a plurality of users with respect to the data entities is collected and a collaborative filtering operation is applied on the data entities to determine similarity levels of the data entities with respect to each other. In addition, for at least one of the data entities, remaining ones of the data entities are ranked according to the determined similarities while discounting for popularities of the data entities. Moreover, identifications of at least another one of the data entities having the highest rankings to the at least one of the data entities are presented to a first user to recommend the at least another one of the data entities for use by the first user.
摘要:
Systems, methods, and machine readable and executable instructions are provided for collaborative filtering. Collaborative filtering includes representing users and objects by rows and columns in a binary ratings matrix having a particular dimensional space. Unknown values in the binary ratings matrix are weighted with a weight matrix having the particular dimensional space. The binary ratings matrix and the weight matrix are hashed into a lower dimensional space by one of row and column. The hashed binary ratings matrix and the hashed weight matrix are low-rank approximated by alternating least squares. A result of the low-rank approximation for the one of row and column is updated using the binary ratings matrix and the weight matrix. A recommendation of one of the objects can be generated for one of the users based on the updated result.
摘要:
Systems (490), methods (100, 200), and computer-readable and executable instructions (324, 424) are provided for estimating costs of behavioral targeting. Estimating costs of behavioral targeting can include scoring a topic with a behavioral targeting model (101, 201). Estimating costs of behavioral targeting can also include obtaining a plurality of data items including geographic location information (102, 202). Estimating costs of behavioral targeting can also include detecting (104, 204) and scoring (209) a sentiment from filtered data items regarding a topic within a region (104, 204). Estimating costs of behavioral targeting can include computing a penalty score for the topic in the region in response to the scored sentiment exceeding a threshold (213), (106, 206). Estimating costs of behavioral targeting can include adjusting the topic score in the region according to the penalty score (108, 208). Furthermore, estimating costs of behavioral targeting can include taking an action with respect to advertising based on the adjusted topic score (110, 210).
摘要:
In a method for delivering an item of interest, identification of the item of interest is received and identification of an action context to trigger delivery of the identified item of interest is received. In addition, the item of interest, the action context, and an association of the item of interest to the action context are stored. Moreover, a determination that an indication regarding the action context has been received is made and the item of interest is delivered.
摘要:
In a method for context-based item bookmarking (300), an instruction to bookmark an item for future delivery and an action context configured to trigger delivery of the bookmarked item are received (304 and 306). In addition, the action context and the item are bookmarked (308) and at least one entity's activities are monitored to determine whether an activity associated with the action context has been performed (310). Moreover, in response to a determination that the activity associated with the action context has been performed, the bookmarked item is delivered to at least one entity (314).
摘要:
For each web page visited, a path is determined through a hierarchy of categories. The hierarchy of categories has levels from a most abstract level to a most concrete level. For each microblog entry of a microblog, a path is determined through the hierarchy of categories. Each microblog entry for which the path is similar to the path for at least one web page is determined as a selected microblog entry.
摘要:
A collaborative filtering method for evaluating a group of items to aid in predicting utility of items for a particular user comprises assigning an item value of either known or missing to each item of the group of items, and applying a modification scheme to the item values of the missing items to assign a confidence value to each of the item values of the missing items to thereby generate a group of modified item values. The group of items having modified item values and the group known items are evaluated to generate a prediction of utility of items for a particular user.