Palo Alto Research Center Inc.

Amobee, Inc.

Palo Alto Research Center Incorported

Jianqiang Shen

Oliver Brdiczka

Masafumi Suzuki

Yiye Ruan

Mummoorthy Murugesan

Yan Qi

Fang Bian

Tai-Ping Yu

Disclosed are systems and methods for managing queries on on-line advertisement data. The system includes a query engine device for receiving queries from and outputting query results to query client devices and a training engine for generating and adjusting a model for predicting an estimation of resource usage for execution of each received query based on each query's corresponding feature vector having values pertaining to the query and a system status. The query engine device is further configured to provide the estimation of resource usage for each query to the corresponding query client device and, in response, receive input from such corresponding query client device and specifying whether to proceed with the corresponding query. A database system receives input from each query's corresponding query client device as to whether to proceed with the query and, in response, initiates or inhibits execution of such query with respect to a database storage system.

Resource estimation for queries in large-scale distributed database system

One embodiment of the present invention provides a system for characteristics-based message delivery. During operation, the system receives activity data associated with a user, and infers a characteristic profile associated with the user based on the received activity data. The system further receives a plurality of messages, estimates the user's preference for the messages based on the inferred characteristic profile and content of the messages, selects a message from the plurality of messages based on the user's preference and a pre-determined bidding price associated with the message and the characteristic profile, and delivers the selected message to the user.

System and method for estimating and clustering multiple-dimension characteristics for auction-based message delivery

A system and method of selecting on-line advertisements in a real-time bidding exchange is disclosed. A bid request associated with a first data set is received. Advertisements are filtered based on each advertisement's campaign constraints as applied to the first data set. A heuristic score for each filtered advertisement is determined based on a small subset of features from the first data set or randomly generated. A bid value is then determined based on a substantial number of the features from the first data set only for each of a top fraction of filtered the advertisements that have the highest heuristic scores. A final bid value and its associated advertisement is selected and sent to a sender of the bid request for presenting in an on-line advertisement space as an impression.

Systems and methods for efficiently selecting advertisements for scoring

One embodiment of the present invention provides a system for selecting a set of nodes to maximize information spreading. During operation, the system receives a budget constraint and a population sample, constructs a social network associated with the population sample, analyzes a network graph associated with the social network to obtain structural information associated with a node within the social network, estimates characteristics associated with the node, and selects the set of nodes that maximizes the information spreading under the budget constraint based on the structural information and the characteristics associated with the node.

System and method for identifying key targets in a social network by heuristically approximating influence

A computer-implemented system and method for determining an appropriate time for providing a message to a driver are provided. A message is received for a driver of a motor vehicle. Movement of the motor vehicle is monitored, and a familiarity of the movement to the driver is determined. Data sensed by the motor vehicle is obtained, and a cognitive load of the driver is calculated based on the familiarity of the movement and the sensed data. The message is provided to the driver when the calculated cognitive load is low.

System and method for determining an appropriate time for providing a message to a driver

A system and method for prioritizing messages based on message importance is provided. Messages from one or more senders are received for a recipient. For each message, an identity of the sender is determined. A determination is made as to whether each message includes a request for an action to be performed. Also, a length of time required to read that message is determined for each message. An importance value for each message is then calculated based on the identity of the sender, whether a request is included in the message, and the length of time to read the message. Those messages with high importance values are identified as high priority messages and are provided to the recipient.

Computer-implemented system and method for prioritizing electronic messages based on importance

A quitting-intention estimating system facilitates detecting an entity's intention to quit an organization. During operation, the system obtains recent electronic-communication information associated with the entity under investigation, such as an employee of a corporation, or a volunteer of a non-profit organization. The system can determine the entity's quitting intention by determining a plurality of recent communication features from the electronic-communication information, for example, by using a variety of feature-extracting modules that extract the features from the entity's electronic communications. The system then computes a quitting-intention value for the entity under investigation, using a quitting-intention estimating function that takes the recent communication features as input. The quitting-intention estimating function detects a change in the entity's behavior from previous communication features, and generates a quitting-intention value which indicates a likelihood that the change in the entity's behavior corresponds to an intention to quit the organization.

System and method for detecting quitting intention based on electronic-communication dynamics

One embodiment of the present invention provides a system for detecting anomalous correlations between public and private activities of a user. During operation, the system collects public and private activity data associated with the user. The system generates a series of feature pairs, each feature pair including a public feature vector and a private feature vector generated from the activity data. Each respective feature pair corresponds to a respective point in time. The system generates a model to determine whether there is an anomaly in a correlation between the user's public and private activity data. The model is associated with a normal correlation between the user's public and private activity data over a period of time. The system collects additional public and private activity data and applies the model to determine whether there is an anomaly. The system may issue an alert in response to detecting an anomaly.

Monitoring user status by comparing public and private activities

The system facilitates the selective display of messages to a user while the user is driving a vehicle. During operation, the system determines the priority of a message based on: a sender of the message; whether the message requests a response; a duration of time within which to read the message; and one or more rules. The system precludes the display of one or more messages while the user is driving a vehicle based on the respective priority of the messages.

System and method for prioritizing messages based on senders and content for drivers

A conversation-simulating system facilitates simulating an intelligent conversation with a human user. During operation, the system can receive a user-statement from the user during a simulated conversation, and generates a set of automatic-statements that each responds to the user-statement. The system then determines a set of behavior-characteristics for the user, and computes relevance scores for the automatic-statements based on the behavior-characteristics. Each relevance score indicates an outcome quality that the user is likely to perceive for the automatic-statement as a response to the user-statement. The system selects an automatic-statement that has a highest relevance score from the set of automatic-statements, and provides the selected automatic-statement to the user.

Method and apparatus for customizing conversation agents based on user characteristics using a relevance score for automatic statements, and a response prediction function

One embodiment of the present invention provides a system for predicting a personality trait. During operation, the system initially obtains personality data associated with users. The system collects sample data associated with the users. Next, the system trains a predictor with the collected sample data and the personality data. Then, the system collects data associated with a particular user, and generates a personality trait score for the particular user by using the predictor to analyze the particular user's collected data.

Method and system for psychological analysis by fusing multiple-view predictions

An entity-profiling system obtains an electronic identifier for a target entity, such as an email address at which the target entity can be reached, and parses the electronic identifier to determine a name for the target entity. The system also parses the electronic identifier to determine a domain with which the target entity is associated. The system then obtains one or more Internet web pages associated with the target entity based on the entity's name and the domain, and generates a profile for the target entity based on the obtained Internet web pages.

Growing community of inventors

Santa Clara, CA, United States of America

Jianqiang Shen