Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A multicore interface with dynamic task management capability and a task loading and offloading method thereof are provided. The method disposes a communication interface between a micro processor unit (MPU) and a digital signal processor (DSP) and dynamically manages tasks assigned by the MPU to the DSP. First, an idle processing unit of the DSP is searched, and then one of a plurality of threads of the task is assigned to the processing unit. Finally, the processing unit is activated to execute the thread. Accordingly, the communication efficiency of the multicore processor can be effectively increased while the hardware cost can be saved.

Abstract: Aspects of the invention include hematology analysis reagents, systems and methods that can be used to preserve blood cell morphology and integrity as well as provide sample integrity and optical clarity to facilitate optical analysis of blood samples. In some embodiments, the reagents include a non-phosphate organic buffer and a sphering surfactant. The pH and osmolality of the reagents may be adjusted to desired ranges. In addition, the reagents can be simply diluted with de-ionized water prior to use.

Abstract: Techniques are described herein for using an impression-trend technique to provide a display advertising supply forecast. A display advertising supply forecast is an estimate of a number of impressions, which are to occur in a future time period, that have specified attribute values. For example, the specified attribute values may be descriptive of impressions with respect to which an advertiser wishes to place ads. An impression-trend technique is a forecasting technique that uses trends regarding past impressions to forecast a number of future impressions that have specified attribute values. The past impressions include attribute values that are related to the specified attribute values.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: Techniques are described herein for using an impression-trend technique to provide a display advertising supply forecast. A display advertising supply forecast is an estimate of a number of impressions, which are to occur in a future time period, that have specified attribute values. For example, the specified attribute values may be descriptive of impressions with respect to which an advertiser wishes to place ads. An impression-trend technique is a forecasting technique that uses trends regarding past impressions to forecast a number of future impressions that have specified attribute values. The past impressions include attribute values that are related to the specified attribute values.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A computer implemented system includes a computer readable storage medium which includes historical demand data for a plurality of advertising inventories, and a processor connected to the computer readable storage medium. The processor is configured for generating a first demand forecast for a first predetermined period of time and a second demand forecast for a second predetermined period of time. The processor is configured for adjusting the first demand forecast by removing an existing demand for each of the plurality of advertising inventories, and for generating a net forecasting demand for each of the plurality of inventories for a third predetermined period of time by combining the second demand forecast and an adjusted first demand forecast. The third predetermined period of time is based on the first and second predetermined periods.

Abstract: An improved system and method for forecasting an inventory of online advertisement impressions for targeting profiles of attributes is provided. An index of advertisement impressions on display advertising properties may be built for a targeting profile of attributes from forecasted impression pools. Impression pools of advertisements sharing the same attributes and trend forecast data for web pages and advertisement placements on the web pages may be integrated to generate the forecasted impression pools. An index of several index tables may be generated from forecasted impression pools. A query may be submitted to obtain an inventory forecast of advertisement impressions for targeting profiles of attributes and the index may be searched to match forecasted impression pools for the targeted profile of attributes. Then the inventory forecast of advertisement impressions on display advertising properties may be returned as query results for the targeting profile of attributes.

Abstract: A method attributes credit for conversions to a plurality of event types. A plurality of probabilities that a single impression of each of a plurality of respective event types causes a conversion by one of a plurality of users are defined. A processor is used to select values for the plurality of probabilities so as to minimize a total squared error based on differences between an observed outcome for each user and a respective expected outcome for each user calculated from the plurality of probabilities.

Abstract: Techniques are described herein for using an impression-trend technique to provide a display advertising supply forecast. A display advertising supply forecast is an estimate of a number of impressions, which are to occur in a future time period, that have specified attribute values. For example, the specified attribute values may be descriptive of impressions with respect to which an advertiser wishes to place ads. An impression-trend technique is a forecasting technique that uses trends regarding past impressions to forecast a number of future impressions that have specified attribute values. The past impressions include attribute values that are related to the specified attribute values.

Abstract: A method for reducing computer system power consumption. The computer system includes a memory module having a plurality of address pins, and a chipset having a plurality of driving units for driving the address pins. The method includes obtaining number of required address pins by detecting a capacity of the memory module, and disabling the driving units so as to make a number of the active driving units substantially equal to the number of the required address pins.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A method for allocating inventory in a networked environment includes receiving a request to purchase a number of display impressions, the request including targeting parameters and a frequency constraint corresponding to a maximum number of times the advertisement can be displayed to a user. The method also includes allocating the requested number of display impressions across a set of user samples, where the number of impressions allocated to any one user sample in the set of user samples is constrained by the frequency constraint. Allocation information that defines how the impressions are allocated among the user samples is stored to a user sample database.

Abstract: A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Abstract: A method for processing data on a distributed computing environment is provided. Input data that is to be processed may be stored on an input storage module. Mapper code can be loaded onto a map module and executed. The mapper code can load a mapper executable file onto the map module from a central storage unit and instantiate the mapper executable file. The mapper code, then, can pass the input data to the mapper executable file. The mapper executable file can generate mapped data based on the input data and pass the mapped data back to the mapper code.

Abstract: An improved system and method for forecasting an inventory of online advertisement impressions for targeting profiles of attributes is provided. An index of advertisement impressions on display advertising properties may be built for a targeting profile of attributes from forecasted impression pools. Impression pools of advertisements sharing the same attributes and trend forecast data for web pages and advertisement placements on the web pages may be integrated to generate the forecasted impression pools. An index of several index tables may be generated from forecasted impression pools. A query may be submitted to obtain an inventory forecast of advertisement impressions for targeting profiles of attributes and the index may be searched to match forecasted impression pools for the targeted profile of attributes. Then the inventory forecast of advertisement impressions on display advertising properties may be returned as query results for the targeting profile of attributes.