Patent application number | Description | Published |
20120253899 | TABLE APPROACH FOR DETERMINING QUALITY SCORES - Some implementations construct a quality score table based on historic data collected for a plurality of ad-keyword pairs. An ad-keyword pair may be selected for determining a quality score. One or more advertisement parameters may be determined for the selected ad-keyword pair. Based on the one or more advertisement parameters, the quality score for the selected ad-keyword pair may be determined from the quality score table. In some implementations, the quality score table is constructed by iteratively cutting a directed graph representing the advertisement parameters and the historic data. Further, in some implementations, the table may be smoothed using a smoothing operation. | 10-04-2012 |
20120253927 | MACHINE LEARNING APPROACH FOR DETERMINING QUALITY SCORES - Some implementations generate a mapping function using one or more historic performance indicators for a set of ad-keyword pairs and one or more advertisement metrics extracted from the set of ad-keyword pairs. The mapping function may be applied to map one or more advertisement metrics of a particular ad-keyword pair to determine a quality score for the particular ad-keyword pair. For example, the quality score may be used when determining whether to select an advertisement for display or may be provided as feedback to an advertiser. Additionally, in some implementations, the mapping function may be applied to determine a quality score for a new ad-keyword pair that has not yet accumulated historic information. | 10-04-2012 |
20120253945 | BID TRAFFIC ESTIMATION - Some implementations provide techniques for estimating impression numbers. For example, a log of advertisement bidding data may be used to generate and train an impression estimation model. In some implementations, an impression estimation component may use a boost regression technique to determine a predicted impression value range based on a proposed bid received from an advertiser. For example, the predicted impression value range may be determined based on a predicted estimation error. Additionally, in some instances, the predicted impression value range may be evaluated using one or more evaluation metrics. | 10-04-2012 |
20130260693 | PROXIMATE BEACON IDENTIFICATION - Among other things, one or more techniques and/or systems are disclosed for identifying a proximate beacon to a mobile device. One or more first received signal strengths (RSSs), relative to the mobile device, may be received and used to determine a first average signal strength (RSS) and a first average RSS deviation for a first beacon during an observation period. An average RSS deviation for the observation period can be determined using the first average RSS deviation (e.g., and other average RSS deviations). If the average RSS deviation meets a desired deviation threshold, the first beacon may be identified as the proximate beacon. In this manner, if the user of the mobile device consents to the same, the user may be provided with relevant information (e.g., advertisements) on the mobile device while in a locale (e.g., store) corresponding to the (known) location of the beacon, for example. | 10-03-2013 |
20130260781 | LOCATING A MOBILE DEVICE - One or more techniques and/or systems are disclosed for identifying a location of a mobile device (e.g., with user consent). A set of one or more indications of received signal strength (RSS) may be received, comprising a first RSS from a first access point (AP). The set of RSS indications may be used to identify a grid area, comprising a first grid space. An expected distance between the first grid space and the first AP may be identified using the first RSS. The expected distance can be combined with a first known distance between the first grid space and the first AP to determine a first grid score for the first grid space. A second grid score may be determined for a second grid space (e.g., and a third, fourth, etc.), and the grid space comprising a desired grid score (e.g., highest) may be selected as the mobile device location. | 10-03-2013 |
20130260782 | LOCATING A MOBILE DEVICE - Identifying a location of a mobile device is disclosed (e.g., presuming user consent to the same). One or more received signal strengths (RSSs), comprising a first RSS, may be received by a first access point (AP) from the mobile device. The RSSs may be used to identify a grid area, comprising a first grid space. A signal distance between the first grid space and the first AP may be identified using the first RSS, and combined with a first grid space distance, comprising a known distance between the first grid space and the first AP, to determine a first grid space likelihood score for the first grid space. A second grid space likelihood score may be determined for a second grid space (e.g., and a third, etc.), and the grid space comprising a desired grid space likelihood score (e.g., highest) may be selected as the mobile device location. | 10-03-2013 |
20150031392 | PROXIMATE BEACON IDENTIFICATION - Among other things, one or more techniques and/or systems are disclosed for identifying a proximate beacon to a mobile device. One or more first received signal strengths (RSSs), relative to the mobile device, may be received and used to determine a first average signal strength (RSS) and a first average RSS deviation for a first beacon during an observation period. An average RSS deviation for the observation period can be determined using the first average RSS deviation (e.g., and other average RSS deviations). If the average RSS deviation meets a desired deviation threshold, the first beacon may be identified as the proximate beacon. In this manner, if the user of the mobile device consents to the same, the user may be provided with relevant information (e.g., advertisements) on the mobile device while in a locale (e.g., store) corresponding to the (known) location of the beacon, for example. | 01-29-2015 |