Abstract: Method and systems personalizing the search results presented to a user in an electronic marketplace. A search query is received and a set of search results related to the search query are obtained. Individual entries of the search results are associated with a category type. The search results are sorted in a number of category groups according to the category type. An entry from each category group is selected and scores are determined for the selected entries. A highest scored entry is assigned to a highest available position in a resultant search result set. The scores for the entries that remain unassigned are increased. For the category group corresponding to the assigned entry, another entry is selected and scored. A highest entry score is assigned the next highest position. The process may continue recursively until all, or a threshold number, of entries have been assigned to the resultant list.

Abstract: Method and systems personalizing the search results presented to a user in an electronic marketplace. Data for a search query in an electronic marketplace is received. The query is executed and search results are received. Scores are calculated each item in the search result based at least in part on at least one of global navigational data and personal navigational data. Each item is allocated a position in an ordered search result list based at least in part on the scores. When at least some subset of the items in the search result list have been scored and allocated a position in the ordered search result list, the ordered search result list may be presented to the user.

Abstract: Techniques for improving advertisement relevance for sponsored search advertising. The method includes steps for processing a click history data structure containing at least a plurality of query-advertisement pairs, populating a first translation table containing a co-occurrence count field, populating a second translation table containing an expected clicks field, and calculating a click propensity score for an advertisement using the click history data structure, the first translation table (for determining overall click likelihood across all historical traffic), and using the second translation table (for removing biases present in the first translation table).

Abstract: Embodiments are directed towards employing long and short term historical user click propensity behaviors to adapt or filter a number of advertisements displayed and their location on a search results' page. A network device tracks a user's short and long term historical click behaviors. For a given search query for the user, a variety of candidate advertisements are selected. A normalized click-through rate (COEC) is estimated for each advertisement. The COEC and the user's short and long term click behavior, represented by User Click Propensity (UCP), is used to generate a User effective Cost Per Thousand (UeCPM) value. Candidate advertisements are filtered based on a minimum threshold value for UeCPMs. Page placement for the remaining advertisements is determined based on a user expected revenue for an advertisement determined from the UCP. Advertisements having a user expected revenue above another threshold are placed in a north page location.

Abstract: A method for executing multiple, cascading ad auctions, including receiving a request to deliver ads in response to a search query for display on a search results page having a plurality of ad sections; executing at least first and second sequential auctions for the plurality of ad sections by: ranking the ads in the first auction and identifying which of the ads placeable in the North section to deliver according to a first utility function that considers a relevance of the search results page with the ads placed; ranking a remainder of the ads not identified for delivery to the North section in the second auction and identifying which of the remainder of the ranked ads to deliver to a second section based on a second utility function; and delivering the ads identified by the first utility function for display in the North section and the ads identified by the second utility function for display in the second section.

Abstract: A method for reducing ad impact on users in a search results page includes receiving a request to deliver ads in response to a search query for display on a search results page; receiving relevance scores for a plurality of ranked web results that are to be served to the search results page; ranking a plurality of ads identified as relevant to the search query according to a position-normalized, click-through-rate metric and bid values, wherein a predetermined number of the top-ranked ads are placeable in a plurality of North ad slots; incrementally and additively placing the placeable ads sequentially according to rank (k) in their respective North ad slots until a utility score generated by a utility function for a current iteration of ads fails to exceed a threshold value; and delivering to the search results page the ads placed in the North ad slots.

Abstract: The present invention is directed towards systems and methods for ranking and providing advertisements in a position auction. The method of the present invention comprises receiving a search query and selecting at least one keyword based upon the search query. A list containing at least one keyword based upon the search query is returned and a list comprising at least one bid corresponding to the returned list of keywords is retrieved. The search query and list comprising at least one bid are used to train an offline simulator. The offline simulator creates a model that predicts optimal scoring factors. A priority score corresponding to each bid is computed using the optimal scoring factors and used to rank the list of bids. Advertisements are then provided corresponding to a plurality of the highest ranking bids.

Abstract: In a method for preventing rollover for a vehicle traveling on a road, for each present position of the vehicle as it moves forward, its speed is forecasted for future positions of the vehicle on the road, based on an assumption regarding driving style of the operator, and based on a map containing road geometry data and statistical speed data for vehicles traveling said road. At each such present position of the vehicle, a maximum safe speed is determined for points on the road forward of the vehicle, based on a maximum lateral acceleration, the road geometry and the vehicle parameters. A rollover warning is generated for any current position of the vehicle at which the forecasted future speed for at least one particular point on the road forward of the vehicle exceeds the determined maximum safe speed at particular point.

Abstract: In a method for preventing rollover for a vehicle traveling on a road, for each present position of the vehicle as it moves forward, its speed is forecasted for each future position of the vehicle on the road, based on an assumption regarding a driving style of a driver of said vehicle, and based on a map containing road geometry data and statistical speed data for vehicles traveling said road. At each such present position of the vehicle, a maximum safe speed of the vehicle is determined for each of a plurality of points on the road forward of the vehicle, based on a maximum lateral acceleration, the road geometry and the physical parameters of the vehicle.

Abstract: A method for on-board real-time diagnostics of a mobile technical system using an adaptive technique to approximate stationary characteristic curves resulting from a workshop test. This adaptive technique uses observed non-stationary normal driving data to eliminate confounding variables.

Abstract: A method for on-board real-time diagnostics of a mobile technical system using an adaptive technique to approximate stationary characteristic curves resulting from a workshop test. This adaptive technique uses observed non-stationary normal driving data to eliminate confounding variables.

Abstract: A system installed in a motor vehicle for inferring a vehicle operator's stress level from body sensors and from environmental data related to the position and operation of the vehicle. The system functions in a training phase using machine learning techniques to derive a model of an individual operators stress reaction to the environment in which the vehicle is operated and, using the results of this training phase, the system is subsequently used to predict stress levels to be expected when certain traffic conditions are imminent based on a projection of the driver's physiolocial state. The result of this prediction of stress level for the individual driver is used to control or warn the driver with respect to operation and scheduling of attention diverting devices such as cellular phones.

Abstract: A system installed in a motor vehicle for inferring a vehicle operator's stress level from body sensors and from environmental data related to the position and operation of the vehicle. The system functions in a training phase using machine learning techniques to derive a model of an individual operators stress reaction to the environment in which the vehicle is operated and, using the results of this training phase, the system is subsequently used to predict stress levels to be expected when certain traffic conditions are imminent based on a projection of the driver's physiolocial state. The result of this prediction of stress level for the individual driver is used to control or warn the driver with respect to operation and scheduling of attention diverting devices such as cellular phones.

Abstract: A method for on-board real-time diagnostics of a mobile technical system using an adaptive technique to approximate stationary characteristic curves resulting from a workshop test. This adaptive technique uses observed non-stationary normal driving data to eliminate confounding variables.