Abstract: In an example embodiment, an online advertising management platform receives a login that identifies a user as a user allowed access to an account maintained by the platform. The platform displays a toolbar having a textbox that allows the user to search for data relating to all accounts to which the user has access. The platform displays a combo box after the user enters a fixed number of characters in the textbox. The combo box includes a list of descriptions of each data object that is accessible and that is relevant to the fixed number of characters. The platform locates the combo box contiguous to the toolbar over some but not all of the view displaying the data relating to the order. The platform displays a data object, rather than a page of search results, after the user clicks a description of a data object from the combo box.

Abstract: The present invention provides systems and methods for computing a relevance rank or score of a point of interest based on its proximity to clusters of other points of interest (POI). The methods of the present invention are based upon novel approaches that use location information and weighting functions in order to filter and sort searches of hotels, destinations, and other properties or other points of interest. In one approach, a relevance rank of a target POI at a location is determined by obtaining a plurality of component POIs that are each within the same geographical region as the target POI. Component POI scores for each of the component POIs are calculated as a function of a distance between the locations of the component POI and the location of the target POI. The relevance rank of the target POI is a combination of the plurality of component POI scores.

Abstract: In an example embodiment, an online advertising management platform receives a login that identifies a user as a user allowed access to an account maintained by the platform. The platform displays a toolbar having a textbox that allows the user to search for data relating to all accounts to which the user has access. The platform displays a first page of initial search results after the user enters an initial search term in the textbox and launches a search. The first page includes a list of data objects relevant to the initial search term grouped by object category and a list box that allows the user to select an object category. The platform displays a second page after the user selects an object category from the list box. The second page includes an entry box that is related to the selected object category and that facilitates subsequent search.

Abstract: In an example embodiment, an online advertising management platform receives a login that identifies a user as a user allowed access to an account maintained by the platform. The platform displays a toolbar having a textbox that allows the user to search for data relating to all accounts to which the user has access. The platform displays a combo box after the user enters a fixed number of characters in the textbox. The combo box includes a list of descriptions of each data object that is accessible and that is relevant to the fixed number of characters. The platform locates the combo box contiguous to the toolbar over some but not all of the view displaying the data relating to the order. The platform displays a data object, rather than a page of search results, after the user clicks a description of a data object from the combo box.

Abstract: The present invention provides systems and methods for computing a relevance rank or score of a point of interest based on its proximity to clusters of other points of interest (POI). The methods of the present invention are based upon novel approaches that use location information and weighting functions in order to filter and sort searches of hotels, destinations, and other properties or other points of interest. In one approach, a relevance rank of a target POI at a location is determined by obtaining a plurality of component POIs that are each within the same geographical region as the target POI. Component POI scores for each of the component POIs are calculated as a function of a distance between the locations of the component POI and the location of the target POI. The relevance rank of the target POI is a combination of the plurality of component POI scores.