Abstract: A system for determining associations between base content and relevant content and for publishing the base content and relevant content on a client browser. The system includes a parsing module configured to parse the base content to form parsed base content; a unit-dictionary module including a plurality of query units; a unit-extraction module configured to extract query units included in the unit dictionary from the parsed base content, wherein the query units extracted from the base content are referred to as the extracted-query units; a unit-ranking module configured to rank the extracted-query units based on at least one of relevance scores and revenue-generation amounts for the query units; and a unit-matching module configured to generate at least one association between the base content and the relevant content based on whether the extracted-query units and at least one of query units and keywords associated with the relevant content are the same.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters. Some or all of the presentations or references are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. The results of such processes might be stored in a presentation details database. A presentation server handles retrieving presentations from the presentation details database for presentation to users along with requests such as search results. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.

Abstract: A system is disclosed for using speech recognition with map data. For example, a user could state a location. The system will recognize the words spoken and find the location on a map using an electronic map database. The map can be displayed such that the location is depicted. Alternatively, the user could state two locations. The system will recognize the words spoken, find both locations on the map using an electronic map database, determine a path between the locations and report that path to the user.

Abstract: A system is disclosed for identifying matching arcs in sets of geometric objects, such as a pair of electronic maps, without relying on attributes being assigned to the arcs. An arc in a first set of geometric objects is identified as matching an arc in a second set of geometric objects, when the arc in the first set is co-bounded on both sides by polygons which match the corresponding co-bounding polygons of the arc in the second set. A determination is made of which polygons in the first set of geometric objects match polygons in the second set of geometric objects, by computing and comparing a set of similarity metrics. Examples of characteristics for which similarity metrics are determined include, proximity, area, shape and rotation. Each similarity metric is determined in an isolated fashion, so that no other metric is reflected in the metric being measured.

Abstract: A system is disclosed for warping models made from geometric objects, such as electronic maps, to correct local distortions in the models without compromising model topology. A set of transformation functions are derived from relationships between points in a first model that match points in a second model. The transformation functions are then applied to the points in the first model to generate a new model with reduced distortion. In order to provide for reducing local distortions, warping is applied to selected corresponding regions of the first model and the second model by triangulating these regions and generating transformation functions for each corresponding pair of triangles. Topology preservation is achieved by identifying matching points in the first model and the second model that have a potential for causing topology deviations. Such matching points are then excluded from the process of developing transformation equations to be used in the warping process.