Abstract: Aspects relating to client server interactions using cookies are provided. A computer-implemented method is provided that includes receiving a request from a user for a first advertisement associated with a first advertiser, the request including first cookie data, the first cookie data including a first identifier specified for a first cookie, the first cookie being associated with a first group of advertisers including the first advertiser and a third advertiser, receiving a request from the user for a second advertisement associated with a second advertiser, the request including second cookie data, the second cookie data including a second identifier specified for a second cookie, the second cookie being associated with a second group of advertisers including the second advertiser and where the advertisers of the second group of advertisers are distinct from the advertisers of the first group of advertisers.

Abstract: Aspects relating to client server interactions using cookies are provided. A computer-implemented method is provided that includes receiving a request from a user for a first advertisement associated with a first advertiser, the request including first cookie data, the first cookie data including a first identifier specified for a first cookie, the first cookie being associated with a first group of advertisers including the first advertiser and a third advertiser, receiving a request from the user for a second advertisement associated with a second advertiser, the request including second cookie data, the second cookie data including a second identifier specified for a second cookie, the second cookie being associated with a second group of advertisers including the second advertiser and where the advertisers of the second group of advertisers are distinct from the advertisers of the first group of advertisers.

Abstract: A resource context system (“context system”) computes a contextual profile for a resource based on selection data for the resource and contextual profiles of other resources that are identified as relevant to the resource. The contextual profile includes values that specify measures of relevance of the resource to each of a plurality of corresponding topics. The contextual profile is provided to a processing system, such as an advertisement management system or a search system that can identify topics for which the resource is relevant based on the contextual profile.

Abstract: A resource context system (“context system”) computes a contextual profile for a resource based on selection data for the resource and contextual profiles of other resources that are identified as relevant to the resource. The contextual profile includes values that specify measures of relevance of the resource to each of a plurality of corresponding topics. The contextual profile is provided to a processing system, such as an advertisement management system or a search system that can identify topics for which the resource is relevant based on the contextual profile.

Abstract: Various computer-implemented methods are disclosed for selecting items, including but not limited to user-submitted blurbs, to present to users. One such method comprises using a plurality of personalized selection algorithms to select items to nominate for presentation to a target user. Each personalized selection algorithm outputs one or more item nominations for the target user together with an associated relevance score for each nominated item. The method further comprises receiving the item nominations and associated relevance scores from the personalized selection algorithms, normalizing the relevance scores, and using at least the normalized relevance scores to select particular items to present to the target user.

Abstract: Various computer-implemented methods are disclosed for selecting content items, including but not limited to user-submitted blurbs, to present to users. One such method comprises storing user-specific item selection history data identifying particular items, such as catalog items, selected by particular users, and recording responses of a plurality of the users to a content item. The method further comprises determining whether the content item should be presented to a target user based, at least in part, on a degree to which the item selection history of the target user is similar to item selection histories of users who responded favorably to the content item.

Abstract: A system provides an interface for users to author and post pieces of content, referred to as “blurbs,” for viewing by other users. Blurbs may also be obtained from external sources, such as from blogs hosted by various web sites. A personalized blurb selection component selects blurbs to present to users based on histories of catalog items selected by such users, and/or based on various other criteria. User feedback provided on specific blurbs may be taken into consideration by the personalized blurb selection algorithms.

Abstract: An electronic catalog system provides an interface for users to author and post pieces of content, referred to as “blurbs,” for viewing by other users. The blurbs submitted by a particular author are made available for viewing in an author-specific blog (web log) format. Blurbs may also be obtained from external sources, such as from blogs hosted by various web sites. A personalized blurb selection component selects blurbs to present to users based on histories of catalog items selected by such users, and/or based on various other criteria. The blurbs selected for a particular user are presented within a personal log or “plog,” which may be updated daily and will typically contain entries from many different authors. User feedback provided on specific blurbs is taken into consideration by the personalized blurb selection algorithms.

Abstract: A method for managing a plurality of different fonts that are installed on a computer. Raw font data for the plurality of fonts are stored in files on a computer hard disk (34). At least some of the fonts for which a character set is defined by the raw data are installed in the graphics user interface operating system running on a computer. The installed fonts are listed in a file (40). The method enables a user (22) to create one or more font menu lists (28) that are displayed to the user whenever selection of a font for use in a document by an application is desired. The font menu lists are subsets of the complete list of installed fonts on the operating system. Applications (42) can access any of the fonts installed on the system, but whenever a font must be selected by the user for use in a document, a more limited list of fonts appropriate for the application then running on the computer is displayed, reducing confusion as to the appropriate fonts that should be considered.

Abstract: A method and system for parametrically generating characters and fonts. A font generation system is run on a computer and allows a user to create a Terafont binary file, which includes a set of universal font generation rules that are applied to generating fonts consistent with a common type of alphabet, and parametric data files, each of which specify a particular font. The user can create a new font, or replicate an existing font. The parametric data are distributed as files or embedded in documents. One or more characters of a font are generated using a font engine that executes the Terafont binary file on a computer using the parametric data specifying that font as an input. The parametric data provided to the font engine at least include a minimal set of font measurement data, such as a PANOSE.TM. number, which are used to compute global variables representing typographic characteristics common to many--if not all--of the glyphs in the font.