Abstract: Method and system for generating personalizing website layout. The method and system monitors a user's behaviors and assigns a user to a user group, which has an assigned personalized template. The templates are personalized in response to the user's behaviors and arranges content to be displayed to the user based on that behavior.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: Briefly, embodiments disclosed herein may relate to generating signals and/or states representative of a template for a web page. One or more areas of a template may be associated with a respective one or more entities of a web page publisher, and content for the one or more areas associated with the one or more entities may be selected.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: A hydrostatic fluid containment system, or flood barrier, that is positioned underground in its open state consisting of a buoyant wall which floats up and above ground level when submerged in a fluid, creating a seal from both buoyant vertical and hydrostatic horizontal forces on the containment wall imposed by the contained fluid. The system will not open prematurely and restrict access of vehicles or pedestrians until containment is necessary. The system comprises a pivot seal which seals the barrier on the upstream side, as well as another sealing element that is positioned between the pivot seal and the buoyant wall. The pivot helps to tilt the barrier towards the upstream direction.

Abstract: A hydrostatic fluid containment system, or flood barrier, that is positioned underground in its open state consisting of a buoyant wall which floats up and above ground level when submerged in a fluid, creating a seal from both buoyant vertical and hydrostatic horizontal forces on the containment wall imposed by the contained fluid. The system will not open prematurely and restrict access of vehicles or pedestrians until containment is necessary. The system comprises a pivot seal which seals the barrier on the upstream side, as well as another sealing element that is positioned between the pivot seal and the buoyant wall. The pivot helps to tilt the barrier towards the upstream direction.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined. Based on user features of a user and items a user has consumed, a set of nearest neighbor items are identified as a set of candidate items, and affinity scores of candidate items are determined. Based on the affinity scores, a candidate item from the set of candidate items is recommended to the user.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: A method and system for generating a topic page for a search query on a search webpage includes receiving a query at the search webpage on a client. The query is transmitted from the search webpage on the client to a search engine on a server. A topic page generator available to the search engine analyzes the query to identify a plurality of dimensions. One or more content modules, including at least one interactive advertising module, that match one or more of the dimensions are selected from a plurality of sources based on a weight associated with each of the content modules. The weight defines the ranking of a content module. The content modules for the plurality of dimensions are glued together and presented on the topic page in the order of the corresponding weight of the content modules. The order of presentation identifies the relevancy of the content modules to the query.

Abstract: Embodiments disclosed herein may relate to producing a layout for a web page.

Abstract: Methods and systems for presenting application modules on a graphical display page are provided. In accordance with one embodiment, content to be displayed on a graphical display page is determined. Then, content features which describe the content that is to be displayed on the graphical display page, and user features which describe characteristics of users are determined. For each application in the plurality of application modules, the probability that specific users will select the application module when displayed on the graphical display page with the determined content is determined based on the content features and the user features. For each application module in the plurality of application modules, an overall score is determined based on the determined probability that the user will select the application module and a commercial value to be paid by a publisher of the application module when it is selected.

Abstract: Method and system for generating personalizing website layout. The method and system monitors a user's behaviors and assigns a user to a user group, which has an assigned personalized template. The templates are personalized in response to the user's behaviors and arranges content to be displayed to the user based on that behavior.

Abstract: A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined and stored. Based on user features of a particular user and items a particular user has consumed, a set of nearest neighbor items comprising nearest neighbor items for user features of the user and items the user has consumed are identified as a set of candidate items, and affinity scores of candidate items are determined.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.

Abstract: Methods and systems for presenting content such as articles based on utility are provided. In one embodiment, a plurality of articles are determined, each article in the plurality of articles including article content and a corresponding preview icon, the preview icon defining a link to the corresponding article content when presented. For each article in the plurality of articles, a user experience utility value is determined. And for each article in the plurality of articles, an economic utility value is also determined. A ranked order of the articles is determined based upon each article's user experience utility value and economic utility value. And a portion of the preview icons of the articles are presented on a graphical display page in a priority orientation based on the ranked order of the articles.

Abstract: Methods and systems for presenting application modules on a graphical display page are provided. In accordance with one embodiment, content to be displayed on a graphical display page is determined. Then, content features which describe the content that is to be displayed on the graphical display page, and user features which describe characteristics of users are determined. For each application in the plurality of application modules, the probability that specific users will select the application module when displayed on the graphical display page with the determined content is determined based on the content features and the user features. For each application module in the plurality of application modules, an overall score is determined based on the determined probability that the user will select the application module and a commercial value to be paid by a publisher of the application module when it is selected.

Abstract: In a pay for placement database search system, in which advertisers pay to include their search listings in a database to be provided with search results in response to queries from searchers, each advertiser decides how much money he wants to spend on a search term. The search provider displays the advertisers' listings in proportion to the amount of money the respective advertisers spend. This permits the advertisers to subscribe to the database search system, deciding how much to pay for a subscription for a predetermined time period. The search provider can recommend an optimal spend amount for the advertisers.

Abstract: A system and method are disclosed for improving a statistical message classifier. A message may be tested with a machine classifier, wherein the machine classifier is capable of making a classification on the message. In the event the message is classifiable by the machine classifier, the statistical message classifier is updated according to the reliable classification made by the machine classifier. The message may also be tested with a first classifier. In the event that the message is not classifiable by the first classifier, it is tested with a second classifier, wherein the second classifier is capable of making a second classification. In the event that the message is classifiable by the second classifier, the statistical message classifier is updated according to the second classification.