A system and method for ranking search results based on a series of attributes derived from the behavior of past searchers is disclosed. The attributes provide a measure of the relevancy between a search query and a URL, file, or other resource based on its relevancy to prior users. The system comprises (1) an attribute database including a plurality of prior search terms or phases; a first set of resources associated with each of the queries; and the attributes, i.e., metrics, characterizing the relevance of the first set of resources to the queries; and (2) a search processor adapted to identify a second set of resources determined to be relevant to a user query; rank each of the second set of resources based on the metrics associated with the query and resource; and provide the user with the search results ranked in accordance the metrics and displayed in a manner to increase the utility of the results for the user.

Search engine using user intent

A fraudulent business transaction application (FBTA) is provided in embodiments of the present invention for monitoring fraudulent transactions. When a consumer supplies account access information in order to carry out an Internet business transaction, the FBTA uses an online fraud mitigation engine to detect phishing intrusions and identity theft. Embodiments are also provided for calculating travel velocity and transaction frequency, which are useful for determining a fraudulent transaction. Further embodiments are provided for authenticating a transaction using a cookie stored on a client device and a behavior profile stored on a server.

Fraud analyst smart cookie

A computer-implemented method is disclosed. The method includes receiving from a remote device a search query, generating a local result set and one or more non-local result sets for the search query, determining a display location for the local result set relative to the non-local result set based on a position of the search query in a local relevance indicium.

Presentation of local results

Embodiments of the invention can provide systems and methods for identifying and measuring trends in consumer content demand within a vertical network of websites and related content In one embodiment, a method can include receiving, from a crawler, content from a plurality of webpages in at least one vertical The method can include receiving, from a processor, data associated with a plurality of selected keywords associated with the at least one vertical, wherein one or more associations between at least a portion of the plurality of selected keywords can be generated In addition, the method can include receiving, from a processor, session data associated with a plurality of consumers accessing content in webpages in the at least one vertical Furthermore, the method can include determining third party data associated with the plurality of consumers accessing at least a portion of webpages comprising at least one of the selected keywords Moreover, the method can include aggregating, based at least in part on the third party data, session data associated with visits to the webpages comprising at least one of the selected keywords

Systems and Methods for Identifying and Measuring Trends in Consumer Content Demand Within Vertically Associated Websites and Related Content

A computer-implemented method is disclosed. The method includes receiving from a remote device a search query, generating a plurality of different category-directed result sets for the search query, determining an order for the plurality of category-directed result sets based on the search query, and transmitting the plurality of category-directed result sets to the remote device, in a manner that the result sets are to be displayed in the remote device in the determined order.

Providing relevance-ordered categories of information

A method for logical view visualization of user behavior in a networked computer environment that includes sites that a user may visit and wherein the sites comprise pages that the user may view and/or resources that the user may request includes the step of collecting raw data representing user behavior which can include requesting resources, viewing pages and visiting sites by the user. This raw data is then refined or pre-processed into page views and visit data and stored in a data mart. Pages are clustered into super pages, and page to super page mappings reflecting the relationship between pages and super pages are stored in the data mart. An automated clustering means is applied to the page view, visit and super page data in the data mart to discover clusters of visits to define super visits having visit behavior characteristics. The visit data stored in the data mart is then scored against the super visit clusters to classify visits into super visits according to visit behavior characteristics. A system is also provided.

Ming Tan

Papers

System and method for logical view analysis and visualization of user behavior in a distributed computer network