Abstract: A method of predicting consumer response to given content. The process begins with the step of collecting a dataset of consumer response to the content, each data item including values for a selected set of segmentation variables related to past consumer behavior. The dataset contains at least twice the number of entries required to provide statistical validity. The process continues by constructing a classification tree structure using the dataset, in which the dataset is subdivided into learning and validation datasets of substantially equal size. Also, the criterion for each successive split is the lowest entropy of segmentation variables not employed to the point of such split. Each successive split of the learning dataset is performed only if that split produces child nodes statistically different from one another, and an identical split of the validation data set produces child nodes statistically similar to child nodes produced on the learning dataset.

Abstract: A method of tracking and publishing categorical user interest data, based on computer user behavior observed by a server coupled in communication with the user's computer. The method includes, as a first step, responsive to a user navigating with a browser to a first content site, receiving one or more categorical navigation history cookies. The next step constitutes categorizing the first content site into one or more subject categories (from a multiplicity of subject categories) and a sponsorship status (as hosting sponsored content or as navigation to sponsored content), which is followed by updating the categorical navigation history cookies to log by subject category and sponsorship status the user navigation to the first content site. The final step is sending to the user's browser the updated categorical navigation history cookies for persistent storage on the user's computer.

Abstract: A method of quantifying the propensity of a consumer to respond positively to an advertisement. The process begins by producing a set of training factors from the entire set of user data available, one set of such factors being associated with each advertisement under study to indicate the probability of positive response to that advertisement. Once the training phase is complete, the application phase begins by receiving input data from a user in real time. The process continues by applying the training factors to the user data to identify the advertisement having the highest probability of positive response and then displaying the identified advertisement to the user.

Abstract: The present invention relates to summarizing cross-network user behavioral data. The summarizing cross-network user behavioral data may particularly include publishing the data to one or more data structures that become accessible to a server hosting an authorized domain when a user accesses the authorized domain.

Abstract: The present invention relates to an advanced search engine. The advanced search engine may include a client component for monitoring an end-user's browsing activity, a remote server (may comprise one or more computers) for storing and processing data received from the client component, and a module that process web pages and serves search results to end-users. The advanced search engine may collect web pages for keywords of proven interest, fetch web pages requested by end-users, generate snippets or abstracts of the web pages, eliminate duplicate web pages, rank the importance of the web pages, and provide relevant web pages or links to web pages in response to an end-user search request for information regarding one or more keywords, for example. Particular aspects of the present invention are described in the claims, specification and drawings.

Abstract: The present invention relates to an advanced search engine. The advanced search engine may include a client component for monitoring an end-user's browsing activity, a remote server (may comprise one or more computers) for storing and processing data received from the client component, and a module that process web pages and serves search results to end-users. The advanced search engine may collect web pages for keywords of proven interest, fetch web pages requested by end-users, generate snippets or abstracts of the web pages, eliminate duplicate web pages, rank the importance of the web pages, and provide relevant web pages or links to web pages in response to an end-user search request for information regarding one or more keywords, for example. Particular aspects of the present invention are described in the claims, specification and drawings.

Abstract: The present invention relates to an advanced search engine. The advanced search engine may include a client component for monitoring an end-user's browsing activity, a remote server (may comprise one or more computers) for storing and processing data received from the client component, and a module that process web pages and serves search results to end-users. The advanced search engine may collect web pages for keywords of proven interest, fetch web pages requested by end-users, generate snippets or abstracts of the web pages, eliminate duplicate web pages, rank the importance of the web pages, and provide relevant web pages or links to web pages in response to an end-user search request for information regarding one or more keywords, for example. Particular aspects of the present invention are described in the claims, specification and drawings.

Abstract: In one embodiment, a message server computer receives client data from a plurality of client computers. The client data may include consumer search, navigation, and/or behavioral information indicative of consumer preferred links for particular keywords. For example, the client data may include recordings of consumer actions across several, different search engines. Upon receipt of a search request for a keyword, a search engine may pass the keyword to the message server computer. The message server computer may generate a set of links determined to be relevant to the keyword based on client data received from the client computers. The search engine may include the set of links in a search result, and provide the search result to the consumer who made the search request. The search result advantageously includes links that are known to be preferred by other consumers performing searches on the Internet.