Abstract: The present system and method relate to an automated crawler for crawling a primary online content object and storing a set of results, a parser for parsing the stored set of results to generate a plurality of key phrases and a content corpus, a plurality of models for processing at least one of the plurality of key phrases or the content corpus, wherein the processing results in a plurality of topic clusters which arrange topics within the primary online content object around a core topic based on semantic similarity, a suggestion generator for generating a suggested topic that is similar to at least one topic among the plurality of topic clusters and for storing the suggested topic, and an application for developing a strategy for development of online presence content.

Abstract: The present system and method relate to an automated crawler for crawling a primary online content object and storing a set of results, a parser for parsing the stored set of results to generate a plurality of key phrases and a content corpus, a plurality of models for processing at least one of the plurality of key phrases or the content corpus, wherein the processing results in a plurality of topic clusters which arrange topics within the primary online content object around a core topic based on semantic similarity, a suggestion generator for generating a suggested topic that is similar to at least one topic among the plurality of topic clusters and for storing the suggested topic, and an application for developing a strategy for development of online presence content.

Abstract: The present system and method relate to enhancements to online search engines and search result rankings, which can benefit from large scale analysis of online content (e.g., Web pages) and vast amounts of information kept and processed from prior searches to develop intelligent associations between various content with one another. Some aspects employ machine learning systems and methods to further enhance the present goals. Other aspects employ novel arrangements of data in data stores to extract best associations and deliver greater search engine rankings to users in an increasingly context-based or personalized type of searching environment.