Abstract: A system and method for using a combination of semantic and statistical processing of input strings or other data content, such as a web page or an electronic document. In accordance with an embodiment, the system enables the injection of semantics into an otherwise statistically-based environment, by recognizing that, within various topics, certain words, combinations of words, or phrases, herein referred to as keyphrases have different weights. Some keyphrases may be relatively unique within a particular topic, or have a relatively high weighting towards that topic; whereas other keyphrases may not be unique, or may have a relatively low rating toward that topic. In accordance with an embodiment, the system allows for characterization of both (a) “sufficient” and (b) “necessary” keyphrases. A keyphrase is considered sufficient for a particular topic when, if that keyphrase is found in the input string or data content, one is likely to be in that topic (but could be in another topic).

Abstract: A system and method for using semantic understanding in storing and searching data and other information. A linearized tuple-based version of a conceptual graph can be created from a user input. A plurality of conceptual graphs, or portions thereof, can be compared to determine matches. An associative database can be created and/or searched using a hierarchy of conceptual graphs in tuple format, so that the data storage and searching of such database is optimized. The associative database can be used to integrate data from multiple different sources; form part of an Internet or other search engine; or used in other implementations. Also disclosed herein is a system and method for use of semantic understanding in searching and providing of content is described herein.