Abstract: An adaptive learning system and method. This method begins when a problem description provided by the user is received. This problem description may include non-tokenized text. The description is then searched character-by-character against a unique keyword data structure for any user-defined keywords. During this matching process, the routine examines each character in the description and compares it to the keywords in the data structure. Once all keywords are identified, the routine generates a set of solutions associated with at least one of the matching keywords. These solutions are then ranked, for example, based on how many times a respective solution has been used (to solve the problem previously) or how may matching keywords are associated with a respective solution.

Abstract: A method for searching a non-tokenized text string for matches against a keyword data structure organized as a set of one or more keyword objects. The method begins by (a) indexing into the keyword data structure using a character in the non-tokenized text string. Preferably, the character is a Unicode value. The routine then continues by (b) comparing a portion of the non-tokenized text string to a keyword object. If the portion of the non-tokenized text string matches the keyword object, the routine saves the keyword object in a match list. If, however, the portion of the non-tokenized text string does not match the keyword object and there are no other keyword objects that share a root with the non-matched keyword object, the routine repeats step (a) with a new character. These steps are then repeated until all characters in the non-tokenized text string have been analyzed against the keyword data structure.