12. The method of claim 1 wherein the mutually dependent relationship extraction rule is entered manually by a user during a request by the user for specific relationships between categories, whereby mutually dependent relationships by categories are defined by the user according to the user's needs.
1. A method of mining a collection of data, comprising: receiving the collection of data, the collection of data comprising key words, wherein a key word comprises a coherent character string; converting the collection of data into labeled data by grouping various types of data into a same format and assigning a label indicating a category of item contents, such that the labeled data is in analyzable condition for concept extraction, and wherein the labeled data comprises the label and a clause comprising the item contents; assigning a category to the key words, wherein the category references a concept so that the key words can be handled as concepts with a meaning; separating the clauses into pairs comprising an independent word and an attached word; assigning categories to the separated clauses using syntactic patterns and a category dictionary; generating, by syntactic analysis, a syntactic tree of a sentence comprising the separated clauses; receiving a syntactically analyzed sentence as input, identifying mutually dependent relationships between or among the categorized key words, according to at least one rule defining mutually dependent relationships between or among categorized key words; grouping the identified mutually dependent relationships into groups of related mutually dependent relationships; and extracting the key words with mutually dependent relationships in the same sentence as labeled data with concepts, wherein the step of extracting key words comprises using a mutually dependent relationship extraction rule comprising a string of categories of arbitrary length to be extracted; searching for unique concepts, a unique concept being a concept whose statistical characteristic is distinguished beyond a threshold with the set to which it belongs; creating and keeping statistical information; visually displaying the statistical information; and presenting a distribution of differences of the unique concepts.