Abstract: A method of querying a user profile commences with a first access to a public portion of a knowledge profile for each of a plurality of potential targets of the electronic document, the public portion of each knowledge profile including public knowledge terms indicative of a knowledge base of a potential target of the electronic document. The first access is responsive to a first query received from an originator. A first matching operation is performed between a document term within the electronic document and public knowledge terms within the public portion of each knowledge profile to identify a first set of targets for which a match exists between the document term and at least one public knowledge term. The first set of targets is published to the originator.

Abstract: A method of constructing a profile comprising terms indicative of a characteristic of an entity commences when first electronic mail address, associated with a first entity, is created within a knowledge management system. The electronic mail address may be created automatically upon submission of an electronic mail document, or may be created manually by a systems administrator. A first electronic document is received via an electronic communications network at the first electronic mail address from a second entity, typically a user of the knowledge management system who is a registered and interactive user. The first electronic document is then parsed to identify profile terms therein. These profile terms are included within a first profile for the first entity. In this way, users of a knowledge management system may construct a profile of an entity (e.g., a customer) that is not a user of or participant within the knowledge management system.

Abstract: A method of assigning a confidence level to a term within an electronic document, such as an e-mail, includes the step of firstly determining a quantitative indicator in the exemplary form of an occurrence value, based on the number of occurrences of a particular term within an electronic document, and associating the occurrence term within the relevant term. Thereafter, a qualitative indicator, based on a quality of the term, is determined. For example, the qualitative indicator may be determined utilizing the parts of speech of words comprising the term. A confidence level value, which may be utilized to indicate a relative importance of the term in describing a user knowledge base, is then generated utilizing the quantitative and qualitative indicators.