Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1, ?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1, ?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1, ?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n can to specification concept graph speck in spec1, spec2, . . . , specm. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1,?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n can to specification concept graph speck in spec1, spec2, . . . , spec m. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: According to an aspect of an embodiment, a computer system including at least one computer is configured to generate, specification concept graphs of nodes spec1, spec2, . . . , specm including concepts node and relation nodes according to at least one of a plurality of digitized data from user input from a plurality of computerized data sources d1, d2, . . . , dl forming a first set of evidences U; generate concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of IKs ?1, ?2, . . . , ?n forming a second set of evidences U; select a subset of concept graphs of nodes c?i1, c?i2, . . . , c?ih from c?1, c?2, . . . , c?n according to a computable measure of any one or combinations of consistency, inconsistency or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Generate knowledge fragments for corresponding obtained subset of concept graphs c?i1, c?i2, . . . c?ih.

Abstract: According to an aspect of an embodiment, a computer system including at least one computer is configured to generate, specification concept graphs of nodes spec1, spec2, . . . , specm including concepts node and relation nodes according to at least one of a plurality of digitized data from user input from a plurality of computerized data sources d1, d2, . . . , dl forming a first set of evidences U; generate concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of IKs ?1, ?2, . . . , ?n forming a second set of evidences U; select a subset of concept graphs of nodes c?i1, c?i2, . . . , c?ih from c?1, c?2, . . . , c?n according to a computable measure of any one or combinations of consistency, inconsistency or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Generate knowledge fragments for corresponding obtained subset of concept graphs c?i1, c?i2, . . . c?ih.

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).

Abstract: A knowledge-based system under uncertainties and/or incompleteness, referred to as augmented knowledge base (AKB) is provided, including constructing, reasoning, analyzing and applying AKBs by creating objects in the form E?A, where A is a rule in a knowledgebase and E is a set of evidences that supports the rule A. A reasoning scheme under uncertainties and/or incompleteness is provided as augmented reasoning (AR).