Abstract: Domain specific knowledge base (KB) contains all concepts from domain and the semantic relations between concepts. The concepts and the semantic relations are extracted from an existing corpus of content for the domain. The World Wide Web Consortium (W3C) standard SKOS (Simple Knowledge Organization System) can be used and two types of semantic relations can be captured: hierarchal and associative. A Natural Language Processing (NLP) software engine can parse the input text to create a semantic knowledge graph, which is then mapped to a SKOS knowledge model. During the linguistic understanding of the text, relevant domain concepts are identified and connected by semantic links. Concepts automatically identified as most important in this domain can be promoted to another layer, referred to as “Topics.

Abstract: Domain specific knowledge base (KB) contains all concepts from domain and the semantic relations between concepts. The concepts and the semantic relations are extracted from an existing corpus of content for the domain. The World Wide Web Consortium (W3C) standard SKOS (Simple Knowledge Organization System) can be used and two types of semantic relations can be captured: hierarchal and associative. A Natural Language Processing (NLP) software engine can parse the input text to create a semantic knowledge graph, which is then mapped to a SKOS knowledge model. During the linguistic understanding of the text, relevant domain concepts are identified and connected by semantic links. Concepts automatically identified as most important in this domain can be promoted to another layer, referred to as “Topics.

Abstract: Domain specific knowledge base (KB) contains all concepts from domain and the semantic relations between concepts. The concepts and the semantic relations are extracted from an existing corpus of content for the domain. The World Wide Web Consortium (W3C) standard SKOS (Simple Knowledge Organization System) can be used and two types of semantic relations can be captured: hierarchal and associative. A Natural Language Processing (NLP) software engine can parse the input text to create a semantic knowledge graph, which is then mapped to a SKOS knowledge model. During the linguistic understanding of the text, relevant domain concepts are identified and connected by semantic links. Concepts automatically identified as most important in this domain can be promoted to another layer, referred to as “Topics.

Abstract: Domain specific knowledge base (KB) contains all concepts from domain and the semantic relations between concepts. The concepts and the semantic relations are extracted from an existing corpus of content for the domain. The World Wide Web Consortium (W3C) standard SKOS (Simple Knowledge Organization System) can be used and two types of semantic relations can be captured: hierarchal and associative. A Natural Language Processing (NLP) software engine can parse the input text to create a semantic knowledge graph, which is then mapped to a SKOS knowledge model. During the linguistic understanding of the text, relevant domain concepts are identified and connected by semantic links. Concepts automatically identified as most important in this domain can be promoted to another layer, referred to as “Topics.

Abstract: A method of determining and an apparatus for displaying, for an organization, a relationship rank between a first party and a second party. A customer relationship management score, a telephone call score, and an e-mail score for the first party relative to the second party may be calculated using a computer system. The customer relationship management score, the telephone call score, and the e-mail score may be calculated using data for the first party and the second party stored in databases. A relationship score for the first party relative to the second party may be calculated using the customer relationship management score, the telephone call score, and the e-mail score. A relationship rank may be calculated for the first party relative to the second party using a computer system. The relationship rank for the first party relative to the second party may be an indication of the strength of the first party's relationship to the second party. The relationship rank may be based on the relationship score.

Abstract: A method of determining and an apparatus for displaying, for an organization, a relationship rank between a first party and a second party. A customer relationship management score, a telephone call score, and an e-mail score for the first party relative to the second party may be calculated using a computer system. The customer relationship management score, the telephone call score, and the e-mail score may be calculated using data for the first party and the second party stored in databases. A relationship score for the first party relative to the second party may be calculated using the customer relationship management score, the telephone call score, and the e-mail score. A relationship rank may be calculated for the first party relative to the second party using a computer system. The relationship rank for the first party relative to the second party may be an indication of the strength of the first party's relationship to the second party. The relationship rank may be based on the relationship score.