Abstract: The present invention provides for analyzing document content for display with reduced cognitive load assists those who are blind, have low vision, or cognitive problems. This present invention also aids those who prefer to receive condensed information orally. Document content is analyzed, a set of salient words and phrases are generated from the document content and the set of salient words and phrases are read.

Abstract: The present invention provides for analyzing document content for display with reduced cognitive load assists those who are blind, have low vision, or cognitive problems. This present invention also aids those who prefer to receive condensed information orally. Document content is analyzed, a set of salient words and phrases are generated from the document content and the set of salient words and phrases are read.

Abstract: The present invention provides for analyzing document content for display with reduced cognitive load, and assists those who are blind, have low vision, or have cognitive problems. This present invention also aids those who prefer to receive condensed information orally. Document content is analyzed, a set of salient words and phrases are generated from the document content, the salient words and phrases are tagged, and the set of salient words and phrases are read.

Abstract: To identify and describe one or more topics in one or more documents in a document set, a term set process creates a basic term set from the document set where the term set comprises one or more basic terms of one or more words in the document. A document vector process then creates a document vector for each document. The document vector has a document vector direction representing what the document is about. A topic vector process then creates one or more topic vectors from the document vectors. Each topic vector has a topic vector direction representing a topic in the document set. A topic term set process creates a topic term set for each topic vector that comprises one or more of the basic terms describing the topic represented by the topic vector. Each of the basic terms in the topic term set associated with the relevancy of the basic term. A topic-document relevance process creates a topic-document relevance for each topic vector and each document vector.

Abstract: Concepts in documents selected are identified to a user. These concepts are represented by multiple words. A search engine is used to that accesses one or more selected documents from a plurality of documents storied in one or more of the memories. Then a markup engine selects multiple-word terms in each of one or more of the selected documents. The selected words, often multiple word/concepts, are selected because they are repeated in one of the documents and because that meet grammatical criteria. After the markup engine selects the selected words, it marks each of the selected words with marker. These active markers can then be used to launch additional searches or displays of related information. Optionally, documents with the selected words are displayed to a user with the markers.