Overview 
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2028's Automated Semantic Knowledge (ASK) has taken three years to develop and addresses the heart of the information organization problem: how to make a system understand the essence of a document. Designed to mimic human reading and analysis, ASK understands a document's semantic relevance by identifying and analyzing the concepts and their relationships via innovative data representations, set algorithms, and heuristics. Just as the Page Rank (Link Analysis) algorithm takes inspiration from the human heuristic of leveraging annotated references (links), ASK uses comparable insightful heuristics to dramatically improve intra-document analysis and search. ASK amalgamates individual pieces of information over a set of documents into a contextual lattice of knowledge.
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Search
- automated semantic knowledge
- single document
- document based
- insightful semantic relevance
- knowledge
- comparable insightful heuristics
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The Two Sides to Search: Reference Based Understanding / Document Based Understanding. Current advances in search have come about from leveraging reference-based analysis (human annotations). Comparable advances in document-based understanding can lead to similar improvements (even in searches currently using reference-based algorithms). In addition, improved document-based analysis can have a farther-reaching impact on electronic document tools. 2028's Automated Semantic Knowledge (ASK) is the counterpart to algorithms such as WebRank to improving search.
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Categorization
- humanistic document analysis
- humanistic relevance metrics
- automated semantic knowledge
- analysis algorithms, network
- automated methods
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A fundamental element of any solution is the method of document analysis used. 2028 s Automated Semantic Knowledge (ASK) provides a clearer, better, and more humanistic document analysis, catalyzing categorization solutions to the next level. Designed to mimic human reading and analysis, ASK understands a document's semantic relevance by identifying and analyzing concepts and their relationships via innovative data representations, set algorithms, and heuristics. Just as Link Analysis algorithms have propelled web search, ASK uses comparable insightful heuristics to improve categorization.
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Targeted Advertising
- individual documents
- ask
- semantic network
- springboards
- real-time analysis
- semantic relevance,
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2028's Automated Semantic Knowledge (ASK) enables clearer individual and aggregate understanding of users and advertisements. ASK springboards any TA solutions to the next level. ASK translates documents, user profiles, and Ad descriptions into a common language in which they can be logically connected and matched. With a clearer understanding of the relevance of concepts and their relationships, ASK provides a platform for the next generation of TA solution. ASK's real-time analysis of individual documents enables TA systems to adapt the Ads shown to the current user session.
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Interactive Intelligence
- ask
- data
- sources
- identifies
- raw data
- interactive
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Despite efforts to capture intelligence, most insight is lost because manual gathering, analyzing, and sharing massive amounts of information in a timely manner is infeasible. 2028's Automated Semantic Knowledge (ASK) is a powerful tool for transforming text into quantified values and useful intelligence by enabling the comparison, connection, and differentiation of data from any electronic source. ASK's Interactive Intelligence Services provides various methods for turning raw data into insight including visualization, monitoring, and quantification. Visualization ASK consolidates textual data of any size and format from disparate sources into a descriptive information picture.
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