Module 5 - Semantic Techniques & Knowledge-Enabled Innovation

This module explores the relationship between innovation and the ability to tap into exiting sources of relevant knowledge. Earlier modules explored methods that enable problem solvers to think creatively and ask the right questions. This module shows how those questions, when cast in the right context, can drive out relevant solutions from both internal and external knowledge sources.

It is well understood that most problems have already been solved - if not directly then at least in part or analogously - but often in another discipline or industry. Yet ironically, the rapidly multiplying worldwide technical information remains largely untapped - due to the mismatch between conventional search technologies and the concept-based needs of product and process designers. The same issues even obscure access to a company's tribal wisdom encoded in the many decades of its digital documents. Managers report that 30-60% of a design team's efforts are redundant to prior work. In today's time and resource-constrained development environment, such inefficiencies are no longer tolerable.

Semantic search technologies have been touted as a solution. In this module we explore the hype and reality, and conclude with a current state-of-the art demonstration in which semantic retrieval is integrated with innovative problem solving methods.

Contents:

• Relationship of Stored Knowledge to Innovative Problem Solving
• Relationship of Search Technologies to Innovative Problem Solving
• Origins, evolution and categories of NLP & semantic technologies
  • Metadata; Taxonomy & Ontology, Semantic Web
  • Statistical & Latent Semantic Analysis
  • Computational Linguistics
• Limitations and constraints of various semantic approaches
• The critical role of the user's question in leveraging semantic search
  • Understanding context and design-intent
• Survey of software solutions and web resources
• Demonstration