GGI Innovation Summit | Seminar Module Abstract 5 - Semantic Technologies & Knowledge-Enabled Innovation

Semantic Technologies & Knowledge-Enabled Innovation - Purpose

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 cull out the relevant solutions from both internal and external knowledge sources.

Semantic Technologies & Knowledge-Enabled Innovation - Productivity

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 Technologies & Knowledge-Enabled Innovation - Semantic Technology

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

Semantic Technologies & Knowledge-Enabled Innovation - Demonstration

James Todhunter is EVP and the Chief Technology Officer of Invention Machine where he is responsible for the company's technology strategy and execution. A seasoned innovator and inventor, Jim works on the front line of innovation and has more than 30 years of experience in software technology and management. Prior to joining Invention Machine, Jim was Chief Technology Officer and Vice President of Engineering at Vality Technology Inc. Before that, he held various management and technology positions at Ardent Software, NCR, and Midas Systems Corporation. His award-winning blog, Innovating to Win, offers insight and observations on building high-performance teams that can drive sustainable innovation across the organization. Jim holds an M.S. in Information and Computer Science from the University of California, Irvine.

During the course of his presentation, Invention Machine's Goldfire® software will be utilized to demonstrate connectivity across the web and deep web to search, using semantic technology, the patent databases of all major industrialized countries in the world. Software exists that is fast enough to translate a technical search request into five languages querying the databases in their native language, locate the results, sort out the irrelevant findings, and return a sortable pareto list of a global reach in under ten seconds.

Some day, a long time from now, this type of software will be resident on everyone's computer. Right now, it can only be found in one place. Invention Machine is a twenty-year old company, this is not an overnight creation. Jim Todhunter is among the best there is to predict this future of Internet Protocol v6 - The Semantic Web.