Harnessing Cyc to Answer Clinical Researchers' Ad Hoc Queries

Abstract

By extending Cyc’s ontology and KB approximately 2%, Cycorp and Cleveland Clinic Foundation (CCF) have built a system to answer clinical researchers’ ad hoc queries. The query may be long and complex, hence only partially understood at first, parsed into a set of CycL (higher-order logic) fragments with open variables. But, surprisingly often, after applying various constraints (medical domain knowledge, common sense, discourse pragmatics, syntax), there is only one single way to fit those fragments together, one semantically meaningful formal query P. The system, SRA (for Semantic Research Assistant), dispatches a series of database calls and then combines, logically and arithmetically, their results into answers to P. Seeing the first few answers stream back, the user may realize that they need to abort, modify, and re-ask their query. Even before they push ASK, just knowing approximately how many answers would be returned can spark such editing. Besides real-time ad hoc query-answering, queries can be bundled and persist over time. One bundle of 275 queries is rerun quarterly by CCF to produce the procedures and outcomes data it needs to report to STS (Society of Thoracic Surgeons, an external hospital accreditation and ranking body); another bundle covers ACC (American College of Cardiology) reporting. Until full articulation/answering of precise, analytical queries becomes as straight-forward and ubiquitous as text search, even partial understanding of a query empowers semantic search over semi-structured data (ontology-tagged text), avoiding many of the false positives and false negatives that standard text searching suffers from.

Reinforcing Math Knowledge by Immersing Students in a Simulated Learning-By-Teaching Experience

“…The Cyc artificial intelligence platform (Forbus 2012;Lenat and Guha 1990;Lenat et al 1985Lenat et al , 2010 is the foundation of BELLA. Cyc comprises an ontology of half a million terms, a symbolic knowledge base (KB) of ten million hand-written rules and general pieces of information (e.g., water flows downhill; dogs have four legs).…”

“…We are in the process of applying Cyc, an enormous symbolic Artificial Intelligence platform (Lenat et al 1985(Lenat et al , 2010Lenat and Guha 1990), to function as an ITS (intelligent tutoring system) for 6th grade mathematics. Applying Cyc means slightly extending its ontology of 500,000 terms, its knowledge base of ten million assertions and rules, its representation language (first order predicate calculus with several second-and higher-order extensions), its inference engine (which comprises a general theorem prover and 1,100 special-purpose efficient reasoners), and its natural language generation/explanation subsystem.…”

Applying Semantic Technology to Business News Analysis

“…An appealing approach of extending and using Cyc for answering clinical researchers' ad hoc queries is described in (Lenat et al 2010). Even long and complex queries are parsed into CycL fragments, which often can be united only in a single way after applying various constraints.…”

Semi-automatic creation of Wigmore Diagrams

“…Searching CYC [9] for "teddy bear" yields: StuffedAnimal, which enhances (see below) to StuffedToy, Toy and so on.…”