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Nancy Salay

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
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3

KR Conference 2004 Conference Paper

Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems

  • Noah S. Friedland
  • Paul G. Allen
  • Michael Witbrock
  • Gavin Matthews
  • Nancy Salay
  • Pierluigi Miraglia
  • Jurgen Angele
  • Steffen Staab

The Halo Pilot, a six-month effort to evaluate the state-ofthe- art in applied Knowledge Representation and Reasoning (KRR) systems, collaboratively developed a taxonomy of failures with the goal of creating a common framework of metrics against which we could measure inter- and intra- system failure characteristics of each of the three Halo knowledge applications. This platform independent taxonomy was designed with the intent of maximizing its coverage of potential failure types; providing the necessary granularity and precision to enable clear categorization of failure types; and providing a productive framework for short and longer term corrective action. Examining the failure analysis and initial empirical use of the taxonomy provides quantitative insights into the strengths and weaknesses of individual systems and raises some issues shared by all three. These results are particularly interesting when considered against the long history of assumed reasons for knowledge system failure. Our study has also uncovered some shortcomings in the taxonomy itself, implying the need to improve both its granularity and precision. It is the hope of Project Halo to eventually produce a failure taxonomy and associated methodology that will be of general use in the fine-grained analysis of knowledge systems.

IJCAI Conference 2003 Conference Paper

Inducing criteria for lexicalization parts of speech using the Cyc KB

  • Tom O'Hara
  • Michael Witbrock
  • Bjern Aldag
  • Stefano Bertolo
  • Nancy Salay
  • Jon Curtis
  • Kathy Panton

We present an approach for learning part-of-speech distinctions by induction over the lexicon of the Cyc knowledge base. This produces good results (74. 6%) using a decision tree that incorporates both semantic features and syntactic features. Accurate results (90. 5%) are achieved for the special case of deciding whether lexical mappings should use count noun or mass noun headwords. Comparable results are also obtained using OpenCyc, the publicly available version of Cyc.

AAAI Conference 2002 Conference Paper

Knowledge Formation and Dialogue Using the KRAKEN Toolset

  • Kathy Panton
  • Nancy Salay
  • David Baxter
  • Cycorp

The KRAKEN toolset is a comprehensive interface for knowledge acquisition that operates in conjunction with the Cyc knowledge base. The KRAKEN system is designed to allow subject-matter experts to make meaningful additions to an existing knowledge base, without the benefit of training in the areas of artificial intelligence, ontology development, or logical representation. Users interact with KRAKEN via a natural-language interface, which translates back and forth between English and the KB’s logical representation language. A variety of specialized tools are available to guide users through the process of creating new concepts, stating facts about those concepts, and querying the knowledge base. KRAKEN has undergone two independent performance evaluations. In this paper we describe the general structure and several of the features of KRAKEN, focussing on key aspects of its functionality in light of the specific knowledge-formation and acquisition challenges they are intended to address.

v2026.09.13