662866
Commonsense Metaphysics and Lexical Semantics
In the TACITUS project for using commonsense knowledge in the understanding of texts about mechanical devices and their failures, we have been developing various commonsense theories that are needed to mediate between the way we talk about the behavior of such devices and causal models of their operation. Of central importance in this effort is the axiomatization of what might be called "commonsense metaphysics". This includes a number of areas that figure in virtually every domain of discourse, such as scalar notions, granularity, time, space, material, physical objects, causality, functionality, force, and shape. Our approach to lexical semantics is then to construct core theories of each of these areas, and then to define, or at least characterize, a large number of lexical items in terms provided by the core theories. In the TACITUS system, processes for solving pragmatics problems posed by a text will use the knowledge base consisting of these theories in conjunction with the logical forms of the sentences in the text to produce an interpretation. In this paper we do not stress these interpretation processes; this is another, important aspect of the TACITUS project, and it will be described in subsequent papers.
27996567
Ernest Davis, Representations of Commonsense Knowledge
21017652
Interactive retrieval of complex documents
Abstract Documents such as reports, articles, memos, and forms have complex structure and layout, as well as multimedia content. Information systems that represent these aspects of documents must be able to handle queries more complex than in typical database or text retrieval systems. In this paper, we describe an interface that allows the specification of uncertain queries and combines evidence about the relevance of documents to produce an overall ranking. We also report the results of an experiment that addresses some of the cognitive aspects of such an interface.
14200223
Implementing ranking strategies using text signatures
Signature files provide an efficient access method for text in documents, but retrieval is usually limited to finding documents that contain a specified Boolean pattern of words. Effective retrieval requires that documents with similar meanings be found through a process of plausible inference. The simplest way of implementing this retrieval process is to rank documents in order of their probability of relevance. In this paper techniques are described for implementing probabilistic ranking strategies with sequential and bit-sliced signature tiles and the limitations of these implementations with regard to their effectiveness are pointed out. A detailed comparison is made between signature-based ranking techniques and ranking using term-based document representatives and inverted files. The comparison shows that term-based representations are at least competitive (in terms of efficiency) with signature files and, in some situations, superior.