Abstract/Details

A UNIFIED THEORY OF INFERENCE FOR TEXT UNDERSTANDING

NORVIG, PETER.  University of California, Berkeley. ProQuest Dissertations Publishing, 1986. 8718104.

Abstract (summary)

Natural languages, like English, are difficult to understand not only because of the variety of forms that can be expressed, but also because of what is not explicitly expressed. The problem of deciding what was implied by a text, of "reading between the lines" is the problem of inference. For a reader to extract the proper set of inferences from a text (the set that was intrended by the text's author) requires a great deal of general knowledge on the part of reader, as well as a capability to reason with this knowledge. When the reader is a computer$\dots$

Past approaches to the problem of inference have often concentrated on a particular type of knowledge structure (such as a script) and postulated an algorithm tuned to process just that type of structure. The problem with this approach is that it is difficult to modify the algorithm when it comes time to add a new type of knowledge structure.

An alternative, unified approach is proposed. This approach is formalized in a computer program named FAUSTUS. The algorithm recognizes six very general classes of inference, classes that are not dependent on individual knowledge structures. Rather, the classes describe very general kinds of connections between concepts. New kinds of knowledge can be added without modifying the algorithm. Thus, the complexity has been shifted from the algorithm to the knowledge base. To accommodate this, a powerful knowledge representation language named KODIAK is employed.

The resulting system is capable of drawing proper inferences (and avoiding improper ones) from a variety of texts, in some cases duplicating the efforts of other systems, and in other cases improving on them. In each case, the same unified algorithm is used, without tuning the program specifically for the text at hand.

Indexing (details)


Subject
Computer science;
Artificial intelligence
Classification
0984: Computer science
0800: Artificial intelligence
Identifier / keyword
Applied sciences
Title
A UNIFIED THEORY OF INFERENCE FOR TEXT UNDERSTANDING
Author
NORVIG, PETER
Number of pages
290
Degree date
1986
School code
0028
Source
DAI-B 48/05, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
University/institution
University of California, Berkeley
University location
United States -- California
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
8718104
ProQuest document ID
303443749
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/303443749