Abstract
Baudin, Catherine; Kedar, Smadar; Underwood, Jody G.; Baya, Vinod;
"Question-based Acquisition of Conceptual Indices for Multimedia
Design Documentation", In proceedings of the 11th National Conference
on Artificial Intelligence AAAI-93, Washington D.C., pp 452-458, July
1993.
Information retrieval systems that use conceptual indexing to describe
the information content perform better than syntactic indexing methods
based on words from a text. However, since conceptual indices
represent the semantics of a piece of information, it is difficult to
extract them automatically from a document, and it is tedious to build
them manually. We implemented an information retrieval system that
acquires conceptual indices of text, graphics and videotaped documents.
Our approach is to use an underlying model of the domain covered by
the documents to constrain the user's queries into indices which
accurately model the content of the documents, and can be reused. We
discuss Dedal a system that facilitates the indexing and retrieval of
design documents in the mechanical engineering domain. A user
formulates a index, Dedal uses the underlying domain model and a set
of retrieval heuristics to approximate the retrieval, and ask for
confirmation from the user. If the user finds the retrieved
information relevant, Dedal acquires a new index based on the query.
We demonstrate the relevance and coverage of the acquired indices
through experimentation.
Vinod Baya
baya@sunrise.stanford.edu