Toyoaki NISHIDA
(with Hideaki Takeda, Kenji Iino, Michiaki Iwadume, Katsuji Onishi,
Tadahisa Okimoto, Yoichi Kado, Motoyuki Takaai, Kazuhiro Takaoka,
Masatoshi Nishiki, Kenji Hanakawa, Shoji Yasumura)
Graduate School of Information Science,
Nara Institute of Science and Technology
8916-5 Takayama, Ikoma, Nara 630-01, Japan
e-mail: nishida@is.aist-nara.ac.jp
In this research, we focus on commonsense knowledge referred to in
spoken dialogue. We attempt to build a computational model of
commonsense knowledge and develop a knowledge server that can provide
commonsense knowledge for various components of spoken dialogue system.
In this fiscal year, we have made a study on the methodologies of
constructing commonsense knowledge base with particular emphasis on
ontology.
First, in order to obtain insights on the feasibility and cost of
building an information base from existing documents, we conducted an
experiment of producing a structured document consisting of an
ontology and associated pieces of text fragments. After having worked
out the whole process for a small fraction of a technical document, we
took a chapter of a technical document (258 pages in Japanese) as
sample and asked students to decompose them into a structured
document. The resulting ontologies contain about 1,100 conceptual
elements and 1,200 relations. We have partly implemented a prototype
information system which can present information upon a given
perspective by reconfiguring text fragments according to the ontology.
The result of the experiments was quite promising. About 116 hours
are required to manually produce a structured document from the sample
document. If the experiment had been made with the contextual media,
the cost would be significantly decreased for the sake of various
computational supports. Our working hypothesis is that building an
information base from existing documents is quite feasible and cost
effective even though it is to be handcrafted.
Second, we have developed the theoretical framework of the {
contextual media}. The contextual media allows information of varying
degree of structural sophistication to be integrated and evolve as
information accumulated into the {information base} increases in
quantity and quality.
Primary elements of the contextual media are {units}. A unit
plays two mutually complementary roles. On the one hand, a unit
represents a {concept} and is used as a lexical item in contextual
media statements. On the other hand, a unit specifies a {context}
in which statement in the contextual media is made. The most
primitive relation in the contextual media is membership of a unit (as
a concept) in another unit (as a context). The statements in a
context may be arbitrarily sophisticated using known knowledge
representation techniques and are organized into an abstraction
hierarchy in which a more sophisticated representation layer is
encapsulated into a less sophisticated representation layer. The
technique is called {encapsulated representation}.
We have developed several techniques for making the contextual media
approach useful. {Connection-based associative retrieval} allows
the user to access information with little prior knowledge about the
contents and structure of the information base with the contextual
media. {Knowledge elaboration assistance package} helps the user
elaborate an information base with respect to the terminology and
structure, by mining tacit information structure in the information
base.
We have made several preliminary studies, which suggest the
feasibility and effectiveness of the contextual media approach.
Third, we have studied theoretical issues in the development of
multiple ontologies in building a distributed and heterogeneous
knowledge-base system.
We have analyzed relationship between ontology and agent in the {
Knowledgeable Community} which is a framework of knowledge sharing and
reuse based on a multi-agent architecture. Ontology is a minimum
requirement for each agent to join the {Knowledgeable Community}.
We have explored a technique for mediation by ontology. A special
agent {mediator} analyzes undirected messages and infer candidates
of recipient agents by consulting ontology and relationship between
ontology and agents.
We have developed a model ontology which is a combination of aspects
each of which can represent a way of conceptualization. Aspects are
combined either as {combination aspect} which means integration of
aspects or {category aspect} which means choice of aspects. Since
ontology by aspect allows heterogeneous and multiple descriptions for
phenomenon in the world, it is appropriate as ontology of a
heterogeneous knowledge-base system.
We have shown translation of messages as a way of interpreting
multiple aspects. A translation agent can translate a message with
some aspect to one with another aspect by analyzing dependency of
aspects. Mediation and translation of messages make it easy to build
each agent because it is required to have less knowledge on other
agents.
Keywords: commonsense knowledge, knowledge sharing and reuse, knowledge media, ontology, mediation