We describe some components of our large-scale multi-users knowledge server WebKB-2 (usable from http://www.webkb.org/). Details may found at this site or in  and .
Knowledge Representation/Retrieval, Ontology Server, Cooperation, RDF.
Current Web search engines can retrieve documents that include keywords but they cannot retrieve precise information in answer to precise queries, e.g. "list the characteristics of American cars for sell under 20,000 AUD in Sydney?", "what are the 5 cheapest ways to travel from Sydney to Brisbane in March 2001?", and "which database systems can handle interactively modifiable schemas?". Answering such queries requires a large-scale cooperatively-built knowledge base (KB) because: (i) the task of producing the necessary information has to be distributed among many providers, (ii) the KB should be not be restricted to a limited domain (which KB should be searched or updated if the knowledge is scatered among many KBs; there is no reliable way to connect, merge or cross-check knowledge from separated KBs).
We developp a Web server (WebKB-2) for such large-scale cooperatively-built KBs. We expect it to be used for supporting "Yellow-Pages like catalogs" or "corporate memories". In this article, we briefly present a few of the elements that we designed to enable a large-scale cooperatively-built KB base and summarise the cooperation and search mechanisms adopted.
A knowledge representation language is needed for representing knowledge.
We designed two notations -- Frame-CG (FCG) and Formalized English (FE) --
to improve on the readability and expressivity of the Conceptual Graph
For instance, the sentence "According to Dr Foo, most cars have 4 wheels."
may be represented by the FCG statement
[most cars, part: 4 wheels](Foo@bar.au)
or the FE statement
`most cars have for part 4 wheels'(Foo@bar.au)
-- the identifier of Dr Foo being
These notations encourage the user to be explicit and exact in his/her
knowledge representations, and limit the number of ways an piece of information
is expressed. This simplifies procedures for comparing/retrieving/cross-checking
For the same reason, we also developed knowledge representation guidelines for the WebKB users: lexical guidelines (e.g. use English singular nouns as category names), semantic guidelines (be precise, contextualize statements, re-use and complement existing knowledge), syntactic guidelines (e.g. how to represent various kinds of quantifiers, collections, intervals, contexts, 2nd order types/relations), ontological guidelines (e.g. how to represent states and processes, descriptions, indexations, characteristics, measures, numbers, collections, temporal/spatial/logical entities/relations).
Each element of the KB (category, category name,
link between categories, concept node or relation node)
is associated with an identifier of the user who created it.
This is required to support updates by multiple users and permit each user to
filter or focus on knowledge from certain users.
Each category (concept/relation types, individuals) has a unique
wn#car, "wn" being the creator identifier) but
may have several names (e.g. the category
wn#car may also
be referred by
second way shows not only the "key name" but all the names).
Conversely, a name may be shared by several categories if it has a variety of
Within statements, categories may be refered via names instead of identifiers
when there is no ambiguity about each refered category (either because a name
refers to only one category or because the signature associated to the used
relations can be exploited to reduce the possibilities).
With our current KB initialized with the
WordNet lexical database,
[most cars, part: 4 wheels]
is ambiguous: there are 5 categories with name
"car" and 6 categories with name "wheel". An unambiguous statement is
[most wn#car, part: 4 wn#wheel]
(or using abbreviations:
[most #car, part: 4 #wheel]).
When WebKB-2 parses an ambiguous statement, it rejects it but helps the user
to refine it by displaying the various possible categories for each ambiguous
Knowledge retrieval, update and checking in WebKB is greatly supported,
and guided by our reuse of the WordNet ontology (the 66,000
categories related to nouns) and its insertion into
an ontology of 100 top-level concept types and 140 basic relation types
signed on these top-level concept types. These relation types were designed
to permit the direct representation of most natural language sentences
but are also relevant for more model-oriented representations.
We distinguished the WordNet
specialization links into
subtype links and
instance links by manually
isolating 2900 individuals. We also made a few other structural
corrections. Finally, we added some categories from other ontologies, e.g.
Ontolingua and the RDF basic standard schema. The categories and links are not
stored in a fixed schema; they can be updated interactively.
An object-oriented database called
is exploited for knowledge storage.
Here is a summary of the protocols for the cooperative edition of the KB.
Any user can reuse any category in links or statements (unless that induces
a detected inconsistency), create new categories, links or statements,
remove the ones s/he created and filter out the others.
A user may not modify a statement that s/he has not created but
s/he can connect it to another statement via a relation of type
A user must also use these relations in order to add a statement that WebKB
detect as a specialization or generalization of another statement. Thus,
conflicts between users are made explicit, re-use is maximized
and redundancy is prevented.
Statements can be retrieved via search for specializations of a query graph. Categories may be retrieved according to their names or connected links. Links may be recursively explored. In all cases, filtering on creators may also be applied.