Semantic Web-Based Information Systems: State-of-the-Art ...

Sheth, Ramakr shnan, & Thomas
Table 1. continued
Utilization Phase
Utilization Phase
Capabilities Implicit Semantics Formal Semantics
Complex query
processing
Question answering (QA)
systems 1
Concept-based search 1
Connection and pattern
explorer 1
Context-aware retriever 1
Dynamic user interfaces 1
Interest-based content
delivery 1
Navigational and research
(Guha, McCool, & Miller,
2003) search
Word frequency and
other CL techniques to
analyze both the
question and answer
sources (Ramakrishnan,
Chakrabarti, Paranjpe, &
Bhattacharya, 2004)
Analyzing occurrence of
words that are associated
with a concept, in
resources
Analyzing semistructured
data stores to
extract patters
(technique in Kuramochi
& Karypis, 2004,
applied to RDF graphs)
Word frequency and
other CL techniques to
analyze resources that
match the search phrase
Analyzing content to
identify concept of
content so as to match
with interest profile
Navigational searches
will need to analyze
unstructured content
Hypothesis
validation queries
(Sheth, Thacker,
& Patel, 2003) or
path queries
(Anyanwu &
Sheth, 2002)
Using formal
ontologies for QA
(Atzeni et al.,
2004)
Using
hypernymy,
partonomy, and
hyponymy to
improve search
(Townley, 2000)
Using ontologies
to extract patterns
that are
meaningful
(Aleman-Meza,
Halaschek, &
Sahoo, 2003)
Using formal
ontologies to
enhance retrieval
Using ontologies
to dynamically
reconfigure user
interfaces (Quan
& Karger, 2004)
User profile will
have ontology
associated with it
which contains
concepts of
interest
Discovery style
queries (Anyanwu
& Sheth, 2002)
on semistructured
data
which is a
combination of
implicit and
formal semantics
Possible Use of
Powerful (Soft)
Semantics
Providing
confidence levels
in answers based
on fuzzy
concepts or
probabilistic
Using fuzzy KR
mechanisms to
represent context
Fuzzy matches
for research
search results
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