Multi-Phase Reasoning of
temporal semantic knowledge
Sakirulai O. Isiaq and Taha Osman
School of Computer and Informatics
Nottingham Trent University
Nottingham United Kingdom.
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Outlines
Dynamics of information (the web)
Application example
Possible solution
Semantic Web
Simple semantic query
Challenges
Proposed solution
Multiphase Reasoning Framework
Multi-phase Temporal reasoning Model
Future work and Issues of MPR Framework.
Dynamics of web Information
• Collection of globally distributed text, files,
media documents and network links.
• The world wide web information is so
enormous that personalised information is
now required by individual user.
• Personalising information may required
individual user’s context(s)in service(s)
recommendation.
• One context might depend on the other in
event of Multi-Contexts.
Dynamics of Information (cont.)
• A large proportion of this information are
subjected to changes due to their dynamism
• This changes are also time-critical, which can
be due to the temporal state inherent from
dynamic application domains or increased in
the use of nomadic smart devices capable of
recording real-time user context
• Time-critical temporal information requires
automation.
Application Example
• Consider a context-aware system using
obtained information from multiple sources
(e.g geonames) and locally sourced event
from the service provider application domain
in-line with user’s device information to enrich
contextual data on services offer to the users.
Solution
• Solution to such application involves two
stages:
• Information exploration:
• Exploring the temporal information in the service’s
provider domain with regards to relevant information
extracted from the user’s device
• Exploration the publicly published information in
extracting the relevant part
• Match-making explored information to
produce adequate service.
Semantic Web
• Simply helps in converting current web information
in an form of unstructured and semi-structured
documents into web of data
• This is done through hierarchical classification and
relationship; i.e. description of concepts, terms, and
relationship within a knowledge domain.
• Built on RDF Framework
• Semantic web is built on RDF, which uses XML
Syntax, an easy machine understandable language.
• Helps to improve automation through using machine
understandable meta-data.
Semantic web (Cont.)
• This advantages of semantic web now encourages people and
organisation to publicly publish semantically tagged
information.
• Lots of the current information are time-critical due to:
– Temporal state inherent in dynamic application domain
e.g. media, news etc.
– Increased demand in the used of nomadic smart devices
that are capable of recording real-time devices.
• Hence, representing and interlinking time-critical multidomain and location-aware information play a critical role
when enabling and enacting such data.
Simple Query Information Retrieval
• Such information should be retrieved using a
simple Query as below:
– Select ?service , ?location
Where
{
?service
cas:relates
?context
rdf:type
}
?context
cas:Context
Challenges
• Exploration and match-making of publicly source
information and application domain information
– Representing time-critical information semantically.
– Temporal Context definition and identification
• Multi reasoning and classification of inter-dependent
contexts.
– Comprehensive coupling and handling of multi contextual
information in service recommendation.
– Multi-Phase reasoning of inter-dependent multicontextual information.
Proposed Solution
Multi-Phase Reasoning Framework
• We proposed a multi-phase frame work in
conjunction with the current semantic technology to
deal with the problems such as:
– Abstraction (temporal knowledge abstraction)
– Supplementary reasoning of extracted temporal
multi-contextual information.
– Alignment and match-making the extracted
temporal information.
• It wraps the service provider application domain in
relating users information and published data.
Multi-phase Temporal Reasoning
Model
• Multi-phase temporal reasoning model
– Adoption of modelling techniques to overcome
the owl limitation through temporal concept
isolation
– The introduction Validity domain (an element of
time) used to
– The introduction of Context domain (concepts to
for the aggregation of context and segregation of
static and temporal contexts)
MPR Framework issues and future
work
• Issues anticipated for MPR framework include:
– Scalability
– Performances issue for large scale datasets
– Quality of services
• Anticipated solution applying Aristotle concepts of
change
– The generation of a substance is the perishing of the other
and vice-versa
– We are trying to apply this concept contextual work i.e. the
generation of one context can be the perishing of the
other, then check the effect the performance of the system
Biblography
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