Abstract:
Semantics are playing key role in the area of decision making. Besides playing an
importance role in web, semantics-based decision making is getting ingress in other fields,
especially in war related technologies. Our proposed framework for rescue 1122 Pakistan, is
also uses semantics and artificial intelligence combined, to enhance the decision making
process and create situation awareness. A simple plane English string defining the incident
works as input to our framework, from that string framework extracts contact information
with the help of regular expression and extracts address information with the help of
knowledge base and semantics. The rest of the string goes into lexical analyzer, which
expands this string, converts it into new sets of ontologies, neglects/discards connecting
words and parses new relationships inside newly formed sets of ontologies with the help of
relationship builder. Newly formulated strings then are used to create new sets of
semantical senses by implementing open source coreNLP and WordNet library rules. Each
set of semantical senses, then represented in equally distinct numerical values for
processing to ID3 algorithm implemented in Accord.Net library. This algorithm uses multiple
iterations of Iterative Dichotomiser machine learning algorithm to predict results with a
much more accuracy. Finally, decision are taken regarding resources to be utilized in the
rescue operation, location of accident and victims, contact details of accident reporting
person, incident type and related rescue activities to be carried out. This guides the rescue
operation till hospitalization of the victim if required, with the help of geographical tagging
of the location over the map inside rescue vehicle and control center’s common operating
picture.
