A Fully Distributed Scheme for Discovery
of Semantic Relationships
ABSTRACT:
The availability of large volumes of Semantic Web data has created the potential of
discovering vast amounts of knowledge. Semantic relation discovery is a fundamental
technology in analytical domains, such as business intelligence and homeland security.
Because of the decentralized and distributed nature of Semantic Web development,
semantic data tend to be created and stored independently in different organizations.
Under such circumstances, discovering semantic relations faces numerous challenges,
such as isolation, scalability, and heterogeneity. This paper proposes an effective
strategy to discover semantic relationships over large scale distributed networks based
on a novel hierarchical knowledge abstraction and an efficient discovery protocol. The
approach will effectively facilitate the realization of the full potential of harnessing the
collective power and utilization of the knowledge scattered over the Internet.
EXISTING SYSTEM:
This paper proposes an effective strategy to discover semantic relationships over largescale distributed networks based on a novel hierarchical knowledge abstraction and an
efficient discovery protocol. The approach will effectively facilitate the realization of the
full potential of harnessing the collective power and utilization of the knowledge
scattered over the Internet.According to existing research on DBpedia, the average
number of outgoing connections of anobject is 5.67, and the distance between any two
objects is normally within 5-9 steps . Considering that the DBpedia is a very large
complex knowledge base, our parameters set for the number of semantic links per entity
and the path length limit would be large enough to model the distributed knowledge
bases.
PROPOSED SYSTEM:
Further Details Contact: A Vinay 9030333433, 08772261612
Email: takeoffstudentprojects@gmail.com | www.takeoffprojects.com
The proposed technique defined the semantic graph on three levels: entity level,
knowledge base level, and zone level. At the knowledge base level, the optimal distances
for crossing each knowledge base were precomputed. A zone-based discovery protocol
was proposed to efficiently search at the knowledge base level. This method also
supported path discovery in dynamic environments. The experimental results revealed
the scalability and efficiency of the discovery framework. The proposed approach is
fully decentralized and scalable. Moreover, it not only efficiently solves the semantic
relation discovery problem, but also improves the traditional search and discovery of
semantic knowledge. Therefore, our proposed methodology also improves the
effectiveness and efficiency of semantic sharing, in general. Moreover, we also aim to
evaluate the proposed approach on real knowledge bases over the Internet.
CONCLUSION:
In this paper, we presented a scalable and efficient approach to discover complex
semantic relationships from distributed knowledge bases. This approach allows users to
share their local knowledge to collectively make new discoveries. By correlating isolated
islands of knowledge base, we constructed a large-scale semantic graph. The relation
discovery problem was then converted into a pathdiscovery problem over the semantic
graph. Inspired by the route planning problem, we adopted abstraction to reduce the
huge discovery space. The proposed technique defined the semantic graph on three
levels: entity level, knowledge base level, and zone level. At the knowledge base level, the
optimal distances for crossing each knowledge base were precomputed. A zone-based
discovery protocol was proposed to efficiently search at the knowledge base level. This
method also supported path discovery in dynamic environments. The experimental
results revealed the scalability and efficiency of the discovery framework.
SYSTEM CONFIGURATION:HARDWARE CONFIGURATION: Processor
 Speed
-
Pentium –IV
1.1 Ghz
Further Details Contact: A Vinay 9030333433, 08772261612
Email: takeoffstudentprojects@gmail.com | www.takeoffprojects.com
 RAM
-
256 MB(min)
 Hard Disk
-
20 GB
 Key Board
-
Standard Windows Keyboard
 Mouse
-
 Monitor
Two or Three Button Mouse
-
SVGA
SOFTWARE CONFIGURATION:-
 Operating System
: Windows XP
 Programming Language
: JAVA
 Java Version
: JDK 1.6 & above.
Further Details Contact: A Vinay 9030333433, 08772261612
Email: takeoffstudentprojects@gmail.com | www.takeoffprojects.com