Optimization
of Heterogeneous Information Real-Time Retrieval Model of Campus Website
Zhiyong
Chen
Education
Technology and Information Center, Guangdong Medical University, Zhanjiang, 524023,
China
Abstract:
Most of the current information retrieval models of campus websites are
centralized. In the case of large amount of information or more requests for
access at the same time, it reduces the real-time performance of the retrieval
and causes the bottleneck of the network. To address this problem, a new
heterogeneous information real-time retrieval model of campus website is
designed in this paper. The model of heterogeneous information network is introduced.
LDAP directory technology is used to organize and manage global index
information. A distributed heterogeneous information retrieval model of campus
web site based on LDAP is designed and its physical architecture is built. The
retrieval node is designed by using distributed structure of network token-ring
and LDAP protocol. The queue is retrieved by using Pop Rank method and Co-Hits
method. A large number of related heterogeneous information will be returned in
the case of large difference between the retrieval key words and the required
retrieval results, which need to be optimized. Rough classification of the
retrieved results is achieved by clustering method to remove the result that is
far apart from most of the retrieval results. The SOM neural network is used
for fine classification to close the desired results and improve the real-time
performance of retrieval. Experimental results show that the designed model is
highly accurate and real-time.
Keywords:
Campus website; Heterogeneous information; Real-time; Retrieval model; Optimization