Abstract:
Web mining is the use of data mining
techniques to automatically discover and extract
information from Web documents and services.
This area of research is so huge today partly due
to the interests of various research communities,
the tremendous growth of information sources
available on the Web and the recent interest in ecommerce.
Web mining is often associated with
IR and IE.Web page clustering is one of the major
preprocessing steps in web mining analysis.In this
paper, clustering method is proposed to semiautomatically
extract Topic Maps from a set of
web pages. Firstly, the web pages are downloaded
from the internet. To extract contents, remove
stopwords and stem. And Second calculate the
TF_IDF, content similarity, link similarity.
Finally, calculating the Newman’s method with
the weighting based on the similarities by contents
of web pages and types of links is applied to
develop the potential clusters. Then the system
generates the topic map by assuming the clusters
as topics, the edges as associations, the web pages
related to the topic as occurrences from the result
of clustering. As the experimental result, more
compact and denser cluster.
