  The process of browsing Search Results is one of the major problems with
traditional Web search engines for English, European, and any other languages
generally, and for Arabic Language particularly. This process is absolutely
time consuming and the browsing style seems to be unattractive. Organizing Web
search results into clusters facilitates users quick browsing through search
results. Traditional clustering techniques (data-centric clustering algorithms)
are inadequate since they don't generate clusters with highly readable names or
cluster labels. To solve this problem, Description-centric algorithms such as
Suffix Tree Clustering (STC) algorithm have been introduced and used
successfully and extensively with different adapted versions for English,
European, and Chinese Languages. However, till the day of writing this paper,
in our knowledge, STC algorithm has been never applied for Arabic Web Snippets
Search Results Clustering.In this paper, we propose first, to study how STC can
be applied for Arabic Language? We then illustrate by example that is
impossible to apply STC after Arabic Snippets pre-processing (stem or root
extraction) because the Merging process yields many redundant clusters.
Secondly, to overcome this problem, we propose to integrate STC in a new scheme
taking into a count the Arabic language properties in order to get the web more
and more adapted to Arabic users. The proposed approach automatically clusters
the web search results into high quality, and high significant clusters labels.
The obtained clusters not only are coherent, but also can convey the contents
to the users concisely and accurately. Therefore the Arabic users can decide at
a glance whether the contents of a cluster are of interest.....
