Conclusions and future work
The core observation that underlies this paper is that, in the case of
search that promises to produce precise answers to user queries, it is
to ensure that it is easy to use and eﬀective for ordinary end users who
necessarily familiar with domain speciﬁc semantic data, ontologies, or
query languages. Our survey of state-of-art semantic search tools
that current tools provide little support for end users.
In contrast with these eﬀorts, our semantic search engine, SemSearch,
vides several means to address this issue. First, SemSearch overcomes
lem of knowledge overhead by supporting a Google-like query interface.
scribed in Section 4, the proposed query interface provides a simple but
way of specifying queries. Second, SemSearch is able to produce precise
for user queries by providing comprehensive means to make sense of user
and to translate them into formal queries. In particular, as described
6, the produced answers on the one hand satisfy user queries and on the
hand are self-explanatory and understandable by end users. Finally,
provides means (i.e., search reﬁnement forms) to support end users in
mulating better queries. A prototype has been implemented. The
study indicates a encouraging results.
Future work will focus on i) carrying out a more thorough evaluation
will help us to investigate the problems of each main component of the
gine and to improve their performance accordingly; ii) developing
means to perform semantic matching between keywords and semantic
without compromising the performance of the search engine in terms of
iii) developing more ﬁne grained rules which on the one hand will help
us to sig-
niﬁcantly reduce the number of keywords combinations and on the other
will help us to identify and keep useful information in the reduction
iv) developing a powerful ranking mechanism, which guarantees the best
always staying on the top.