  Because of the data deluge in scientific publication, finding relevant
information is getting harder and harder for researchers and readers. Building
an enhanced scientific search engine by taking semantic relations into account
poses a great challenge. As a starting point, semantic relations between
keywords from scientific articles could be extracted in order to classify
articles. This might help later in the process of browsing and searching for
content in a meaningful scientific way. Indeed, by connecting keywords, the
context of the article can be extracted. This paper aims to provide ideas to
build such a smart search engine and describes the initial contributions
towards achieving such an ambitious goal.
