20 Nov 2014

Relevant Data in the Rising Tide of Big Data: A Text-Mining Analysis in Construction Safety Index

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The previous generation of academia
faced the problem of insufficient data, academic journal articles and
books. Thanks to the rapid development of World Wide Web
since 90s, academic papers published in one place can be viewed in
another side of the globe, insufficient literature and data problems
have been relieved. Modern academic researchers, however, face another
major problem of big data. There are too many irrelevant articles. Much
of the time has been spent to search for the relevant articles from the
irrelevant ones. One of the major aims of this chapter is to review the
problem of big data based on the example of construction safety index.
Construction safety is an important issue Worldwide. The development of
construction safety index is of particular importance as it provides an
objective measurement on the level of safety on sites. This chapter
reviews (1) how intelligence is the academic search engine in screening
the relevant articles out the irrelevant materials, (2) compare and
contrast the methods which are used to construct the construction safety
indices with the other indices constructed worldwide.