In the modern society, Internet provides massive amounts of heterogeneous information, hence Information overload has become an ubiquitous issue. In this paper, we conduct a large scale quantitative study for articles dealing with (1) information overloading; (2) faceted search; and (3) filtering the data in three major databases, namely, Web of Science, ScienceDirect, and IEEE Explore. These three databases have presented 172 articles, which can be classified into four categories. The first category contains review and survey papers related to information overload. The second category includes papers that concentrate on developing theoretical frameworks to reduce information overloading. The third category contains papers dealing with improving structure or architectural of software for filtering the huge data. The fourth category includes papers that provide criteria to evaluate filtering techniques. Finally, our contribution provides further understanding of information overload, and gives an important basis for future research. Moreover, we illustrate that the dynamic faceted filters are more efficient to reduce the information overload.

No abstract

No abstract

No abstract

No abstract