Classical information retrieval (IR) methods often lose valuable information when aggregating weights, which may diminish the discriminating power between documents. To cope with this problem, the paper presents an approach for ranking documents in IR, based on a vector-based ordering technique already considered in fuzzy logic for multiple criteria analysis purpose. Moreover, the proposed appr...

The quality of the ranking function is an important factor that determines the quality of the Information Retrieval system. Each document is assigned a score by the ranking function; the score indicates the likelihood of relevance of the document given a query. In the vector space model, the ranking function is defined by a mathematic expression such as: ∑ ∈ = q t d q score ) , ( tf(t in d) * i...

The well-studied problem of statistical rank aggregation has been applied to comparing sports teams, information retrieval, and most recently to data generated by human judgment. Such human-generated rankings may be substantially different from traditional statistical ranking data. In this work, we show that a recently proposed generalized random utility model reveals distinctive patterns in hu...

A novel ranking method based on multi-time information fusion is proposed for intuitionistic fuzzy sets (IFSs) and applied to the threat assessment problem, a multi-attribute decision making (MADM) one. This method integrates a designed intuitionistic fuzzy entropy (IFE), the closeness degree of technique for order preference by similarity to ideal solution (TOPSIS), the decision maker¡¯s (DM¡¯...

Objective –This study intends to examine the relationship between investment efficiency and financial information excellence. The study is also examining the moderating impact of sustainability on the relation between excellence in financial information and investment productivity. Methodology –The cumulative measurements are 668 firm-years and are made up of 257 subsamples of underinvestment a...