We test and confirm the hypothesis that individual investors are net buyers of attentiongrabbing stocks, e.g., stocks in the news, stocks experiencing high abnormal trading volume, and stocks with extreme one day returns. Attention-driven buying results from the difficulty that investors have searching the thousands of stocks they can potentially buy. Individual investors don’t face the same se...

One can use the Leiden Rankings for grouping research universities by considering universities which are not significantly different as a homogeneous set. Such groupings reduce the complexity of the rankings without losing information. We pursue this classification using both statistical significance and effect sizes of differences among 902 universities in 54 countries; we focus on the UK, Ger...

The exchangeability assumption as defined in this paper on ranking functions seems intuitively natural, and indeed, specific ranking functions previously proposed in the literature are all exchangeable. While pointwise ranking functions are vacuously exchangeable, we now discuss two specifically listwise ranking functions previously proposed by [22] and [26] in light of our representation theor...

This paper is a continuation of the study of surprise as a base for constructing qualitative calculi for representing and reasoning about uncertain knowledge. Here, we further elaborate on κ, a qualitative ranking function which we developed in (Ibrahim, Tawfik, and Ngom 2009b) and which constructs qualitative ranks for events by obtaining the order of magnitude abstraction of the degree of sur...

In this paper, we provide an overview of the NTCIR IMine task, which is a core task of NTCIR-11 and also a succeeding work of INTENT@NTCIR-9 and INTENT2@NTCIR-10 tasks. IMine is composed of a subtopic mining (SM) task, a document ranking (DR) task and a TaskMine (TM) pilot task. 21 groups from Canada, China, Germany, France, Japan, Korea, Spain, UK and United States registered to the task, whic...

This paper describes our contribution to the English Entrance Exams task of CLEF 2015, which requires participating systems to automatically solve multiple choice reading comprehension tasks. We use a combination of text segmentation and different similarity measures with the aim of exploiting two observed aspects of tests: 1) the often linear relationship between reading text and test question...

This is an overview of the NTCIR-9 INTENT task, which comprises the Subtopic Mining and the Document Ranking subtasks. The INTENT task attracted participating teams from seven different countries/regions – 16 teams for Subtopic Mining and 8 teams for Document Ranking. The Subtopic Mining subtask received 42 Chinese runs and 14 Japanese runs; the Document Ranking subtask received 24 Chinese runs...