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...

In this paper, we address the problem of ranking clinical documents using centrality based approach. We model the documents to be ranked as nodes in a graph and place edges between documents based on their similarity. Given a query, we compute similarity of the query with respect to every document in the graph. Based on these similarity values, documents are ranked for a given query. Initially,...

Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and during the last few years enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is low. One of the reasons is the low study desire and...

This paper examines the problem of ranking a collection of objects using pairwise comparisons (rankings of two objects). In a companion paper in the regular NIPS 2011 program [1], we showed that if each object x ∈ Rd is assigned a score f(x) = ||x − r|| for some unknown r ∈ Rd, then our recently proposed active ranking algorithm can recover the ranking of the scores using about d log n selectiv...

Expert finding, aiming to answer the question: “Who are experts on topic X?”, is becoming one of the biggest challenges for information management. Much work has been conducted for expert finding. Methods based on language model, topic model, and random walk have been proposed. However, little work has studied why people want to find experts. In this work, we describe Expert2Bólè, a search tool...

This paper regards the query keywords selection problem in source retrieval as learning a ranking model to choose the method of keywords extraction over suspicious document segments. Four basic methods are used in our ranking function: BM25, TFIDF, TF and EW. Then, a ranking model based on Ranking SVM is proposed to rank the query keywords group which is contributed to get the higher evaluation...