In this paper, w e extend an existing para­ graph retrieval approach to why-question answ ering. The starting-point is a system that retrieves a relevant answ er for 73% o f the test questions. However, in 41% o f these cases, the h ighest ranked relevant answ er is no t ranked in the top-10. We aim to im prove the ranking by adding a re ­ ranking m odule. For re-ranking w e con­ sider 31 featu...

The paper reviews some axioms of additivity concerning ranking methods used for generalized tournaments with possible missing values and multiple comparisons. It is shown that one of the most natural properties, called consistency, has strong links to independence of irrelevant comparisons, an axiom judged unfavourable when players have different opponents. Therefore some directions of weakenin...

We present a method that identifies speakers that are likely to have a high false-reject rate in a text-dependent speaker verification system (“goats”). The method normally uses only the enrollment data to perform this task. We begin with extracting an appropriate feature from each enrollment session. We then rank all the enrollment sessions in the system based on this feature. The lowest-ranki...

A regression analysis of results from the Times Higher Education World University Rankings (THES-Ranking) from 2010-2014 shows high fluctuations in the rank and score for lower scoring universities (below position 50) which lead to inconsistent “up and downs” in the total results. We conclude that these fluctuations do not correspond to actual university performance. They create the impression ...

In the database retrieval and nearest neighbor classification tasks, the two basic problems are to represent the query and database objects, and to learn the ranking scores of the database objects to the query. Many studies have been conducted for the representation learning and the ranking score learning problems, however, they are always learned independently from each other. In this paper, w...

This paper describes the iLab-Edinburgh Sentiment Analysis system, winner of the Arabic Twitter Task 7 in SemEval-2016. The system employs a hybrid approach of supervised learning and rule-based methods to predict a sentiment intensity (SI) score for a given Arabic Twitter phrase. First, the supervised method uses an ensemble of trained linear regression models to produce an initial SI score fo...

Cell tracking is often implemented as cell detection and data association steps. For a particular detection output it is a challenge to automatically select the best association algorithm. We approach this challenge by developing novel measures for ranking the association algorithms according to their performance without the need for a ground truth. We formulate tracking as a binary classi cati...

Fuzzy risk analysis, as a powerful tool to address uncertain information, can provide an appropriate method for risk analysis. However, the previous fuzzy risk analysis methods still have some weaknesses. To overcome the weaknesses of existing fuzzy risk analysis methods, a novel method for ranking generalized fuzzy numbers is proposed for addressing fuzzy risk analysis problems. In the propose...