Our QA system consists of two different components. One is for the factoid and list questions, and the other is for the other questions. The components are processed individually, and each result is combined into our submitted run. For the factoid questions, we have tried to find answers by proximity-based named entity search. Given a question, fine-grained named entities for candidate answers ...

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used to evaluate tumor permeability, yet measurements have not been directly validated in brain tumors. Our purpose was to compare estimates of forward leakage K(trans) derived from DCE-MRI to the estimates K obtained using [(14)C]aminoisobutyric acid quantitative autoradiography ([(14)C]AIB QAR), an established method of ...

Abstract With the swift growth of information over past few years, taking full benefit is increasingly essential. Question Answering System one promising methods to access this much information. The lacks humans’ common sense and reasoning power cannot identify unanswerable questions irrelevant questions. These are answered by making unreliable incorrect guesses. In paper, we address limitation...

Visual Question Answering (VQA) has attracted much attention in both computer vision and natural language processing communities, not least because it offers insight into the relationships between two important sources of information. Current datasets, and the models built upon them, have focused on questions which are answerable by direct analysis of the question and image alone. The set of su...

Recently, quaternion collaborative representationbased classification (QCRC) and quaternion sparse representation-based classification (QSRC) have been proposed for color face recognition. They can obtain correlation information among different color channels. However, their performance is unstable in different conditions. For example, QSRC performs better than than QCRC on some situations but ...

In this paper, we describe our experimentations in answer formulation for question-answering (QA) systems. In the context of QA, answer formulation can serve two purposes: improving answer extraction or improving human-computer interaction (HCI). Each purpose has different precision/recall requirements. We present our experiments for both purposes and argue that formulations of better linguisti...

What is the importance of cooperativity? That depends on the system, but let’s take hemoglobin. Hemoglobin’s mission is to pick up a large amount of oxygen in the lungs, where the oxygen concentration (or partial pressure) is about 100 torr, and then drop off a good fraction of it in the peripheral tissues where the oxygen concentration is about 20 torr. Cooperativity helps make this transport ...

Each day, millions of people ask questions and search for answers on the World Wide Web. Due to this, the Internet has grown to a world wide database of questions and answers, accessible to almost everyone. Since this database is so huge, it is hard to find out whether a question has been answered or even asked before. As a consequence, users are asking the same questions again and again, produ...