This FYI RFC is one of two FYI’s called, "Questions and Answers" (Q/A), produced by the User Services Working Group of the Internet Engineering Task Force (IETF). The goal is to document the most commonly asked questions and answers in the Internet. New Questions and Answers In addition to updating information contained in the previous version of this FYI RFC, the following new questions have b...

Open forum threads exhibit a great variability in the quality and quantity of the answers they attract, making it difficult to manually moderate and separate relevant from irrelevant content. The goal of SemEval 2015 Task 3 (Subtask A, English) is to build systems that automatically distinguish between relevant and irrelevant content in forum threads. We extend a short answer assessment system ...

This paper describes the KeLP system participating in the SemEval-2016 Community Question Answering (cQA) task. The challenge tasks are modeled as binary classification problems: kernel-based classifiers are trained on the SemEval datasets and their scores are used to sort the instances and produce the final ranking. All classifiers and kernels have been implemented within the Kernel-based Lear...

This paper describes the Entrance Exams task at the CLEF QA Track 2015. Following the last two editions, the data set has been extracted from actual university entrance examinations including a variety of topics and question types. Systems receive a set of Multiple-Choice Reading Comprehension tests where the task is to select the correct answer among a finite set of candidates, according to th...

We present a Question Answering system for technical domains which makes an intelligent use of paraphrases to increase the likelihood of finding the answer to the user’s question. The system implements a simple and efficient logic representation of questions and answers that maps paraphrases to the same underlying semantic representation. Further, paraphrases of technical terminology are dealt ...

In this paper, we explore the utility of attitude types for improving question answering (QA) on both web-based discussions and news data. We present a set of attitude types developed with an eye toward QA and show that they can be reliably annotated. Using the attitude annotations, we develop automatic classifiers for recognizing two main types of attitudes: sentiment and arguing. Finally, we ...

We present the implementation of an autonomous chatbot, SHIHbot, deployed on Facebook, which answers a wide variety of sexual health questions on HIV/AIDS. The chatbot's response database is compiled from professional medical and public health resources in order to provide reliable information to users. The system's backend is NPCEditor, a response selection platform trained on linked questions...

The online participatory exam transforms the traditional exam into a constructivist, cooperative and engaging learning experience. Students learn from designing and answering exam questions, from evaluating their peers’ performance, and from reading questions, answers and evaluations. This paper, aimed at faculty who teach online and at researchers interested in online learning, describes the p...

Presented herein is a novel model for similar question ranking within collaborative question answer platforms. The presented approach integrates a regression stage to relate topics derived from questions to those derived from question-answer pairs. This helps to avoid problems caused by the differences in vocabulary used within questions and answers, and the tendency for questions to be shorter...