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This paper presents a syntax-driven ap- proach to question answering, specifically the answer-sentence selection problem for short-answer questions. Rather than us- ing syntactic features to augment exist- ing statistical classifiers …...

We describe tree edit models for representing sequences of tree transformations involving complex reordering phenomena and demon- strate that they offer a simple, intuitive, and effective method for modeling pairs …...

This paper describes Al-Bayan team participa- tion in SemEval-2015 Task 3, Subtask A. Task 3 targets semantic solutions for answer selec- tion in community question answering systems. We propose a …...

Community Question Answering (cQA) pro- vides new interesting research directions to the traditional Question Answering (QA) field, e.g., the exploitation of the interaction between users and the structure of related …...

AbstractAnswer selection is a core component in any question-answering systems. It aims to select correct answer sentences for a given question from a pool of candidate sentences. In recent years, …...

Community question answering platforms need to automatically rank answers and ques- tions with respect to a given question. In this paper, we present the approaches for the An- swer Selection …...

AbstractThis work studies comparatively two typical sentence matching tasks: textual entailment (TE) and answer selection (AS), observing that weaker phrase alignments are more critical in TE, while stronger phrase alignments …...

AbstractWe present a system for Answer Selection that integrates fine-grained Question Classification with a Deep Learning model designed for Answer Selection. We detail the necessary changes to the Question Classification …...

AbstractAnswer selection is an important but challenging task. Significant progresses have been made in domains where a large amount of labeled training data is available. However, obtaining rich annotated data …...

AbstractAnswer selection is an important research problem, with applications in many areas. Previous deep learning based approaches for the task mainly adopt the Compare-Aggregate architecture that performs word-level comparison followed …...

AbstractIn this paper, we establish the effectiveness of using hard negatives, coupled with a siamese network and a suitable loss function, for the tasks of answer selection and answer triggering. …...

AbstractAnswer selection aims at identifying the correct answer for a given question from a set of potentially correct answers. Contrary to previous works, which typically focus on the semantic similarity …...

AbstractIn Community-based Question Answering system(CQA), Answer Selection(AS) is a critical task, which focuses on finding a suitable answer within a list of candidate answers. For neural network models, the key …...

AbstractIn this paper, we present a fast and strong neural approach for general purpose text matching applications. We explore what is sufficient to build a fast and well-performed text matching …...

AbstractGenerative models for Information Retrieval, where ranking of documents is viewed as the task of generating a query from a document’s language model, were very successful in various IR tasks …...

AbstractCommunity Question Answering (CQA) forums provide answers to many real-life questions. These forums are trendy among machine learning researchers due to their large size. Automatic answer selection, answer ranking, question …...

AbstractDeep neural models have become the mainstream in answer selection, yielding state-of-the-art performance. However, these models tend to rely on spurious correlations between prediction labels and input features, which in …...

AbstractConversational Question Answering (ConvQA) models aim at answering a question with its relevant paragraph and previous question-answer pairs that occurred during conversation multiple times. To apply such models to a …...