In this paper, we present the gated selfmatching networks for reading comprehension style question answering, which aims to answer questions from a given passage. We first match the question and passage with gated attention-based recurrent networks to obtain the question-aware passage representation. Then we propose a self-matching attention mechanism to refine the representation by matching th...

We have explored the feasibility of automated question answering from video material used in conjunction with PowerPoint slides. We have tested separately and combined two recently becoming popular approaches to question answering: 1) the approach based on deep Natural Language parsing and 2) a self-learning probabilistic pattern matching approach. The advantages and shortcomings of each of the...

This paper presents a Question and Answering system based on predicate-argument matching. Predicate-argument structures are utilized to capture more semantics in questions than a set of keywords. In addition to the predicate-argument matching, relation type matching is also used to handle expressions which are not mediated by verbs.

Users’ interactions with search engines is shifting towards more complex information needs and the need for a deeper semantic understanding of the query intent is needed. In this paper we propose a novel semantic matching criterion that adopts distributed representations of words in order to address complex information needs in a scalable way. We show that combining this criterion with other we...

This paper presents the results of developing subjectivity classifiers for Implicit Opinion Question (IOQ) identification. IOQs are defined as opinion questions with no opinion words. An IOQ example is “will the U.S. government pay more attention to the Pacific Rim?” Our analysis on community questions of Yahoo! Answers shows that a large proportion of opinion questions are IOQs. It is thus imp...

QAnswer is a question answering system that uses DBpedia as a knowledge base and converts natural language questions into a SPARQL query. In order to improve the match between entities and relations and natural language text, we make use of Wikipedia to extract lexicalizations of the DBpedia entities and then match them with the question. These entities are validated on the ontology, while miss...

Answering precise questions requires applying Natural Language techniques in order to locate the answers inside retrieved documents. The QALC system, presented in this paper, participated to the Question Answering track of the TREC8 and TREC9 evaluations. QALC exploits an analysis of documents based on the search for multi-word terms and their variations. These indexes are used to select a mini...

In this paper, we describe a Turkish factoid QA system which uses surface level patterns called answer patterns in order to extract the answers from the documents that are retrieved from the web. The answer patterns are learned using five different answer pattern extraction methods with the help of the web. Our novel approach to extract named entity tagged answer patterns and our new confidence...

The paper describes a question answering system for German called InSicht. All documents in the system are analyzed by a syntactico-semantic parser in order to represent each document sentence by a semantic network (in the MultiNet formalism) or a partial semantic network (if only a parse in chunk mode succeeds). A question sent to InSicht is parsed yielding its semantic network representation ...

Community-based Question Answering (CQA) has become popular in knowledge sharing sites since it allows users to get answers to complex, detailed, and personal questions directly from other users. Large archives of historical questions and associated answers have been accumulated. Retrieving relevant historical answers that best match a question is an essential component of a CQA service. Most s...