Conference Paper

Experiments with Interactive Question-Answering.

DOI: 10.3115/1219840.1219866 Conference: ACL 2005, 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 25-30 June 2005, University of Michigan, USA
Source: DBLP


This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Gen- erated off-line from topic representations of complex scenarios, predictive ques- tions represent requests for information that capture the most salient (and diverse) aspects of a topic. We present experimen- tal results from large user studies (featur- ing a fully-implemented interactive Q/A system named FERRET) that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a Q/A dialogue.

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    • "Statistical measures here were introduced for automatically selecting a number of useful domain-dependent P-A templates, resulting in a completely unsupervised learning of the information structure given a corpus. Kiyota et al. [20]; Dzikovska et al. [21]; Harabagiu et al., [22] proved every P-A structure was not useful for information extraction and retrieval because the predicate argument (P-A) structure generated by a parser as a baseline. In fact, the useful information structure was dependent upon domains [5]. "
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    ABSTRACT: We present a novel scheme of sentence transformation for Indonesian medical question generation (ImeQG) system by utilizing effectively documents for information navigation. Through the ImeQG proposed method, we conducted a general procedure of dependency analysis for extract verbs and relevant phrases to generate natural sentences by applying transformation rules. For this purpose, we defined some P-A templates based on a statistical measure. An experimental evaluation in this proposed method showed 79.00% for precision, 87.80% for recall and 81.50% for F1. Keywords—sentence transformation, predicate argument structure, Indonesian medical sentence, QA-pairs.
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    • "These questions include, for example, a request to evaluate the naturalness of the system in general, but the objectivity of such a method is debatable. Harabagiu et al. (2005) note that in terms of interactive question answering (and in dialogue systems) dialogue as a whole is usually evaluated in terms of: • Efficiency, defined as the number of questions that the user must pose to find particular information; • Effectiveness, defined by the relevance of the answers returned; • User satisfaction. "
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    ABSTRACT: The increasing amount of information available online has led to the development of technologies that help to deal with it. One of them is Interactive Question Answering (IQA), a research field that has emerged at the intersection of question answering and dialogue systems, and which allows users to find the answers to questions in an interactive way. During the answering process, the automatic system can initiate a dialogue with the user in order to clarify missing or ambiguous information, or suggest further topics for discussion. This chapter presents the state-of-the-art in the field of interactive question answering. Given that IQA inherits a lot of features from dialogue systems and question answering, these fields are also briefly presented. Analysis of the existing systems reveals that in general IQA systems rely on a scaled-down version of a dialogue system, sometimes built on top of question answering systems. Evaluation of IQA is also discussed, showing that it combines evaluation techniques from question answering and dialogue systems.
    No preview · Chapter · Oct 2013
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    • "Our proposed scheme solves this problem by using information extraction based on semantic parsing from web texts, without constructing an RDB. We adopt the predicateargument (P-A) structure generated by a parser as a baseline, but every P-A structure is not useful for information extraction and retrieval(Y.Kiyota et al., 2002; M.O.Dzikovska et al., 2003; S.Harabagiu et al., 2005). In fact, the useful information structure is dependent on domains. "
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    ABSTRACT: We present a novel scheme of spoken dialogue systems which uses the up-to-date information on the web. The scheme is based on information extraction which is defined by the predicate-argument (P-A) structure and realized by semantic parsing. Based on the information structure, the dialogue system can perform question answering and also proactive information presentation. Feasibility of this scheme is demonstrated with experiments using a domain of baseball news. In order to automatically select useful domain-dependent P-A templates, statistical measures are introduced, resulting to a completely unsupervised learning of the information structure given a corpus. Similarity measures of P-A structures are also introduced to select relevant information. An experimental evaluation shows that the proposed system can make more relevant responses compared with the conventional "bag-of-words" scheme.
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