José L. Vicedo

TREC: Experiment and evaluation in information retrieval

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Question Answering in Restricted Domains: An Overview

Automated question answering has been a topic of research and development since the earliest AI applications. Computing power has increased since the first such systems were developed, and the general methodology has changed from the use of hand-encoded knowledge bases about simple domains to the use of text collections as the main knowledge source over more complex domains. Still, many research issues remain. The focus of this article is on the use of restricted domains for automated question answering. The article contains a historical perspective on question answering over restricted domains and an overview of the current methods and applications used in restricted domains. A main characteristic of question answering in restricted domains is the integration of domain-specific information that is either developed for question answering or that has been developed for other purposes. We explore the main methods developed to leverage this domain-specific information.Automated question answering has been a topic of research and development since the earliest AI applications. Computing power has increased since the first such systems were developed, and the general methodology has changed from the use of hand-encoded knowledge bases about simple domains to the use of text collections as the main knowledge source over more complex domains. Still, many research issues remain. The focus of this article is on the use of restricted domains for automated question answering. The article contains a historical perspective on question answering over restricted domains and an overview of the current methods and applications used in restricted domains. A main characteristic of question answering in restricted domains is the integration of domain-specific information that is either developed for question answering or that has been developed for other purposes. We explore the main methods developed to leverage this domain-specific information.

Splitting Complex Temporal Questions for Question Answering Systems

This paper presents a multi-layered Question Answering (Q.A.) architecture suitable for enhancing current Q.A. capabilities with the possibility of processing complex questions. That is, questions whose answer needs to be gathered from pieces of factual information scattered in different documents. Specifically, we have designed a layer oriented to process the different types of temporal questions. Complex temporal questions are first decomposed into simpler ones, according to the temporal relationships expressed in the original question.In the same way, the answers of each simple question are re-composed, fulfilling the temporal restrictions of the original complex question.Using this architecture, a Temporal Q.A. system has been developed.In this paper, we focus on explaining the first part of the process: the decomposition of the complex questions. Furthermore, it has been evaluated with the TERQAS question corpus of 112 temporal questions. For the task of question splitting our system has performed, in terms of precision and recall, 85% and 71%, respectively.

Importance of pronominal anaphora resolution in question answering systems

The main aim of this paper is to analyse the effects of applying pronominal anaphora resolution to Question Answering (QA) systems. For this task a complete QA system has been implemented. System evaluation measures performance improvements obtained when information that is referenced anaphorically in documents is not ignored.A hydro-thermic energy converter capable to convert thermal energy contained in hot water in mechanical energy by utilizing the low Curie-temperature property of ferromagnetic alloys in a directional magnetic field alternation of the ferromagnetic property of said alloy such that a magnetic one-directional tractive force resolves.

Enhancing QA systems with complex temporal question processing capabilities

This paper presents a multilayered architecture that enhances the capabilities of current QA systems and allows different types of complex questions or queries to be processed. The answers to these questions need to be gathered from factual information scattered throughout different documents. Specifically, we designed a specialized layer to process the different types of temporal questions. Complex temporal questions are first decomposed into simple questions, according to the temporal relations expressed in the original question. In the same way, the answers to the resulting simple questions are recomposed, fulfilling the temporal restrictions of the original complex question. A novel aspect of this approach resides in the decomposition which uses a minimal quantity of resources, with the final aim of obtaining a portable platform that is easily extensible to other languages. In this paper we also present a methodology for evaluation of the decomposition of the questions as well as the ability of the implemented temporal layer to perform at a multilingual level. The temporal layer was first performed for English, then evaluated and compared with: a) a general purpose QA system (F-measure 65.47% for QA plus English temporal layer vs. 38.01% for the general QA system), and b) a well-known QA system. Much better results were obtained for temporal questions with the multilayered system. This system was therefore extended to Spanish and very good results were again obtained in the evaluation (F-measure 40.36% for QA plus Spanish temporal layer vs. 22.94% for the general QA system).

The QALL-ME Framework: A specifiable-domain multilingual Question Answering architecture

This paper presents the QALL-ME Framework, a reusable architecture for building multi- and cross-lingual Question Answering (QA) systems working on structured data modelled by an ontology. It is released as free open source software with a set of demo components and extensive documentation, which makes it easy to use and adapt. The main characteristics of the QALL-ME Framework are: (i) its domain portability, achieved by an ontology modelling the target domain; (ii) the context awareness regarding space and time of the question; (iii) the use of textual entailment engines as the core of the question interpretation; and (iv) an architecture based on Service Oriented Architecture (SOA), which is realized using interchangeable web services for the framework components. Furthermore, we present a running example to clarify how the framework processes questions as well as a case study that shows a QA application built as an instantiation of the QALL-ME Framework for cinema/movie events in the tourism domain.

Question Answering in Spanish

This paper describes the architecture, operation and results obtained with the Question Answering prototype for Spanish developed in the Department of Language Processing and Information Systems at the University of Alicante for the CLEF 2003 Spanish monolingual QA evaluation task. Our system has been fully developed from scratch and it combines shallow natural language processing tools with statistical data redundancy techniques. The system is able to perform QA tasks independently from static corpora or from Web documents. Moreover, the World Wide Web can be used as an external resource to obtain evidence to support and complement the CLEF Spanish corpora.

Passage selection to improve Question Answering

Open-Domain Question Answering systems (QA) performs the task of detecting text fragments in a collection of documents that contain the response to users queries. These systems use high complexity tools that reduce its applicability to the treatment of small amounts of text. Consequently, when working on large document collections, QA systems apply Information Retrieval (IR) techniques to reduce drastically text collections to a tractable quantity of relevant text. In this paper, we propose a novel Passage Retrieval (PR) model that performs this task with better performance for QA purposes than current best IR systems

IR-n System at CLEF-2002

Passage Retrieval is an alternative to traditional document-oriented Information Retrieval. These systems use contiguous text fragments (or passages) instead of full documents as the basic unit of information. The IR-n system is a passage retrieval system that uses groups of contiguous sentences as units of information. This paper reports on experiments with the IR-n system at CLEF-2002 where it has obtained considerably better results than in the previous participation in CLEF-2001.

Hen liver and plasma can metabolize hexyl-DCP phosphoramidate at a rate comparable to that of rat

The in vitro and in vivo biochemical properties of O-hexyl, O-dichlorophenyl phosphoramidate (hexyl-DCP) as inhibitor of acetylcholinesterase (AChE) and neuropathy target esterase (NTE) were studied, as well as their neurotoxic effects. The differences found were suggested to be due to biotransformation effects. In this work, the in vitro time-dependent degradation of hexyl-DCP by plasma, liver and brain homogenates of rat and hen at 37 degrees C at pH 7.4 are studied using 100 nM initial concentration. The loss of inhibitory potency against AChE was used as sensor of the biodegradation rate. An approximate estimation of the residual compound was made by comparison with an inhibition calibration curve. The rate of enzymatic degradation was corrected for the spontaneous hydrolysis. Rat tissues showed some higher activities (24, 17, 1 mU/g for plasma, liver, and brain, respectively) than hen (17, 6, 1 mU/g), with activities being highest for plasma and lowest for brain. Hexyl-DCP is a chiral compound. The loss of anti-AChE power could be due to degradation of only one of the two stereoisomers.