Morphological Cues for Lexical Semantics

Most natural language processing tasks require lexical semantic information. Automated acquisition of this information would thus increase the robustness and portability of NLP systems. This paper describes an acquisition method which makes use of fixed correspondences between derivational affixes and lexical semantic information. One advantage of this method, and of other methods that rely only on surface characteristics of language, is that the necessary input is currently available

Analyses for elucidating current question answering technology

Journal ArticleIn this paper, we take a detailed look at the performance of components of an idealized question answering system on two diff erent tasks: the TREC Question Answering task and a set of reading comprehension exams. We carry out three types of analysis: inherent properties of the data, feature analysis, and performance bounds. Based on these analyses we explain some of the performance results of the current generation of Q/A systems and make predictions on future work. In particular, we present four fi ndings: (1) Q/A system performance is correlated with answer repetition; (2) relative overlap scores are more effective than absolute overlap scores; (3) equivalence classes on scoring functions can be used to quantify performance bounds; and (4) perfect answer typing still leaves a great deal of ambiguity for a Q/A system because sentences often contain several items of the same type

How to Evaluate your Question Answering System Every Day and Still Get Real Work Done

In this paper, we report on Qaviar, an experimental automated evaluation system for question answering applications. The goal of our research was to find an automatically calculated measure that correlates well with human judges' assessment of answer correctness in the context of question answering tasks. Qaviar judges the response by computing recall against the stemmed content words in the human-generated answer key. It counts the answer correct if it exceeds agiven recall threshold. We determined that the answer correctness predicted by Qaviar agreed with the human 93% to 95% of the time. 41 question-answering systems were ranked by both Qaviar and human assessors, and these rankings correlated with a Kendall's Tau measure of 0.920, compared to a correlation of 0.956 between human assessors on the same data.Comment: 6 pages, 3 figures, to appear in Proceedings of the Second International Conference on Language Resources and Evaluation (LREC 2000

Child Care in the Postwelfare Reform Era: Analysis and Strategies for Advocates

Adequate child care is essential to enable poor women to support their families with work outside the home. In 1994 the U.S. General Accounting Office found that offering a child care subsidy to poor mothers increased the likelihood by 15 percent that the mothers would work. An Illinois study found that 20 percent of parents who left public assistance for work returned to assistance because of child care problems. In Minnesota a study found that lack of child care caused 14 percent of parents awaiting child care subsidies to leave their jobs and rely on public assistance. These studies confirm what advocates know: Poor parents, like other parents, cannot work without child care. The goal of this article is to assist advocates in helping their clients access quality child care and assuring that they do not lose needed public assistance when child care is unavailable

Looking Under the Hood : Tools for Diagnosing your Question Answering Engine

In this paper we analyze two question answering tasks : the TREC-8 question answering task and a set of reading comprehension exams. First, we show that Q/A systems perform better when there are multiple answer opportunities per question. Next, we analyze common approaches to two subproblems: term overlap for answer sentence identification, and answer typing for short answer extraction. We present general tools for analyzing the strengths and limitations of techniques for these subproblems. Our results quantify the limitations of both term overlap and answer typing to distinguish between competing answer candidates.Comment: Revision of paper appearing in the Proceedings of the Workshop on Open-Domain Question Answerin

Murine Typhus and Leptospirosis as Causes of Acute Undifferentiated Fever, Indonesia

To investigate rickettsioses and leptospirosis among urban residents of Semarang, Indonesia, we tested the blood of 137 patients with fever. Evidence of Rickettsia typhi, the agent of murine typhus, was found in 9 patients. Another 9 patients showed inconclusive serologic results. Thirteen patients received a diagnosis of leptospirosis. No dual infections were detected

A BURST-BAUS consensus document for best practice in the conduct of scrotal exploration for suspected testicular torsion : the Finding consensus for orchIdopeXy In Torsion (FIX-IT) study

Acknowledgements The authors would like to thank Jacqueline Emkes and Rachel Jury for their contribution to our protocol development with respect to patient and public involvement. Similarly, the authors would like to thank Dr Matthew Coward, Department of Urology, University of North Carolina, and Dr Selcuk Sarikaya, Department of Urology, University of Ankara, for their international perspectives and input to our study protocol. We would like to acknowledge the BAUS Trustees for allowing this collaboration. Unrelated to this work, The BURST Research Collaborative would like to acknowledge funding from the BJUI, the Urology Foundation, Ferring Pharmaceuticals Ltd, Rosetrees Trust and Action Bladder Cancer UK. Veeru Kasivisvanathan is an Academic Clinical Lecturer funded by the United Kingdom National Institute for Health Research (NIHR). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. PubMed Indexed Collaborative Authors: Matthew Coward, Selcuk Sarikaya, Jacqueline Emkes, Rachel Jury. Research Funding Department of Health National Institute for Health Research National Institute for Health Research Rosetrees Trust Ferring Pharmaceuticals Urology Foundation University of North CarolinaPeer reviewedPublisher PD

Affective interaction with a virtual character through an fNIRS brain-computer interface

Affective brain-computer interfaces (BCI) harness Neuroscience knowledge to develop affective interaction from first principles. In this article, we explore affective engagement with a virtual agent through Neurofeedback (NF). We report an experiment where subjects engage with a virtual agent by expressing positive attitudes towards her under a NF paradigm. We use for affective input the asymmetric activity in the dorsolateral prefrontal cortex (DL-PFC), which has been previously found to be related to the high-level affective-motivational dimension of approach/avoidance. The magnitude of left-asymmetric DL-PFC activity, measured using functional near infrared spectroscopy (fNIRS) and treated as a proxy for approach, is mapped onto a control mechanism for the virtual agent’s facial expressions, in which action units (AUs) are activated through a neural network. We carried out an experiment with 18 subjects, which demonstrated that subjects are able to successfully engage with the virtual agent by controlling their mental disposition through NF, and that they perceived the agent’s responses as realistic and consistent with their projected mental disposition. This interaction paradigm is particularly relevant in the case of affective BCI as it facilitates the volitional activation of specific areas normally not under conscious control. Overall, our contribution reconciles a model of affect derived from brain metabolic data with an ecologically valid, yet computationally controllable, virtual affective communication environment