876 resultados para Recall-Precision Curves
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The present is marked by the availability of large volumes of heterogeneous data, whose management is extremely complex. While the treatment of factual data has been widely studied, the processing of subjective information still poses important challenges. This is especially true in tasks that combine Opinion Analysis with other challenges, such as the ones related to Question Answering. In this paper, we describe the different approaches we employed in the NTCIR 8 MOAT monolingual English (opinionatedness, relevance, answerness and polarity) and cross-lingual English-Chinese tasks, implemented in our OpAL system. The results obtained when using different settings of the system, as well as the error analysis performed after the competition, offered us some clear insights on the best combination of techniques, that balance between precision and recall. Contrary to our initial intuitions, we have also seen that the inclusion of specialized Natural Language Processing tools dealing with Temporality or Anaphora Resolution lowers the system performance, while the use of topic detection techniques using faceted search with Wikipedia and Latent Semantic Analysis leads to satisfactory system performance, both for the monolingual setting, as well as in a multilingual one.
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This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system for the recognition and normalization of temporal expressions originally developed for Spanish. TERSEO was first extended to English through the automatic translation of the temporal expressions. Then, an improved porting process was applied to Italian, where the automatic translation of the temporal expressions from English and from Spanish was combined with the extraction of new expressions from an Italian annotated corpus. Experimental results demonstrate how, while still adhering to the rule-based paradigm, the development of automatic rule translation procedures allowed us to minimize the effort required for porting to new languages. Relying on such procedures, and without any manual effort or previous knowledge of the target language, TERSEO recognizes and normalizes temporal expressions in Italian with good results (72% precision and 83% recall for recognition).
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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.
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In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.
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In this paper a multilingual method for event ordering based on temporal expression resolution is presented. This method has been implemented through the TERSEO system which consists of three main units: temporal expression recognizing, resolution of the coreference introduced by these expressions, and event ordering. By means of this system, chronological information related to events can be extracted from documental databases. This information is automatically added to the documental database in order to allow its use by question answering systems in those cases referring to temporality. The system has been evaluated obtaining results of 91 % precision and 71 % recall. For this, a blind evaluation process has been developed guaranteing a reliable annotation process that was measured through the kappa factor.
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Este artículo presenta un nuevo algoritmo de fusión de clasificadores a partir de su matriz de confusión de la que se extraen los valores de precisión (precision) y cobertura (recall) de cada uno de ellos. Los únicos datos requeridos para poder aplicar este nuevo método de fusión son las clases o etiquetas asignadas por cada uno de los sistemas y las clases de referencia en la parte de desarrollo de la base de datos. Se describe el algoritmo propuesto y se recogen los resultados obtenidos en la combinación de las salidas de dos sistemas participantes en la campaña de evaluación de segmentación de audio Albayzin 2012. Se ha comprobado la robustez del algoritmo, obteniendo una reducción relativa del error de segmentación del 6.28% utilizando para realizar la fusión el sistema con menor y mayor tasa de error de los presentados a la evaluación.
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Paper submitted to the XVIII Conference on Design of Circuits and Integrated Systems (DCIS), Ciudad Real, España, 2003.
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Paper submitted to 10th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Sharjah, Emiratos Árabes, 2003.
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Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey at the European Southern Observatory Very Large Telescope. Aims. A key aim is to provide precise radial velocities (RVs) and projected equatorial velocities (vsini) for representative samples of Galactic stars, which will complement information obtained by the Gaia astrometry satellite. Methods. We present an analysis to empirically quantify the size and distribution of uncertainties in RV and vsini using spectra from repeated exposures of the same stars. Results. We show that the uncertainties vary as simple scaling functions of signal-to-noise ratio (S/N) and vsini, that the uncertainties become larger with increasing photospheric temperature, but that the dependence on stellar gravity, metallicity and age is weak. The underlying uncertainty distributions have extended tails that are better represented by Student’s t-distributions than by normal distributions. Conclusions. Parametrised results are provided, which enable estimates of the RV precision for almost all GES measurements, and estimates of the vsini precision for stars in young clusters, as a function of S/N, vsini and stellar temperature. The precision of individual high S/N GES RV measurements is 0.22–0.26 km s-1, dependent on instrumental configuration.
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A single and very easy to use Graphical User Interface (GUI- MATLAB) based on the topological information contained in the Gibbs energy of mixing function has been developed as a friendly tool to check the coherence of NRTL parameters obtained in a correlation data procedure. Thus, the analysis of the GM/RT surface, the GM/RT for the binaries and the GM/RT in planes containing the tie lines should be necessary to validate the obtained parameters for the different models for correlating phase equlibrium data.
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Superior recall of domain-specific patterns is well established as a defining attribute of expert performers. Recent studies on the developmental histories of expert team ball sport players (e.g. Baker, Côté, & Abernethy, 2003a) also suggest that experts characteristically receive exposure to a wide range of sports in their developing years and that this related sports experience may reduce the amount of sport-specific training needed to become an expert. This study examined whether the facilitation of expertise associated with other sport experience might arise from positive transfer of pattern recall skills from one sport to another. Expert netball, basketball and field hockey players and experienced non-experts performed a recall task for patterns of play derived from each of these sports. Experts from sports different to those shown in the presented pattern consistently outperformed non-experts in their recall of defensive player positions, suggesting some selective transfer of pattern recall skills may indeed be possible
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This paper introduces a more sophisticated modelling of the labour market functioning of the European member and candidate states through the introduction of labour supply curves in an applied general equilibrium model. A labour supply curve offers a middle way in labour supply modelling, sitting between the two commonly adopted extremes of spare capacity and full employment. The first part of the paper outlines the theoretical foundation of the labour supply curve. Real world data is then used to derive labour supply curves for each member state, along with Croatia and Turkey. Finally, the impact of the newly specified labour markets on the results of an illustrative scenario involving reform of the common agricultural policy is explored. The results of computable general equilibrium analysis with the labour supply curve confirm the theoretical expectation that modelling the labour supply through an upwards-sloping curve produces results that lie between the extremes of spare capacity of the labour factor and fully employed labour. This specification captures a greater degree of heterogeneity in the labour markets of the member and candidate states, allowing for a more nuanced modelling of the effects of policy reform, including welfare effects.
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Internet traffic classification is a relevant and mature research field, anyway of growing importance and with still open technical challenges, also due to the pervasive presence of Internet-connected devices into everyday life. We claim the need for innovative traffic classification solutions capable of being lightweight, of adopting a domain-based approach, of not only concentrating on application-level protocol categorization but also classifying Internet traffic by subject. To this purpose, this paper originally proposes a classification solution that leverages domain name information extracted from IPFIX summaries, DNS logs, and DHCP leases, with the possibility to be applied to any kind of traffic. Our proposed solution is based on an extension of Word2vec unsupervised learning techniques running on a specialized Apache Spark cluster. In particular, learning techniques are leveraged to generate word-embeddings from a mixed dataset composed by domain names and natural language corpuses in a lightweight way and with general applicability. The paper also reports lessons learnt from our implementation and deployment experience that demonstrates that our solution can process 5500 IPFIX summaries per second on an Apache Spark cluster with 1 slave instance in Amazon EC2 at a cost of $ 3860 year. Reported experimental results about Precision, Recall, F-Measure, Accuracy, and Cohen's Kappa show the feasibility and effectiveness of the proposal. The experiments prove that words contained in domain names do have a relation with the kind of traffic directed towards them, therefore using specifically trained word embeddings we are able to classify them in customizable categories. We also show that training word embeddings on larger natural language corpuses leads improvements in terms of precision up to 180%.
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In this consensus document we summarize the current knowledge on major asthma, rhinitis, and atopic dermatitis endotypes under the auspices of the PRACTALL collaboration platform. PRACTALL is an initiative of the European Academy of Allergy and Clinical Immunology and the American Academy of Allergy, Asthma & Immunology aiming to harmonize the European and American approaches to best allergy practice and science. Precision medicine is of broad relevance for the management of asthma, rhinitis, and atopic dermatitis in the context of a better selection of treatment responders, risk prediction, and design of disease-modifying strategies. Progress has been made in profiling the type 2 immune response-driven asthma. The endotype driven approach for non-type 2 immune response asthma, rhinitis, and atopic dermatitis is lagging behind. Validation and qualification of biomarkers are needed to facilitate their translation into pathway-specific diagnostic tests. Wide consensus between academia, governmental regulators, and industry for further development and application of precision medicine in management of allergic diseases is of utmost importance. Improved knowledge of disease pathogenesis together with defining validated and qualified biomarkers are key approaches to precision medicine.
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EINLEITUNG Anhand eines Pelvitrainer Modells wurde ein sogenannter „Handheld Roboter“ (Kymerax© Precision- Drive Articulating Surgical System von Terumo©) mit konventionellen laparoskopischen Instrumenten verglichen. Das Kymerax© System verfügt über eine Instrumentenspitze, welche durch Knöpfe am Handgriff zusätzlich abgewinkelt und rotiert werden kann. METHODE 45 Probanden wurden in 2 Erfahrungsgruppen aufgeteilt: 20 ExpertInnen (mehr als 50 selbstständig durchgeführte laparoskopische Operationen pro Jahr) und 25 StudentInnen (keine Erfahrung in der Laparoskopie). Sie führten 6 standardisierte Übungen durch, wobei die ersten beiden Übungen jeweils nur der Instrumenteninstruktion dienten und nicht ausgewertet wurden. In den restlichen 4 Übungen wurden Zeit, Fehleranzahl und Präzision erfasst. Es wurde in 2 Gruppen randomisiert. Eine Gruppe führte die Übungen zuerst mit dem konventionellen System und dann mit dem Kymerax© System durch. Bei der anderen Gruppe erfolgten die Übungen in umgekehrter Reihenfolge. Am Ende beantworteten die Teilnehmer Fragen zu den Übungen und den Operationssystemen. Die Daten wurden mittels Varianzanalyse ausgewertet. RESULTATE In allen 4 gemessenen Übungen brauchten die Probanden mit Kymerax© signifikant mehr Zeit (20%-40%). Vorteile des Kymerax© Systems waren eine bessere Nadelkontrolle bei einer auf den Operateur gerichteten Stichrichtung, eine geringere Abweichung beim Schneiden einer graden Linie, sowie ein geringeres Ausfransen der Schnittlinie beim graden wie beim runden Schneiden. Im Gegensatz zu den Experten kamen Studenten, welche das Kymerax© System in der zweiten Runde verwendeten, besser mit diesem zu Recht, als Ihre Studentenkollegen, die das Kymerax© System in der ersten Runde verwendeten. In der Befragung gaben über 90% der Teilnehmer an, dass das Kymerax© System bei der Durchführung der Übungen einen Vorteil bringt. Die Probanden empfanden jedoch die Bedienung als gewöhnungsbedürftig und erschöpften mit dem Kymerax© System schneller. Bemängelt wurde beim Kymerax© System die nicht freie Rotation, die eingeschränkte Abwinklung, die Sichteinschränkung durch den 7mm Schaft sowie die Ergonomie des Handgriffs. DISKUSSION Das Kymerax© System bringt Vorteile bei gewissen komplexen laparoskopischen Aufgaben. Der Preis hierfür ist die langsamere Durchführung der Aufgaben, die längere Angewöhnungszeit an das Instrument sowie die schnellere Ermüdung des Benutzers. Das System zeigt ein grosses Potential für die laparoskopische Chirurgie, jedoch sind weitere Verbesserungen notwendig. Von der Firma Terumo© wurde zwischenzeitlich das Operationssystem vom Markt genommen.