MUC-4 evaluation metrics

Chinchor, Nancy

doi:10.3115/1072064.1072067

Cited by 467 publications

(278 citation statements)

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“…Podem-se estabelecer alguns pesos diferentes para cada medida (Precisão e Abrangência), dando flexibilidade para a definição de critérios de importância (Chinchor, 1992;Sasaki, 2007). Chinchor (1992) define a Média-F pela Equação 3.…”

Section: Média-funclassified

Uma arquitetura hibrida para a indexação de documentos do Diário Oficial do Município de Cachoeiro de Itapemirim

Xavier¹,

Silva²,

Gomes

2015

Transinformação

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ResumoTécnicas de Mineração de Textos vêm sendo amplamente utilizadas para processamento de grandes volumes de documentos. Contudo, ainda há uma grande defasagem na tentativa de definir uma arquitetura para sistemas transacionais com elementos de inteligência computacional. Este trabalho tem o objetivo de apresentar uma proposta de arquitetura para a construção de um sistema computacional que utiliza técnicas de Mineração de Textos para indexar conteúdos da base do Diário Oficial do município de Itapemirim, no estado do Espírito Santo, transformando a informação antes disponível em linguagem natural para um formato estruturado, passível de ser persistido. Para validar a arquitetura, foi desenvolvido um protótipo em linguagem Java acessível no ambiente Web. Para avaliação da ferramenta, o estudo de caso proposto contou com uma base composta por 22 documentos, contendo 198 atos normativos da base daquele Diário Oficial, para os quais foram identificados bons níveis de precisão e abrangência na recuperação da informação. Este trabalho contribui com a apresentação de uma arquitetura híbrida, composta por elementos do modelo de sistemas transacionais e elementos da Mineração de Textos, além da utilização de padrões de projetos de software. Palavras-chave: Diário Oficial de Cachoeiro de Itapemirim. Indexação de documentos. Mineração de textos. Recuperação da informação. Abstract Text mining techniques have been widely used to process large volumes of documents. However, there is still a large gap when defining the architecture for systems with transactional elements of computational intelligence. The aim of the paper is to outline a proposed architecture to build a computational system that uses text mining techniques to index content from the database of the Official Gazette in the city of

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Section: Média-funclassified

Uma arquitetura hibrida para a indexação de documentos do Diário Oficial do Município de Cachoeiro de Itapemirim

Xavier¹,

Silva²,

Gomes

2015

Transinformação

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“…Yellow Page style). We have carried out evaluation of this application using traditional IE metrics [8,22]: precision, recall, and f-score. An expert manually annotated 5 documents and we compared the results of the system annotations against this gold standard set.…”

Section: Fig 4 Obie For International Company Intelligencementioning

confidence: 99%

Ontology-Based Information Extraction for Business Intelligence

et al. 2007

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Abstract. Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

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“…The F-measure provides a way of combining recall 429 and prediction to get a single measure which falls between recall 430 and precision. Thus, the F-measure is calculated as the harmonic 431 mean of precision and recall and tends towards the lower of the 432 two (Chinchor, 1992):…”

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Automated classification of urban locations for environmental noise impact assessment on the basis of road-traffic content

Torija

Ruíz

2016

Expert Systems with Applications

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a b s t r a c tUrban and road planners must take right decisions related to urban traffic management and controlling noise pollution. Their assessments and resolutions have important consequences on the annoyance of population exposed to road-traffic-noise and controlling other environmental pollutants (e.g. NOx or ultrafine particles emitted by heavy vehicles). One of the key decisions is the selection of which noise control actions should be taken in sensitive areas (residential or hospital areas, school areas etc), that could include costly measures such as reducing the overall traffic, banning or reducing traffic of heavy vehicles, inspection of motorbikes sound emission, etc. For an efficient decision-making in noise control actions, it is critical to classify a given location in a sensitive area according to the different prevailing traffic conditions. This paper outlines an expert system aimed to help urban planners to classify urban locations based on their traffic composition. To induce knowledge into the system, several machine learning algorithms are used, based on multi-layer Perceptron and support vector machines with sequential minimal optimization. As input variables for these algorithms, a combination of environment variables was used. For the development of the classification models, four feature selection techniques, i.e., two subset evaluation (correlation-based feature-subset selection and consistency-based subset evaluation) and two attribute evaluation (ReliefF and minimum redundancy maximum relevance) were implemented to reduce the models' complexity. The overall procedure was tested on a full database collected in the city of Granada (Spain), which includes urban locations with road-traffic as dominant noise source. Among all the possibilities tested, support vector machines based models achieves the better results in classifying the considered urban locations into the 4 categories observed, with values of average weighted F-measure and Kappa statistics (used as indicators) up to 0.9 and 0.8. Regarding the feature selection techniques, attribute evaluation algorithms (ReliefF and mRMR) achieve better classification results than subset evaluation algorithms in reducing the model complexity, and so relevant environmental variables are chosen for the proposed procedure. Results show that these tools can be used for addressing a prompt assessment of potential road-traffic-noise related problems, as well as for gathering information in order to take more well-founded actions against urban road-traffic noise.

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MUC-4 evaluation metrics

Cited by 467 publications

References 1 publication

Uma arquitetura hibrida para a indexação de documentos do Diário Oficial do Município de Cachoeiro de Itapemirim

Uma arquitetura hibrida para a indexação de documentos do Diário Oficial do Município de Cachoeiro de Itapemirim

Ontology-Based Information Extraction for Business Intelligence

Automated classification of urban locations for environmental noise impact assessment on the basis of road-traffic content

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