<p>This thesis describes and introduces novel methods for knowledge discovery and presents a software system that is able to extract information from biomedical literature, review interesting connections between various biomedical concepts and in so doing, generates new hypotheses. The experimental results obtained by using methods described in this thesis, are compared to currently published results obtained by other methods and a number of case studies are described. This thesis shows how the technology&nbsp / resented can be integrated with the researchers&rsquo / own knowledge, experimentation and observations for optimal progression of scientific research.</p>

Coral reef habitats are being threatened by global warming, natural disasters and the increased pressure of the global population. These habitats are in urgent need of efficient monitoring and management programs to sustain their biological, economic and cultural values for the global community. Habitats maps, describing the extent, composition and the condition of the benthos in time and space, form a valuable information source for scientists and managers to answer their management questions. Adequate and accurate habitat maps are needed and can be provided by a range of mapping approaches, which are based on integration of field and remotely sensed image data sets. Scientists, technicians and managers lack knowledge on the cost effectiveness and procedures for calibrating and validating mapping approaches that integratef field data and remote sensing imagery, for use in various coral reef and seagrass environments. This knowledge is required to adequately design, apply and assess operational mapping approaches and their maps. Hence, the aim of this study is to improve habitat mapping capabilities by integrating low cost remote sensing approaches and field-calibration and -validation methods for a range of coral reef and seagrass environments. To achieve this aim, commonly used habitat mapping approaches that integrated field-calibration and -validation methods with remote sensing image based processing techniques were studied, in different coral reef and seagrass environments in Fiji and Australia. These environments varied in: water clarity, water depth, benthic composition, spatial complexity of benthic features, and remoteness. The study had three objectives: (1) to evaluate the accuracy, cost and perceived relevance of eight commonly used benthic cover mapping approaches for three different coral reef environments. (2) Conduct a cost-benefit comparison of two field survey methods for calibrating and validating maps of coral reef benthos derived from high-spatial resolution satellite images in three different coral reef environments. (3) Identify considerations for comparing the thematic accuracy of multi-use image based habitat maps in various coral reef and seagrass environments. A scientific assessment and an evaluation of the relevance for managers, was conducted on eight commonly used habitat mapping approaches for three different coral reef environments. This analysis revealed a preference for a mapping approach based on supervised classification of Quickbird imagery integrated with basic field data. This approach produced an accurate map within a short time with low cost in that suited the user’s purpose. Additionally, the results indicated that user preference in selecting a suitable map was affected by: variations in environmental complexity; map purpose, and resource management requirements. To assess the variation in performance of methods for calibration and validation for coral reef benthic community maps, derived from high-spatial resolution satellite images, a comparison was conducted between spot check and georeferenced photo-transect based mapping approaches. The assessment found that the transect based method was a robust procedure which could be used in a range of coral reef environments to map the benthic communities accurately. In contrast, the spot check method is a fast and low cost approach suitable to map benthic communities which have lower spatial complexity. However, the spot check approach provides robust results, if it is applied in a standardised manner, providing a description of selected homogenous areas with georeferenced benthic cover photos. Considerations for comparing the thematic accuracy of multi-use image based habitat maps in various coral reef and seagrass environments were assessed. This included a review of 80 scientific publications on coral reef and seagrass habitat mapping, which revealed a lack of knowledge and reporting in regards to the assessment of the thematic map accuracy. These publications commonly used thematic accuracy measures and factors controlling their variation were then determined for various habitat mapping approaches for different coral reefs and seagrass environments. Assessment of these measures found that variations in accuracy levels were not only a result of actual differences in map accuracy, but were also due to: spatial complexity of benthic features present in the study area; distribution of the calibration and validation samples relative to each other, and the level of detail provided by these samples. Two main outcomes resulted from this dissertation. The first was the development of a robust mapping approach based on georeferenced photo-transect method integrated with high spatial resolution imagery, which is able to accurately map a variety of coral reef and seagrass habitats. The second outcome is an increase in capacity for coral reef and seagrass habitat mapping by scientists and managers. This increase is accomplished by providing knowledge on various habitat mapping approaches in regards to their: cost/time, accuracy and user relevance; performance of calibration and validation field methods; and performance of accuracy measures, when applied in a range of coral reef and seagrass environments. The findings and outcomes from this dissertation will significantly contribute to management of coral reef and seagrass environments by enabling scientists and managers to choose appropriate combinations of: field and image data sources; processing approaches, and validation methods for habitat mapping in these environments.

Sony’s Support Application team wanted an experiment to be conducted by which they could determine if it was suitable to use Machine Learning to improve the quantity and quality of search results of the in-application search tool. By improving the quantity and quality of the results the team wanted to improve the customer’s journey. A supervised machine learning model was created to classify articles into four categories; Wi-Fi &amp; Connectivity, Apps &amp; Settings, System &amp; Performance, andBattery Power &amp; Charging. The same model was used to create a service that categorized the search terms into one of the four categories. The classified articles and the classified search terms were used to complement the existing search tool. The baseline for the experiment was the result of the search tool without classification. The results of the experiment show that the number of articles did indeed increase but due mainly to the broadness of the categories the search results held low quality.

Submitted by Jordan (jordanbiblio@gmail.com) on 2017-03-14T14:12:37Z No. of bitstreams: 1 DISS_2015_Cassia Rosin.pdf: 1981747 bytes, checksum: 255846d68f24309d20764dc0e60fdd9f (MD5) / Approved for entry into archive by Jordan (jordanbiblio@gmail.com) on 2017-03-14T16:03:05Z (GMT) No. of bitstreams: 1 DISS_2015_Cassia Rosin.pdf: 1981747 bytes, checksum: 255846d68f24309d20764dc0e60fdd9f (MD5) / Made available in DSpace on 2017-03-14T16:03:05Z (GMT). No. of bitstreams: 1 DISS_2015_Cassia Rosin.pdf: 1981747 bytes, checksum: 255846d68f24309d20764dc0e60fdd9f (MD5) Previous issue date: 2015-02-27 / CAPES / O Cerrado mato-grossense sofreu intensivo processo de desmatamento a partir dos anos 60, por iniciativas do Governo Federal aliado a interesses internacionais que visavam o desenvolvimento da agricultura nessa região. Estimativas atuais indicam a existência de um remanescente de apenas 55% de Cerrado, porém, a fronteira agrícola continua em expansão, comprometendo estas áreas que ainda se encontram preservadas. Grande parte dos resultados encontrados na literatura sobre os efeitos da remoção da vegetação são referentes a florestas tropicais e ainda para bacias hidrográficas inferiores a 1 km². Para a Floresta Amazônica, foram realizados diversos estudos sobre o desmatamento. No entanto, há carência de estudos sobre os efeitos da transformação do Cerrado em paisagem agropastoril. Portanto, o presente trabalho visa correlacionar a mudança da cobertura do solo com a variação temporal da precipitação e vazão na bacia do Rio das Mortes. Para avaliar possíveis alterações hidrológicas, foram utilizadas series de precipitação e vazão de médias, máximas e mínimas diárias mensais e anuais dos períodos seco e chuvoso, para as quais realizou-se a análise de tendência de Mann-Kendall. De posse das series diárias mensais dos dados pluviométricos e fluviométricos, foram preparadas as médias decadais consecutivas, as quais foram apresentadas em gráficos bloxplot e as médias entre os três períodos (1975 a 1984; 1985 a 1994; e 1995 a 2004) foram comparadas pelo teste t-student. Para avaliação da cobertura do solo foram utilizadas imagens de 12 orbitas-pontos do satélite Landsat 5 sensor TM, com intervalo decadal, no período de 1984, 1994 e 2004. As imagens foram pré-processadas e classificadas pelo algoritmo vizinho mais próximo. As análises de tendências de Mann-Kendall para as séries temporais pluviométricas foram pouco expressivas resultando em apenas 11% das séries com tendências significativas, sugerindo que sistema climatológico local depende muito pouco da evaporação da superfície da área. As análises de tendências de Mann-Kendall para as séries temporais fluviométricas apresentaram tendências tanto negativas como positivas. A estação cujas análises apresentaram em todas as séries tendência negativa, demonstra forte conexão em relação ao tipo de uso e sobre-exploração dos recursos hídricos. Já nas estações que apresentaram tendência de aumento, podemos notar que o tipo de uso e as caraterísticas físicas do solo influenciam a dinâmica hídrica na bacia. Analisando as áreas de vegetação nativa da Bacia do Rio das Mortes, verifica-se que houve uma redução das mesmas nos anos de 1984, 1994 e 2004, as quais correspondem, respectivamente, a 79%, 71% e 57% da área. Enquanto as classes que expressam uso antrópico em 1984 ocupavam 21% da bacia e em 2004 passaram a ocupar 43% da área da bacia do Rio das Mortes. A redução da vegetação nativa e aumento das classes de uso antrópico se deu de forma mais intensa na região do Alto Rio das Mortes, resultando em alteração da vazão que apresentou redução de fluxo em função da sobre-exploração. Porem a analise das estações pluviométricas evidencia grande variabilidade na precipitação, o que sugere que o sistema climatológico local possa ter maior dependência dos padrões de circulação atmosféricos que da evaporação da superfície da área. / The Mato Grosso Cerrado suffered intensive deforestation process from the 60s, by Federal Government initiatives combined with international interests aimed at the development of agriculture in this region. Current estimates indicate that there is a remnant of only 55% of Cerrado, however, the agricultural frontier continues to expand, committing these areas that are still preserved. Much of the results found in the literature on the effects of vegetation removal are for tropical forests and watersheds yet for less than 1 km². To the Amazon rainforest, were conducted several studies on deforestation. However, there are few studies on the effects of the transformation of the Cerrado in agropastoral landscape. Therefore, this study intends to correlate the change of land cover with the temporal variation of precipitation and flow in the Rio das Mortes. To evaluate possible hydrological changes were used series of precipitation and flow averages, monthly and annual daily maximum and minimum of dry and wet periods, for which there was the Mann-Kendall trend analysis. Having the monthly series of daily rainfall and runoff data were prepared averages consecutive decadal, which were presented in bloxplot graphics and the average of the three periods (1975-1984, 1985-1994, and 1995-2004) were compared by Student's t-test. For assessment of land cover were used images of 12-point orbits of Landsat 5 TM sensor, with decadal interval, from 1984, 1994 and 2004. The images were pre-processed and classified by the nearest neighbor algorithm. Analysis Mann-Kendall trends for rainfall was insignificant time series resulting in only 11% of the series with significant trends suggesting that the local climatological system depends very little evaporation of surface area. Analyses of Mann-Kendall trend for fluviometric time series presented both negative and positive trends. The station whose analyzes presented in all negative trend series shows strong connection with the type of use and over-exploitation of water resources. Already in the stations showed an increasing trend, we note that the type of use and the physical characteristics of the soil influence the water dynamics in the basin. Analyzing the areas of native vegetation of the Rio das Mortes Basin, it appears that there was a reduction of the same in 1984, 1994 and 2004, which correspond, respectively, to 79%, 71% and 57% of the area. While the classes expressing anthropic use in 1984 occupied 21% of the basin and in 2004 came to occupy 43% of the basin area of Rio das Mortes. The reduction of native vegetation and increased anthropogenic use classes occurred more intensely in the Upper Rio das Mortes region, resulting in change of flow that decreased flow due to the over-exploitation. However, analysis of rainfall stations shows great variability in the precipitation, which suggests that local climatological system can be increased reliance on air flow patterns that the evaporation surface area.

A urbanização é uma das ações antrópicas que mais crescem no mundo atual. Por este motivo pesquisas ecológicas são realizadas nas cidades com o objetivo de reconhecer seus impactos, e as aves são utilizadas como uma das ferramentas para diagnóstico ambiental. Assim, o presente estudo avaliou o método de levantamento de aves por ponto fixo, método amplamente utilizado em estudos com aves em diversos ambientes. Foram analisados três pontos que podem influenciar a amostragem de aves através deste método: 1) o habitat onde o levantamento é realizado, observando a composição dos elementos urbanos existentes na cidade; 2) o intervalo de tempo adotado em cada ponto fixo para a coleta de dados; 3) os fatores potencialmente prejudiciais a observação de aves, tais como o ruído sonoro urbano e a presença de conversas causadas por pessoas curiosas. Com a área de estudo estratificada a partir da quantidade de cobertura arbórea existente nos bairros abrangidos, 90 unidades amostrais foram selecionadas. Nestes, foram quantificados os elementos urbanos presentes, a riqueza, o número de contato de aves, os ruídos sonoros e a presença de conversas. Os resultados demonstraram que a reunião de um número maior de espécies e contatos pode ser favorecida pelas áreas de cobertura arbórea, enquanto áreas construídas e pisos impermeáveis podem prejudicar o número de espécies, sendo o número de contato prejudicado apenas pelas áreas de pisos impermeáveis. O número de espécies observadas não foi significativamente diferente após nove minutos de coleta de dados, entretanto o número de contatos continuou crescendo, demonstrando haver recontagens de indivíduos após este intervalo. A riqueza de espécies foi significativamente diferente entre os dados coletados no período seco e no período chuvoso. Conforme houve a maior presença do ruído sonoro urbano menor foi o número de espécies e contatos obtidos nos pontos. A incidência de conversas ocasionadas por pessoas curiosas foi baixa não prejudicando as coletas de dados. Os resultados encontrados sugerem que: o levantamento de aves no meio urbano através do ponto fixo deve considerar a composição do ambiente, já que a riqueza e o número de contato podem variar de acordo com a presença dos diferentes elementos; sejam adotados intervalos de tempo por ponto não superiores a nove minutos; quando possível diferentes épocas do ano devem ser utilizadas para as coletas de dados, visto que podem ser encontradas diferenças entre as estações; sejam escolhidos locais e momentos para as coletas de dados com baixo ruído sonoro. Por fim, o método de ponto fixo foi considerado eficaz para amostragem de aves urbanas, desde que tais cuidados sejam considerados. / The urbanization is one of the anthropic activities with the highest growth rate in the world. Due to this reason, ecological research are conducted in the cities with the goal of recognizing its impacts, using birds as one of the tools to assess the environmental diagnosis. Therefore, the present study assessed the samples by point counts method, which is broadly used for bird census in many environments. Three issues that might affect the sampling of the birds by using this method were analyzed: 1) the habitat where the sampling is performed, observing the urban elements presented in the city; 2) the period of point count duration spent in each sample; 3) the potential factors which disturb the birds detectability, as urban noise and presence of curious citizens who can talk to the researcher in the point count. The research area was stratified from the amount of tree canopies in the selected suburbs, where 90 sample units were selected. In these units, the presence of urban elements, the richness, the number of birds contacts, the noise and the presence of conversations were quantified. The results showed that the number of species and contacts can be benefited from the tree canopy area, while build up areas and impermeable grounds may harm the number of species, although the contact number is harmed only by the impermeable grounds. The number of observed species did not differ significantly after nine minutes of sample period, however the number of contacts kept increasing, demonstrating a repeated counting birds after this interval. The species richness was significantly different between the samples collected in dry and wet seasons. As the urban noise increased, a lower number of species and birds contacts was acknowledged. The incidence of conversation performed by curious people was low, not being able to harm the sample collection. The results suggest that: the bird survey inside the cities by point counts should consider the composition of environment, since the richness and the number of birds contacts can vary according to the presence of different elements; the time of interval should not exceed nine minutes; when possible, different annual seasons should be used for sampling, since differences may be found among them; places and moments for the sampling should be chosen with a low noise. Finally, the point counts method was considered efficient for the sampling of urban birds, provided that such care are considered.

Philosophiae Doctor - PhD / This thesis describes and introduces novel methods for knowledge discovery and presents a software system that is able to extract information from biomedical literature, review interesting connections between various biomedical concepts and in so doing, generates new hypotheses. The experimental results obtained by using methods described in this thesis, are compared to currently published results obtained by other methods and a number of case studies are described. This thesis shows how the technology, resented can be integrated with the researchers own knowledge, experimentation and observations for optimal progression of scientific research. / South Africa

La cartographie du couvert végétal est un outil essentiel au suivi et à la gestion et des milieux « naturels ». Des cartes caractérisant les essences forestières à l'échelle régionale sont nécessaires pour la gestion des milieux forestiers. Les séries temporelles d'images satellitaires optiques à moyenne résolution spatiale, peuvent permettre de satisfaire ce besoin. L'objectif de cette thèse est d'améliorer la classification supervisée d'une série temporelle afin de produire des cartes à l'échelle régionale détaillant la composition en essences de la végétation forestière. Nous avons d'abord évalué l'apport de la stratification du site d'étude pour améliorer les résultats de la classification d'une série temporelle d'images MODIS. Le recours à une stratification à partir d'une segmentation orientée objet améliore la classification supervisée, avec une augmentation de la valeur de Kappa et du taux de rejet des pixels à classer. Un seuil minimal et un seuil maximal de la surface de végétation à classer ont été identifiés, correspondant respectivement à un taux de rejet trop élevé et à une absence d'effet de la stratification. Nous avons ensuite évalué l'influence de l'organisation de la série temporelle d'images à moyenne résolution spatiale et du choix de l'algorithme de classification. Cette évaluation a été effectuée pour trois algorithmes (maximum de vraisemblance, Support Vector Machine, Random Forest) en faisant varier les caractéristiques de la série temporelle. On observe un effet de la temporalité et de la radiométrie sur la précision de la classification particulièrement significatif et la supériorité de l'algorithme Random Forest. Sur le plan thématique, des confusions subsistent et certains mélanges d'essences sont mal distingués. Nous avons alors cherché à évaluer l'apport du changement de résolution spatiale des images composant la série temporelle pour améliorer les résultats de classification. Les conclusions effectuées précédemment avec les données MODIS sont confortées, ce qui permet de conclure qu'elles sont indépendantes des données d'entrée et de leur résolution spatiale. Une amélioration significative est apportée par le changement de résolution spatiale, avec une augmentation de l'indice de Kappa de 0,60 à 0,72 obtenue grâce à la diminution de la proportion de pixels mixtes. Quelle que soit la résolution spatiale des images utilisées, les résultats obtenus montrent que la définition d'une procédure optimale améliore sensiblement les résultats de la classification. / Forest cover mapping is an essential tool for forest management. Detailed maps, characterizing forest types at a régional scale, are needed. This need can be fulfilled by médium spatial resolution optical satellite images time sériés. This thesis aims at improving the supervised classification procédure applied to a time sériés, to produce maps detailing forest types at a régional scale. To meet this goal, the improvement of the results obtained by the classification of a MODIS time sériés, performed with a stratification of the study area, was assessed. An improvement of classification accuracy due to stratification built by object-based image analysis was observed, with an increase of the Kappa index value and an increase of the reject fraction rate. These two phenomena are correlated to the classified végétation area. A minimal and a maximal value were identified, respectively related to a too high reject fraction rate and a neutral stratification impact.We carried out a second study, aiming at assessing the influence of the médium spatial resolution time sériés organization and of the algorithm on classification quality. Three distinct classification algorithms (maximum likelihood, Support Vector Machine, Random Forest) and several time sériés were studied. A significant improvement due to temporal and radiométrie effects and the superiority of Random Forest were highlighted by the results. Thematic confusions and low user's and producer's accuracies were still observed for several classes. We finally studied the improvement brought by a spatial resolution change for the images composing the time sériés to discriminate classes of mixed forest species. The conclusions of the former study (MODIS images) were confirmed with DEIMOS images. We can conclude that these effects are independent from input data and their spatial resolution. A significant improvement was also observed with an increase of the Kappa index value from 0,60 with MODIS data to 0,72 with DEIMOS data, due to a decrease of the mixed pixels rate.

Algoritmos de aprendizado semi-supervisionado ativo podem se configurar como ferramentas úteis em cenários práticos em que os dados são numerosamente obtidos, mas atribuir seus respectivos rótulos de classe se configura como uma tarefa custosa/difícil. A literatura em aprendizado ativo destaca diversos algoritmos, este trabalho partiu do tradicional Hierarchical Sampling estabelecido para operar sobre hierarquias de grupos. As características de tal algoritmo o coloca à frente de outros métodos ativos, entretanto o mesmo ainda apresenta algumas dificuldades. A fim de aprimorá-lo e contornar suas principais dificuldades, incluindo sua sensibilidade na escolha particular de uma hierarquia de grupos como entrada, este trabalho propôs estratégias que possibilitaram melhorar o algoritmo na sua forma original e diante de variantes propostas na literatura. Os experimentos em diferentes bases de dados reais mostraram que o algoritmo proposto neste trabalho é capaz de superar e competir em qualidade dentro do cenário de classificação ativa com outros algoritmos ativos da literatura. / Active semi-supervised learning can play an important role in classification scenarios in which labeled data are laborious and/or expensive to obtain, while unlabeled data are numerous and can be easily acquired. There are many active algorithms in the literature and this work focuses on an active semi-supervised algorithm that can be driven by clustering hierarchy, the well-known Hierarchical Sampling (HS) algorithm. This work takes as a starting point the original Hierarchical Sampling algorithm and perform changes in different aspects of the original algorithm in order to tackle its main drawbacks, including its sensitivity to the choice of a single particular hierarchy. Experimental results over many real datasets show that the proposed algorithm performs superior or competitive when compared to a number of state-of-the-art algorithms for active semi-supervised classification.

Nas últimas décadas, com o crescimento acelerado na geração e armazenamento de dados, houve um aumento na necessidade de criação e gerenciamento de grandes bases de dados. Logo, a utilização de técnicas de mineração de dados adequadas para descoberta de padrões e informações úteis em bases de dados é uma tarefa de interesse. Em especial, bases de séries temporais têm sido alvo de pesquisas em áreas como medicina, economia e agrometeorologia. Em mineração de dados, uma das tarefas mais exploradas é a classificação. Entretanto, é comum em bases de séries temporais, a quantidade e complexidade de dados extrapolarem a capacidade humana de análise manual dos dados, o que torna o processo de supervisão dos dados custoso. Como consequência disso, são produzidos poucos dados rotulados, em comparação a um grande volume de dados não rotulados disponíveis. Nesse cenário, uma abordagem adequada para análise desses dados é a classificação semissupervisionada, que considera dados rotulados e não rotulados para o treinamento do classificador. Nesse contexto, este trabalho de mestrado propõe 1) uma metodologia de análise de dados obtidos a partir de séries temporais de imagens de satélite (SITS) usando tarefas de mineração de dados e 2) uma técnica baseada em grafos para classificação semissupervisionada de séries temporais extraídas de imagens de satélite. A metodologia e a técnica de classificação desenvolvidas são aplicadas na análise de séries temporais de índices de vegetação obtidas a partir de SITS, visando a identificação de áreas de plantio de cana-de-açúcar. Os resultados obtidos em análise experimental, realizada com apoio de especialistas no domínio de aplicação, indicam que a metodologia proposta é adequada para auxiliar pesquisas em agricultura. Além disso, os resultados do estudo comparativo mostram que a técnica de classificação semissupervisionada desenvolvida supera métodos de classificação supervisionada consolidados na literatura e métodos correlatos de classificação semissupervisionada. / The amount of digital data generated and stored as well as the need of creation and management of large databases has increased significantly, in the last decades. The possibility of finding valid and potentially useful patterns and information in large databases has attracted the attention of many scientific areas. Time series databases have been explored using data mining methods in serveral domains of application, such as economics, medicine and agrometeorology. Due to the large volume and complexity of some time series databases, the process of labeling data for supervised tasks, such as classification, can be very expensive. To overcome the problem of scarcity of labeled data, semi-supervised classification, which benefits from both labeled and unlabeled data available, can be applied to classify data from large time series databases. In this Master dissertation, we propose 1) a framework for the analysis of data extracted from satellite image time series (SITS) using data mining tasks and 2) a graph-based semi-supervised classification method, developed to classify temporal data obtained from satellite images. According to experts in agrometeorology, the use of the proposed method and framework provides an automatic way of analyzing data extracted from SITS, which is very useful for supporting research in this domain of application. We apply the framework and the proposed semi-supervised classification method in the analysis of vegetation index time series, aiming at identifying sugarcane crop fields, in Brazil. Experimental results indicate that our proposed framework is useful for supporting researches in agriculture, according to experts in the domain of application. We also show that our method is more accurate than traditional supervised methods and related semi-supervised methods.

Lorsqu'un enseignant veut évaluer le savoir-faire des apprenants à l'aide d'un logiciel, il utilise souvent les systèmes Tutoriels Intelligents (STI). Or, les STI sont difficiles à développer et destinés à un domaine pédagogique très ciblé. Depuis plusieurs années, l'utilisation d'algorithmes de classification par apprentissage supervisé a été proposée pour évaluer le savoir des apprenants. Notre hypothèse est que ces mêmes algorithmes vont aussi nous permettre d'évaluer leur savoir-faire. Notre domaine d'application étant l'électronique numérique, nous proposons une mesure de similarité entre schémas électroniques et une bas d'apprentissage générée automatiquement. cette base d'apprentissage est composées de schémas électroniques pédagogiquement étiquetés "bons" ou "mauvais" avec des informations concernant le degré de simplification des erreurs commises. Finalement, l'utilisation d'un algorithme de classification simple (les k plus proches voisins) nous a permis de faire une évaluation des schémas électroniques dans la majorité des cas. / When a teacher wants to evaluate the know-how of the learners using a software, he often uses Intelligent Tutorial Systems (ITS). However, those systems are difficult to develop and intended for a very targeted educational domain. For several years, the used of supervised classification algorithms was proposed to estimate the learners' knowledge. From this fact, we assume that the same kinf of algorithms can help to adress the learners' know-how evaluation. Our application field being digital system design, we propose a similarity measure between digital circuits and instances issued from an automatically generated database. This database consists of electronic circuits pedagogically labelled "good" or "bad" with information concerning the simplification degrees or made mistakes. Finally, the use of a simple classification algorithm (namely k-nearest neighbours classifier) allowed us to achieve a circuit's evaluation in most cases.