Search results for "Processing"

showing 10 items of 8572 documents

Implementing structured document production to support enterprise content management

2017

Within enterprise content management (ECM), the major goal is to develop and deploy systematic solutions for managing documents and other content items. ECM implementation concerns the development and deployment of new content management solutions and practices in an organization. Extensible Markup Language (XML) offers a standardized format for documents supporting the management and preservation of documents as structured documents. However, the deployment of XML may require a demanding standardization process, changes in work practices, and new tools for document management. Consequently, this research explores the implementation of structured document production environments. The focus …

sähköiset asiakirjatECMenterprise content managementmetadataComputingMethodologies_DOCUMENTANDTEXTPROCESSINGtiedonhallintasisällönhallintatiedonhallintajärjestelmätXMLstructured documentsrakenteiset dokumentitasiakirjahallinto
researchProduct

Model selection using limiting distributions of second-order blind source separation algorithms

2015

Signals, recorded over time, are often observed as mixtures of multiple source signals. To extract relevant information from such measurements one needs to determine the mixing coefficients. In case of weakly stationary time series with uncorrelated source signals, this separation can be achieved by jointly diagonalizing sample autocovariances at different lags, and several algorithms address this task. Often the mixing estimates contain close-to-zero entries and one wants to decide whether the corresponding source signals have a relevant impact on the observations or not. To address this question of model selection we consider the recently published second-order blind identification proced…

ta112Series (mathematics)Estimation theoryModel selectionasymptotic normalitypattern identificationAsymptotic distributionInformation Criteriaoint diagonalization SOBI AsympBlind signal separationMatrix (mathematics)Control and Systems EngineeringSOBISignal Processingjoint diagonalizationComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringAlgorithmSoftwareMixing (physics)MathematicsSignal Processing
researchProduct

Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system

2017

We tackle three different challenges in solving a real-world industrial problem: formulating the optimization problem, connecting different simulation tools and dealing with computationally expensive objective functions. The problem to be optimized is an air intake ventilation system of a tractor and consists of three computationally expensive objective functions. We describe the modeling of the system and its numerical evaluation with a commercial software. To obtain solutions in few function evaluations, a recently proposed surrogate-assisted evolutionary algorithm K-RVEA is applied. The diameters of four different outlets of the ventilation system are considered as decision variables. Fr…

ta1130209 industrial biotechnologyMathematical optimizationnumerical modelsOptimization problemlineaarinen optimointiLinear programmingComputer sciencesoftwarehydraulijärjestelmätventilationEvolutionary algorithmlinear programming02 engineering and technologyFunction (mathematics)Set (abstract data type)resistance020901 industrial engineering & automationhydraulic systemsilmanvaihto0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingShape optimizationoptimization
researchProduct

Anomaly detection approach to keystroke dynamics based user authentication

2017

Keystroke dynamics is one of the authentication mechanisms which uses natural typing pattern of a user for identification. In this work, we introduced Dependence Clustering based approach to user authentication using keystroke dynamics. In addition, we applied a k-NN-based approach that demonstrated strong results. Most of the existing approaches use only genuine users data for training and validation. We designed a cross validation procedure with artificially generated impostor samples that improves the learning process yet allows fair comparison to previous works. We evaluated the methods using the CMU keystroke dynamics benchmark dataset. Both proposed approaches outperformed the previou…

ta113AuthenticationpääsynvalvontaComputer scienceaccess control02 engineering and technologycomputer.software_genreKeystroke dynamicstodentaminen020204 information systems0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Unsupervised learningauthentication020201 artificial intelligence & image processingAnomaly detectionData miningtietoturvadata securitycomputer
researchProduct

DOBRO : a prediction error correcting robot under drifts

2016

We propose DOBRO, a light online learning module, which is equipped with a smart correction policy helping making decision to correct or not the given prediction depending on how likely the correction will lead to a better prediction performance. DOBRO is a standalone module requiring nothing more than a time series of prediction errors and it is flexible to be integrated into any black-box model to improve its performance under drifts. We performed evaluation in a real-world application with bus arrival time prediction problem. The obtained results show that DOBRO improved prediction performance significantly meanwhile it did not hurt the accuracy when drift does not happen.

ta113Concept driftComputer scienceMean squared prediction error02 engineering and technologyARIMAconcept drifton-line prediction error correction020204 information systems0202 electrical engineering electronic engineering information engineeringRobot020201 artificial intelligence & image processingAutoregressive integrated moving averageSimulation
researchProduct

Gear classification and fault detection using a diffusion map framework

2015

This article proposes a system health monitoring approach that detects abnormal behavior of machines. Diffusion map is used to reduce the dimensionality of training data, which facilitates the classification of newly arriving measurements. The new measurements are handled with Nyström extension. The method is trained and tested with real gear monitoring data from several windmill parks. A machine health index is proposed, showing that data recordings can be classified as working or failing using dimensionality reduction and warning levels in the low dimensional space. The proposed approach can be used with any system that produces high-dimensional measurement data. peerReviewed

ta113Diffusion (acoustics)Training setta214Computer scienceDimensionality reductiondiffusion mapExtension (predicate logic)computer.software_genreFault detection and isolationfault detectionsystem health monitoringArtificial IntelligenceSignal ProcessingComputer Vision and Pattern RecognitionData miningCluster analysiscomputerSoftwareCurse of dimensionalityclustering
researchProduct

Interface Detection Using a Quenched-Noise Version of the Edwards-Wilkinson Equation

2015

We report here a multipurpose dynamic-interface-based segmentation tool, suitable for segmenting planar, cylindrical, and spherical surfaces in 3D. The method is fast enough to be used conveniently even for large images. Its implementation is straightforward and can be easily realized in many environments. Its memory consumption is low, and the set of parameters is small and easy to understand. The method is based on the Edwards-Wilkinson equation, which is traditionally used to model the equilibrium fluctuations of a propagating interface under the influence of temporally and spatially varying noise. We report here an adaptation of this equation into multidimensional image segmentation, an…

ta113Image segmentationta114DiscretizationInterface (Java)Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONobject detectionimage edge detectionImage segmentationComputer Graphics and Computer-Aided DesignGrayscaleGray-scaleObject detectionSurface topographyNoiseMathematical modelThree-dimensional displaysSegmentationTomography3D image processingNoiseSurface morphologyAlgorithmSoftwareIEEE Transactions on Image Processing
researchProduct

Investigating serendipity in recommender systems based on real user feedback

2018

Over the past several years, research in recommender systems has emphasized the importance of serendipity, but there is still no consensus on the definition of this concept and whether serendipitous items should be recommended is still not a well-addressed question. According to the most common definition, serendipity consists of three components: relevance, novelty and unexpectedness, where each component has multiple variations. In this paper, we looked at eight different definitions of serendipity and asked users how they perceived them in the context of movie recommendations. We surveyed 475 users of the movie recommender system, MovieLens regarding 2146 movies in total and compared tho…

ta113Information retrievalComputer scienceSerendipityuutuudetpalautesuosittelujärjestelmätNoveltyserendipityContext (language use)02 engineering and technologyVariation (game tree)Recommender systemunexpectednessPreferenceMovieLenssattumanovelty020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingRelevance (information retrieval)relevancerecommender systemsProceedings of the 33rd Annual ACM Symposium on Applied Computing
researchProduct

Cross-Domain Recommendations with Overlapping Items

2016

In recent years, there has been an increasing interest in cross-domain recommender systems. However, most existing works focus on the situation when only users or users and items overlap in different domains. In this paper, we investigate whether the source domain can boost the recommendation performance in the target domain when only items overlap. Due to the lack of publicly available datasets, we collect a dataset from two domains related to music, involving both the users’ rating scores and the description of the items. We then conduct experiments using collaborative filtering and content-based filtering approaches for validation purpose. According to our experimental results, the sourc…

ta113Information retrievaldata collectionComputer sciencesuosittelujärjestelmät02 engineering and technologyDomain (software engineering)020204 information systemscollaborative filtering0202 electrical engineering electronic engineering information engineeringcross-domain recommendationscontent-based filtering020201 artificial intelligence & image processingrecommender systems
researchProduct

User session level diverse reranking of search results

2018

Most Web search diversity approaches can be categorized as Document Level Diversification (DocLD), Topic Level Diversification (TopicLD) or Term Level Diversification (TermLD). DocLD selects the relevant documents with minimal content overlap to each other. It does not take the coverage of query subtopics into account. TopicLD solves this by modeling query subtopics explicitly. However, the automatic mining of query subtopics is difficult. TermLD tries to cover as many query topic terms as possible, which reduces the task of finding a query's subtopics into finding a set of representative topic terms. In this paper, we propose a novel User Session Level Diversification (UserLD) approach bas…

ta113InternetInformation retrievalWeb search queryuser sessionComputer scienceCognitive NeuroscienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVAL02 engineering and technologyGraphComputer Science Applicationssearch result rerankingQuery expansionsession graphArtificial IntelligenceWeb query classification020204 information systems0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)020201 artificial intelligence & image processingtiedonhakuhakutuloksetsearch result diversification
researchProduct