Search results for "cluster analysis."

showing 5 items of 805 documents

Research literature clustering using diffusion maps

2013

We apply the knowledge discovery process to the mapping of current topics in a particular field of science. We are interested in how articles form clusters and what are the contents of the found clusters. A framework involving web scraping, keyword extraction, dimensionality reduction and clustering using the diffusion map algorithm is presented. We use publicly available information about articles in high-impact journals. The method should be of use to practitioners or scientists who want to overview recent research in a field of science. As a case study, we map the topics in data mining literature in the year 2011. peerReviewed

ta113kirjallisuuskatsausklusterointiComputer scienceProcess (engineering)Dimensionality reductiondiffuusiokuvausta111Diffusion mapKeyword extractionliterature mappingdiffusion mapKnowledge discovery processLibrary and Information Sciencescomputer.software_genreData scienceField (geography)Computer Science ApplicationsKnowledge extractionTiedonhavaitsemisprosessitiedonlouhintaCluster analysiscomputerWeb scrapingclustering
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Scalable implementation of dependence clustering in Apache Spark

2017

This article proposes a scalable version of the Dependence Clustering algorithm which belongs to the class of spectral clustering methods. The method is implemented in Apache Spark using GraphX API primitives. Moreover, a fast approximate diffusion procedure that enables algorithms of spectral clustering type in Spark environment is introduced. In addition, the proposed algorithm is benchmarked against Spectral clustering. Results of applying the method to real-life data allow concluding that the implementation scales well, yet demonstrating good performance for densely connected graphs. peerReviewed

ta113ta213Apache SparkComputer sciencedatasetsCorrelation clusteringdata miningcomputer.software_genrealgorithmsSpectral clusteringComputational sciencedependence clusteringData stream clusteringCURE data clustering algorithmScalabilitySpark (mathematics)algoritmitCanopy clustering algorithmData miningtiedonlouhintaCluster analysisclustering algorithmscomputerdata processingtietojenkäsittely
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Axiology of the historial city and the cap rate. The case of the old town of Ragusa Superiore

2017

Il contributo affronta il tema del ruolo che il mercato immobiliare assume nei processi di valorizzazione dei tessuti urbani storici nella logica dell’approccio al valor capitale. L’articolazione, eterogeneità e multi-contestualità del patrimonio immobiliare della città storica, la molteplicità delle relazioni tra valori e prezzo, la complessa dialettica fondo/flusso, l’eterogeneità dei profili dei soggetti economici che interagiscono nel mercato, danno vita ad un assortimento di approcci all’investimento immobiliare che in questo contributo, attraverso l’analisi del saggio di capitalizzazione si intendono rappresentare. La convergenza tra valori di contesto e potenzialità inespresse da una…

tessuti urbani storici mercato immobiliare teoria del capitale procedimento analitico saggio di capitalizzazioneSettore ICAR/22 - Estimohistorial urban fabrics real estate market theory of the capital income approach fuzzy cluster analysis capitalization rate
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Application of the Information Bottleneck method to discover user profiles in a Web store

2018

The paper deals with the problem of discovering groups of Web users with similar behavioral patterns on an e-commerce site. We introduce a novel approach to the unsupervised classification of user sessions, based on session attributes related to the user click-stream behavior, to gain insight into characteristics of various user profiles. The approach uses the agglomerative Information Bottleneck (IB) algorithm. Based on log data for a real online store, efficiency of the approach in terms of its ability to differentiate between buying and non-buying sessions was validated, indicating some possible practical applications of the our method. Experiments performed for a number of session sampl…

unsupervised classificationComputer science02 engineering and technologyE-commerceCustomer profile020204 information systems0202 electrical engineering electronic engineering information engineeringe-commerceWeb storeCluster analysisUser profileInformation retrievalbusiness.industrycustomer profileBehavioral patternInformation bottleneck methoddata miningComputer Science Applicationsmachine learningComputational Theory and MathematicsAgglomerative Information Bottleneck020201 artificial intelligence & image processinguser profilebusinessclusteringInformation SystemsJournal of Organizational Computing and Electronic Commerce
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Identifying the Sales Patterns of Online Stores with Time Series Clustering

2018

Electronic commerce, especially in the business-to-consumer (B2C) context, has for years been a popular research topic in information systems (IS). However, the prior research on the topic has traditionally been dominated by the consumer focus instead of the business focus of online stores. For example, whereas various segmentations exist for online consumers based on their purchase behaviour, no such segmentations have been developed for online stores based on their sales patterns. In this study, our objective is to address this gap in prior research by identifying the most typical sales patterns of online stores operating in the B2C context. By using self-organising maps (SOM) to analyse …

verkkokauppa (verkkoliiketoiminta)Series (mathematics)Computer scienceverkkokauppabusiness-to-consumercomputer.software_genreB2Conline storesklusteritsegmentointisales patternsSegmentationData miningCluster analysiscomputertime series clustering
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