Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge. Information retrieval (IR) is concerned with gathering relevant information from unstructured and semantically fuzzy data in texts and other media, searching for information within documents and for metadata about documents, as well as searching relational databases and the Web. Automation of information retrieval enables the reduction of what has been called "information overload". Information retrieval can be combined with knowledge discovery to create software tools that empower users of decision support systems to better understand and use the knowledge underlying large data sets.
TOPICSBioInformatics & Pattern DiscoveryFoundations of Knowledge Discovery in DatabasesInformation ExtractionInteractive and Online Data MiningMachine LearningMining Multimedia DataMining Text and Semi-structured DataPre-processing and Post-processing for Data MiningProcess MiningSoftware DevelopmentStructured Data Analysis and Statistical MethodsBusiness Intelligence ApplicationsUser Profiling and Recommender SystemsVisual Data Mining and Data VisualizationWeb MiningClustering and Classification MethodsCollaborative FilteringConcept MiningContext DiscoveryData AnalyticsData Mining in Electronic CommerceData Reduction and Quality Assessment
09月18日
2018
09月20日
2018
注册截止日期
2017年11月01日 葡萄牙 Funchal,Portugal
第九届知识管理与信息共享国际会议2016年11月09日 葡萄牙 Porto,Portugal
第8届知识管理与信息共享国际会议2015年11月12日 葡萄牙
第七届知识管理与信息共享国际会议
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