Uncertain Data
Clustering Multi Attribute Uncertain Data using Probability Distribution
... DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density-based clustering algorithm. Density-based clustering methods have been developed to discover clusters with arbitrary shape. These ...
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A Review Paper on Frequent Pattern Mining with Uncertain Data
... of uncertain data.[6] Specifically, the algorithm scans an uncertain database to find all distinct frequent items ...the uncertain database a second time to insert each database transaction into ...
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Overview of Important Algorithms to mine Frequent Patterns from Uncertain Data
... in data is caused by factors like data randomness, data incompleteness, ...big data has brought tools for the problem of frequent pattern mining of uncertain ...
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Uncertain Data Mining using Decision Tree and Bagging Technique
... important data mining techniques and Decision Tree is a most common structure for classification which is used in many ...known data. Traditional classifier extended to handle uncertain data ...
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Threshold interval indexing techniques for complicated uncertain data
... Uncertain data is an increasingly prevalent topic in database research, given the advance of in- struments which inherently generate uncertainty in their ...indexing uncertain data for range ...
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A survey paper on Frame work for classification of uncertain data
... because uncertain data fields’ attributes have no longer confident ...on uncertain data NFCC is less time consuming as it directly mines the patterns the time consumed in pattern mining and ...
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Credal classification of uncertain data using belief functions
... should have the same (as much as possible similar) distances to each involved specific class center taking into account the data dispersion. In CCR, the specific class contains the objects very close to the center ...
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Performance Analysis on Uncertain Data using Decision Tree
... physical data generation and collection process, measurement and decision ...of uncertain data in sensor networks, such as temperature, humidity, and ...[5]Since data uncertainty is important ...
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Cost-sensitive Naïve Bayes Classification of Uncertain Data
... Abstract—Data uncertainty is widespread in real-word applications. It has captured a lot of attention, but little job has been paid to the research of cost sensitive algorithm on uncertain data. The ...
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Developing Decision Trees for Handling Uncertain Data
... used data mining ...dimensional data, and their representation is intuitive and generally easy to assimilate by ...the data whose values are ...the data collection process. Example sources of ...
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Crowdsourcing For Top-K Query Processing Over Uncertain Data Base Paper
... over uncertain data, and in particular its complexity and existing techniques, highly depend on data ...succinct data representations ...database). Data objects are usually evaluated by ...
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Uncertain<T>: A First-Order Type for Uncertain Data
... This case study emulates a binary sensor with Gaussian noise to explore accuracy when ground truth is available. For many problems using uncertain data, ground truth is difficult and costly to obtain, but ...
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Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
... Outline: The paper is organised as follows: Section 2 introduces the problem of classification with uncertain data. In section 3 we make use of Chebyshev inequalities for multivariate random variable to ...
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Querying Uncertain Data in XML
... support uncertain attribute values ProTDB converts all attribute values to regular ...which data uncertainty and lineage are first-class citizens, introduced by Widom et ...the uncertain data, ...
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Reducing the Search Space for Interesting Patterns from Uncertain Data
... which data are ...of uncertain data are usually associated with existential probabilities expressing the likelihood of these items to be present in the transaction, the search space for mining from ...
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Managing continuous uncertain data by a probabilistic XML database management system
... Another aspect of query optimization is the following. As described in chapter 5 the im- plementation of all the query operators process continuous uncertain data that has been dis- cretized. This approach ...
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Interval network data envelopment analysis model for classification of investment companies in the presence of uncertain data
... network data envelopment analysis (INDEA) model for classification and ranking of investment companies (ICs) by considering internal structure and ...the uncertain data only known to lie within the ...
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A Survey of Uncertain Data Handling
... designed uncertain databases around specific application ...unclean data under possible world’s ...dynamic data cleaning in such a way that clean and consistent answers may be obtained for ...for ...
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Query Selectivity Estimation for Uncertain Data
... Efficient algorithms for selectivity estimation of probabilistic threshold queries over uncertain data... Selectivity estimation for traditional relational.[r] ...
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Sequential pattern mining with uncertain data
... incorporate uncertain information in traditional data mining ...of uncertain sequential pattern mining strongly de- pends on both the domain and the ...scale uncertain databases, which make ...
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