[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 5291 || Clustering Uncertain Data Via K-Medoids

[Lecture Notes in Computer Science] Scal

[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 6379 || Uncertainty in Clustering and Classification

✍ Deshpande, Amol; Hunter, Anthony 📂 Article 📅 2010 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 87 KB

Managing uncertainty and inconsistency has been extensively explored in - ti?cial Intelligence over a number of years. Now with the advent of massive amounts of data and knowledge from distributed heterogeneous,and potentially con?icting, sources, there is interest in developing and applying formali

[Lecture Notes in Computer Science] Adva

[Lecture Notes in Computer Science] Advanced Data Mining and Applications Volume 6440 || Kernel Based K-Medoids for Clustering Data with Uncertainty

✍ Cao, Longbing; Feng, Yong; Zhong, Jiang 📂 Article 📅 2010 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 203 KB

With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fash

[Lecture Notes in Computer Science] Scal

[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 7520 || Density-Based Projected Clustering of Data Streams

✍ Hüllermeier, Eyke; Link, Sebastian; Fober, Thomas; Seeger, Bernhard 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg ⚖ 437 KB

[Lecture Notes in Computer Science] Scal

[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 6379 || Uncertainty in Decision Tree Classifiers

✍ Deshpande, Amol; Hunter, Anthony 📂 Article 📅 2010 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 320 KB

Managing uncertainty and inconsistency has been extensively explored in - ti?cial Intelligence over a number of years. Now with the advent of massive amounts of data and knowledge from distributed heterogeneous,and potentially con?icting, sources, there is interest in developing and applying formali

[Lecture Notes in Computer Science] Scal

[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 6379 || DK-BKM: Decremental K Belief K-Modes Method

✍ Deshpande, Amol; Hunter, Anthony 📂 Article 📅 2010 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 233 KB

Managing uncertainty and inconsistency has been extensively explored in - ti?cial Intelligence over a number of years. Now with the advent of massive amounts of data and knowledge from distributed heterogeneous,and potentially con?icting, sources, there is interest in developing and applying formali

[Lecture Notes in Computer Science] Scal

[Lecture Notes in Computer Science] Scalable Uncertainty Management Volume 5291 || Performance Evaluation of Algorithms for Soft Evidential Update in Bayesian Networks: First Results

✍ Greco, Sergio; Lukasiewicz, Thomas 📂 Article 📅 2008 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 401 KB

This Book Constitutes The Refereed Proceedings Of The Second International Conference On Scalable Uncertainty Management, Sum 2008, Held In Naples, Italy, In Oktober 2008. The 27 Revised Full Papers Presented Together With The Extended Abstracts Of 3 Invited Talks/tutorials Were Carefully Reviewed A