[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Single-pass online learning

[ACM Press the 12th ACM SIGKDD internati

✍ Carvalho, Vitor R.; Cohen, William W. 📂 Article 📅 2006 🏛 ACM Press ⚖ 725 KB

To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such as perceptron or Winnow are naturally suited to stream processing; however, in practice multiple passes over the same trai

[ACM Press the 12th ACM SIGKDD internati

[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Evolutionary clustering

✍ Chakrabarti, Deepayan; Kumar, Ravi; Tomkins, Andrew 📂 Article 📅 2006 🏛 ACM Press ⚖ 815 KB

[ACM Press the 12th ACM SIGKDD internati

[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Topics over time

✍ Wang, Xuerui; McCallum, Andrew 📂 Article 📅 2006 🏛 ACM Press ⚖ 930 KB

[ACM Press the 12th ACM SIGKDD internati

[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Outlier detection by active learning

✍ Abe, Naoki; Zadrozny, Bianca; Langford, John 📂 Article 📅 2006 🏛 ACM Press ⚖ 134 KB

[ACM Press the 12th ACM SIGKDD internati

[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Outlier detection by active learning

✍ Abe, Naoki; Zadrozny, Bianca; Langford, John 📂 Article 📅 2006 🏛 ACM Press ⚖ 134 KB

Most existing approaches to outlier detection are based on density estimation methods. There are two notable issues with these methods: one is the lack of explanation for outlier flagging decisions, and the other is the relatively high computational requirement. In this paper, we present a novel app

[ACM Press the 12th ACM SIGKDD internati

[ACM Press the 12th ACM SIGKDD international conference - Philadelphia, PA, USA (2006.08.20-2006.08.23)] Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06 - Statistical entity-topic models

✍ Newman, David; Chemudugunta, Chaitanya; Smyth, Padhraic 📂 Article 📅 2006 🏛 ACM Press ⚖ 726 KB