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I subscribe to Springer Lecture Notes in Computer Science (LNCS) alerts. Several times now, I have received alerts when there was no web content at the URLs that they sent me. Very annoying, wasting my time. Please, this is 2009: try and make things work! . The latest was yesterday: at Mon, 20 Jul 2009 14:53:35 -0700 (PDT) I got an alert email from Springer LNCS: Dear Glen Newton, We are pleased to deliver your requested table of contents alert for a new volume of "Lecture Notes in Computer Science", subseries: "Lecture Notes in Artificial Intelligence". Volume 5632: Machine Learning and Data Mining in Pattern Recognition by Petra Perner is now available on the SpringerLink web site at http://springer.r.delivery.net/r/r?2.1.Ee.2Tp.1gRdiL.ByTshW..N.I9y2.3DBm.bW89MQ%5f%5fDJNcFRf0 Going to this page (as of Tues 14:26 ET July 21 2009, ~24hrs later), or to any of the URLs for the articles (including DOIs, like http://dx.doi.org/10.1007/978-3-642-03070-3_5 ) gives me - ...

Uncertainty Reasoning for the Semantic Web I, ISWC International Workshops, URSW 2005-2007, Revised Selected and Invited Papers. DOI http://dx.doi.org/10.1007/978-3-540-89765-1 , Lecture Notes in Computer Science . Of note: Towards Machine Learning on the Semantic Web. http://dx.doi.org/10.1007/978-3-540-89765-1_17 Author copy: http://www.cs.ubc.ca/spider/poole/papers/SemSciChapter2008.pdf Semantic Science: Ontologies, Data and Probabilistic Theories. http://dx.doi.org/10.1007/978-3-540-89765-1_2 Analogical Reasoning in Description Logics . http://dx.doi.org/10.1007/978-3-540-89765-1_19 Table of Contents: Fernando Bobillo, Miguel Delgado, Juan Gómez-Romero. 2008. A Crisp Representation for Fuzzy with Fuzzy Nominals and General Concept Inclusions. http://dx.doi.org/10.1007/978-3-540-89765-1_11 Mauro Mazzieri, Aldo Franco Dragoni. 2008. A Fuzzy Semantics for the Resource Description Framework . http://dx.doi.org/10.1007/978-3-540-89765-1_15 Matthias Nickles, Ruth Cobos. 2008. An Approa...

In the October 2008 special issue on inductive logic programming in Machine Learning , Dietterich et al [ 1 ] lay-out the following ten outstanding problems for the next ten years: Statistical predicate invention Generalizing across domains Learning many levels of structure Deep combination of learning and inference Learning to map between representations Learning in the large Structured prediction with intractable inference Reinforcement learning with structured time Expanding SRL (Statistical Relational Learning) to statistical relational AI Learning to debug programs [ 1 ] Thomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli (2008). Structured machine learning: the next ten years Machine Learning, 73 (1), 3-23 DOI: 10.1007/s10994-008-5079-1