Fragments of order

High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a natural total or partial order underlying the variables of the data set. Examples of variables for which such orders exist include terms in documents, courses in enrollment data, and paleontological sites in fossil data collections. The observations in such applications are flat, unordered sets; however, the data sets respect the underlying ordering of the variables. By this we mean that if A B C are three variables respecting the underlying ordering , and both of variables A and C appear in an observation, then, up to noise levels, variable B also appears in this observation. Similarly, if A1 A2 ? ? ? Al-1 Al is a longer sequence of variables, we do not expect to see many observations for which there are indices i < j < k such that Ai and Ak occur in the observation but Aj does not. In this paper we stu...

• Type: Conference
• Year: 2003
• Where: KDD
• Authors: Aristides Gionis, Teija Kujala, Heikki Mannila
• Keywords: Data Mining, Data Sets Respect, Fossil Data Collections, KDD 2003, Real Data Sets