Department of Information and Computer Science, Aalto University, Helsinki, Finland
Mika Klemettinen, Heikki Mannila, Pirjo Ronkainen, Hannu Toivonen, A. Inkeri Verkamo
Proceedings of the Third International Conference on Information and Knowledge Management (CIKM'94), 1994 – CIKM
Association rules, introduced by Agrawal, Imielinski, and Swami, are rules of the form “for 90% of the rows of the relation, if the row has value 1 in the columns in set W, then it has 1 also in column B”. Efficient methods exist for discovering ...
Heikki Mannila, Hannu Toivonen, A. Inkeri Verkamo
KDD Workshop 1994: Seattle, 1994 – KDD
Association rules are statements of the form "for 90 % of the rows of the relation, if the row has value 1 in the columns in set W , then it has 1 also in column B". Agrawal, Imielinski, and Swami introduced the problem of mining ...
Heikki Mannila, Hannu Toivonen, A. Inkeri Verkamo
Proceedings of the 1st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1995 – KDD
Sequences of events describing the behavior and actions of users or systems can be collected in several domains. In this paper we consider the problem of recognizing frequent episodes in such sequences of events. An episode is defined to be a ...
Heikki Mannila, Kari-Jouko Räihä
VLDB'87, Proceedings of 13th International Conference on Very Large Data Bases, 1987 – VLDB
Thomas Eiter, Georg Gottlob, Heikki Mannila
ACM Transactions on Database Systems, vol. 22,no. 3,1997 – TODS
We consider disjunctive Datalog, a powerful database query language based on disjunctive logic programming. Briefly, disjunctive Datalog is a variant of Datalog where disjunctions may appear in the rule heads; advanced versions also allow for ...
Tomasz Imielinski, Heikki Mannila
Communications of the ACM, vol. 39,no. 11,1996 – CACM
Discovery The concept of data mining as a querying process and the first steps toward efficient development of knowledge discovery applications are discussed. DATABASE MINING IS NOT SIMPLY ANOTHER buzzword for statistical data analysis or inductive ...
Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant, Hannu Toivonen, A. Inkeri Verkamo
Advances in Knowledge Discovery and Data Mining , AAAI/MIT Press, 1996
Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2001 – KDD
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however, empirical results are sparse. We present experimental results on using ...
Heikki Mannila, Hannu Toivonen, A. Inkeri Verkamo
Data Mining and Knowledge Discovery, vol. 1,no. 3,1997 – DATAMINE
Sequences of events describing the behavior and actions of users or systems can be collected in several domains. An episode is a collection of events that occur relatively close to each other in a given partial order. We consider the problem of ...
Dimitrios Gunopulos, Heikki Mannila, Roni Khardon, Hannu Toivonen
Sixteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1997 – PODS
Several data mining problems can be formulated as problems of finding maximally specific sentences that are interesting in a database. We first show that this problem has a close relationship with the hypergraph transversal problem. We then analyze ...