Web Mining: Pattern Discovery from World Wide Web Transactions

Oil fence especially adapted for the defining of impurities on a water surface and made of a web of cloth shaped material. The web exhibits alternating connected portions and multiple layer portions made in such a manner that between the layers of the multiple layer portions pockets and/or channels are formed, which are defined by the single layer portions, in order to receive for one thing float bodies for the support of the oil fence in water, and for another thing sinking weights in order to give the oil fence the intended upright position in the water. The present cloth shaped web comprises a preferably impregnated and/or coated textile material, which is woven with alternating single layer portions forming said connected portions and portions with at least two layers, between which said pockets and/or channels are formed. The single layer portions are by means of a per se known weaving technique shaped from the interwoven weft of the converging layers of the adjacent multiple layer portions, thereby obtaining an extremely strong connection of said portions.

[1]  Jennifer Widom,et al.  Querying Semistructured Heterogeneous Information , 1995, J. Syst. Integr..

[2]  Ramakrishnan Srikant,et al.  Mining Sequential Patterns: Generalizations and Performance Improvements , 1996, EDBT.

[3]  R. Ng,et al.  Eecient and Eeective Clustering Methods for Spatial Data Mining , 1994 .

[4]  Jaideep Srivastava,et al.  Myriad: Design and implementation of a federated database prototype , 1995, Softw. Pract. Exp..

[5]  Shamkant B. Navathe,et al.  An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.

[6]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[7]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[8]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[9]  Philip S. Yu,et al.  Data mining for path traversal patterns in a web environment , 1996, Proceedings of 16th International Conference on Distributed Computing Systems.

[10]  Usama M. Fayyad,et al.  Knowledge Discovery in Databases: An Overview , 1997, ILP.

[11]  Jiawei Han,et al.  Resource and Knowledge Discovery in Global Information Systems: A Preliminary Design and Experiment , 1995, KDD.

[12]  Heikki Mannila,et al.  Discovering Frequent Episodes in Sequences , 1995, KDD.

[13]  Dan Suciu,et al.  A query language and optimization techniques for unstructured data , 1996, SIGMOD '96.

[14]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[15]  Ramakrishnan Srikant,et al.  Mining generalized association rules , 1995, Future Gener. Comput. Syst..

[16]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[17]  Philip K. Chan,et al.  Systems for Knowledge Discovery in Databases , 1993, IEEE Trans. Knowl. Data Eng..

[18]  Jiawei Han,et al.  Data-Driven Discovery of Quantitative Rules in Relational Databases , 1993, IEEE Trans. Knowl. Data Eng..

[19]  Jorma Rissanen,et al.  SLIQ: A Fast Scalable Classifier for Data Mining , 1996, EDBT.

[20]  Arun N. Swami,et al.  Set-oriented mining for association rules in relational databases , 1995, Proceedings of the Eleventh International Conference on Data Engineering.