The First International Conference on Knowledge Discovery and Data Mining
Sponsored by the Association for the Advancement of Artificial Intelligence
The First International Conference on Knowledge Discovery and Data Mining (KDD-95) was held August 20–21, 1995, Montreal, Quebec, Canada
Knowledge Discovery in Databases (KDD) and Data Mining are areas of common interest to researchers in machine learning, machine discovery, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The rapid growth of data and information created a need and an opportunity for extracting knowledge from databases, and both researchers and application developers have been responding to that need. KDD applications have been developed for astronomy, biology, finance, insurance, marketing, medicine, and many other fields. Core problems in KDD include representation issues, search complexity, the use of prior knowledge, statistical inference, and algorithms for the analysis of massive amounts of data both in size and dimensionality.
Due to strong demand for participation and the growing demand for formal proceedings, it has become necessary to change the format of the previous KDD workshops to a conference with open attendance. This conference will continue in the tradition of the 1989, 1991, 1993, and 1994 KDD workshops by bringing together researchers and application developers from different areas, and focusing on unifying themes such as the use of domain knowledge, managing uncertainty, interactive (human-oriented) presentation, and applications.
For further information about the KDD 1995 Conference, consult the following: