Abstract
Statistical relational learning constructs statistical mod- els from relational databases, combining the powers of re- lational learning and statistical learning. Its strong abil- ity and special property make statistical relational learn- ing become one of the important areas in machine learn- ing. In this paper, the general concepts and characteris- tics of statistical relational learning are presented firstly. Then some major branches of this newly emerging field are discussed, including logic and rule-based approaches, frame and object-oriented approaches, and several other important approaches. After that some methods of apply- ing rough set in statistical relational learning are described, such as gRS-ILP and VPRSILP. Finally applications of sta- tistical relational learning are briefly introduced and some future directions of statistical relational learning and the prospects of rough set in this area are pointed out.
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