2-Stage Data Conflict Resolution Based on Markov Logic Networks

In data integration,how to resolve the data conflicts accurately is a key issue that is closely related to the quality of integrated data.Current methods only consider single attribute,neither conflict degree nor mutual influence of different attributes are considered in data conflict resolution.It causes their accuracy not to be high.For the shortcomings of existing methods,a 2-stage approach for resolving data conflict based on Markov Logic Networks is proposed.This approach can divide different attributes according to their conflict degree and carry on 2-stage data conflict resolution:(1) In the first stage,the attributes which conflict degree is low can be resolved by simple rules such as voting and mutual verification of facts;(2) In the second stage,with the aid of the results from the first stage,the attributes which conflict degree is high can be resolve via adding some more complex rules such as mutual influence between sources and facts,inter-dependency of sources and low conflict degree attributes to high conflict degree attributes influence.Experimental results using a large number of real-world data show that the proposed approach can resolve the integrated data conflict effectively,which is more accurate.