Improving the Efficiency of Term Weighting in Set of Dynamic Documents

In real information systems, there are few static documents. On the other hand, there are too many documents that their content change during the time that could be considered as signals to improve the quality of information retrieval. Unfortunately, considering all these changes could be time-consuming. In this paper, a method has been proposed that the time of analyzing these changes could be reduced significantly. The main idea of this method is choosing a special part of changes that do not make effective changes in the quality of information retrieval; but it could be possible to reduce the analyzing time. To evaluate the proposed method, three different datasets selected from Wikipedia. Different factors have been assessed in term weighting and the effect of the proposed method investigated on these factors. The results of empirical experiments showed that the proposed method could keep the quality of retrieved information in an acceptable rate and reduce the documents‘ analysis time as a result.