关键词: 对象共指消解, MapReduce, 语义Web

Abstract: Object coreference resolution is a hotspot topic in the research area of the semantic Web. Although there are many novel approaches for resolving object coreference, their efficiency is still far away from practical use. At present, the MapReduce framework is widely used for processing data because of its simplicity and higher computational capability with lower cost. This paper proposes two parallel algorithms in terms of different phases of Map-
Reduce to resolve object coreference in the semantic Web. Specifically, given a labeled training set and a threshold, the algorithms can efficiently find the most discriminative properties whose confidences are no less than the predefined threshold. These discriminative properties are used to identify object coreference holding similar values. The paper reports the results from experiments on real datasets, by increasing the dataset size, to evaluate the speed-up and scale-up properties of the proposed algorithms using MapReduce.

Key words: object coreference resolution, MapReduce, semantic Web