Abstract
The proliferation of online digital libraries offers users a great opportunity to search their desired literatures on Web. Cross-library search applications can help users search more literature information from multiple digital libraries. Duplicate literatures detection is always a necessary step when merging the search results from multiple digital libraries due to heterogeneity and autonomy of digital libraries. To this end, this paper proposes a holistic solution which includes achieving automatic training set, holistic attribute mapping, and weight of attribute training. The experiments on real digital libraries show that the proposed solution is highly effective.
© 2016 Wei Liu, Jianxun Zeng, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
