Abstract
With the tremendous increasing of information, the demands of information from people advanced the development of Nature Language Processing (NLP). As a consequent, Sentence compression, which is an important part of automatic summarization, draws much more attention. Sentence compression has been widely used in automatic title generation, Searching Engine, Topic detection and Summarization. Under the framework of discriminative model, this paper presents a decoding method based on Integer Linear Programming (ILP), which considers sentence compression as the selection of the optimal compressed target sentence. Experiment results show that the ILP-based system maintains a good compression ratio while remaining the main information of source sentence. Compared to other decoding method, this method has the advantage of speed and using fewer features in the case of similar results obtained.
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Wang, H., Zhang, Y., Zhou, G. (2013). Sentence Compression Based on ILP Decoding Method. In: Zhou, G., Li, J., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2013. Communications in Computer and Information Science, vol 400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41644-6_3
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DOI: https://doi.org/10.1007/978-3-642-41644-6_3
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