Article ID Journal Published Year Pages File Type
515504 Information Processing & Management 2013 12 Pages PDF
Abstract

•We extend the TF–ISF method to use local context.•We extend the TF–ISF method to promote retrieval of long sentences.•Context and promoting retrieval of long sentences both improves sentence retrieval.•We also combine using context and promoting retrieval of long sentences.•It is useful to use at the same time context and promoting retrieval of long sentences.

In this paper we propose improved variants of the sentence retrieval method TF–ISF (a TF–IDF or Term Frequency–Inverse Document Frequency variant for sentence retrieval). The improvement is achieved by using context consisting of neighboring sentences and at the same time promoting the retrieval of longer sentences. We thoroughly compare new modified TF–ISF methods to the TF–ISF baseline, to an earlier attempt to include context into TF–ISF named tfmix and to a language modeling based method that uses context and promoting retrieval of long sentences named 3MMPDS. Experimental results show that the TF–ISF method can be improved using local context. Results also show that the TF–ISF method can be improved by promoting the retrieval of longer sentences. Finally we show that the best results are achieved when combining both modifications. All new methods (TF–ISF variants) also show statistically significant better results than the other tested methods.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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