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Pregled bibliografske jedinice broj: 633899

Časopis

Autori: Doko, Alen; Štula, Maja; Šerić, Ljiljana
Naslov: Improved sentence retrieval using local context and sentence length
Izvornik: Information processing & management (0306-4573) 49 (2013), 6; 1301-1312
Vrsta rada: članak
Ključne riječi: sentence retrieval; TF-ISF; context; sentence length
Sažetak:
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 (TFISF variants) also show statistically significant better results than the other tested methods.
Projekt / tema: 023-0232005-2003
Izvorni jezik: ENG
Rad je citiran u
bazama podataka:
Web of Science: Science Citation
Current Contents Citation Index
Scopus
Web of Science: Social Science Citation Index
Web of Science: Science Citation Index Expanded
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo
URL Internet adrese: http://www.sciencedirect.com/science/article/pii/S0306457313000721
http://dx.doi.org/10.1016/j.ipm.2013.06.004
Broj citata:
Altmetric:
DOI: 10.1016/j.ipm.2013.06.004
URL cjelovitog teksta:
Google Scholar: Improved sentence retrieval using local context and sentence length
Upisao u CROSBI: Maja Štula (Maja.Stula@fesb.hr), 21. Lip. 2013. u 13:35 sati



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