By Erik D. Demaine (auth.), Roberto Grossi, Fabrizio Sebastiani, Fabrizio Silvestri (eds.)
This ebook constitutes the complaints of the 18th overseas Symposium on String Processing and data Retrieval, SPIRE 2011, held in Pisa, Italy, in October 2011.
The 30 lengthy and 10 brief papers including 1 keynote provided have been rigorously reviewed and chosen from 102 submissions. The papers are dependent in topical sections on creation to net retrieval, series studying, computational geography, space-efficient information constructions, algorithmic research of organic information, compression, textual content and algorithms.
Read or Download String Processing and Information Retrieval: 18th International Symposium, SPIRE 2011, Pisa, Italy, October 17-21, 2011. Proceedings PDF
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Additional info for String Processing and Information Retrieval: 18th International Symposium, SPIRE 2011, Pisa, Italy, October 17-21, 2011. Proceedings
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For a given pair of values (m, k) we want to find a seed with the largest possible weight since, under standard assumptions, this maximizes the filtration efficiency. For the problem of lossless seed design, an important breakthrough has been obtained in [4] where, for any given pair (m, k), the authors provide a spaced seed with an asymptotically optimal weight. e. e. up to a few hundreds): the seeds in [4] are asymptotically optimal as m → ∞, but we have no guarantees on their quality for small m.
Recall from Section 3 that our approach modifies the original snippet by replacing some text. The exact same title and URL were presented to the workers in case they wanted to look at the article in detail. The results show that 42% of the time the modified snippet was preferred and in 35% of the time the original snippet was selected. For the remaining 23%, it was not possible to reach a consensus among workers. An example would be that 2 workers selected snippet A, 2 workers B, and the third one selected that A and B look the same.
Grossi et al. ): SPIRE 2011, LNCS 7024, pp. 26–31, 2011. c Springer-Verlag Berlin Heidelberg 2011 Enhancing Document Snippets Using Temporal Information 2 27 Temporal Order As the basis for analyzing a document in time, we adopt the temporal framework presented in [2]. We assume a discrete representation of time based on the Gregorian Calendar, with a single day being an atomic time interval called chronon. Assume a document d from a document collection D. Using the approach presented in [2], one can determine the sequence t-seq(d) = (c1 , p1 ), (c2 , p2 ), · · · , (ck , pk ) of chronon/position pairs that describe the temporal expressions occurring in d.