Download Advances in Artificial Intelligence: 22nd Canadian by Evgeniy Gabrilovich (auth.), Yong Gao, Nathalie Japkowicz PDF

By Evgeniy Gabrilovich (auth.), Yong Gao, Nathalie Japkowicz (eds.)

This e-book constitutes the refereed complaints of the 22st convention of the Canadian Society for Computational stories of Intelligence, Canadian AI 2009, held in Windsor, Canada, in may possibly 2008.

The 30 revised complete papers awarded including five revised brief papers and eight papers from the graduate scholar symposium have been rigorously reviewed and chosen from seventy five submissions. The papers current unique high quality learn in all components of man-made Intelligence and observe historic AI strategies to trendy challenge domain names in addition to fresh concepts to old challenge settings.

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Read or Download Advances in Artificial Intelligence: 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009 Kelowna, Canada, May 25-27, 2009 Proceedings PDF

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Additional resources for Advances in Artificial Intelligence: 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009 Kelowna, Canada, May 25-27, 2009 Proceedings

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Higher-level IBM models can potentially improve the quality of the word alignments produced. At the very least, HMM models [14], for which Viterbi alignments can be computed efficiently, should be considered. The alignment method used in current phrasebased SMT is another alternative we are considering. Acknowledgements This research is being funded by an NSERC grant. The authors wish to thank Elliott Macklovitch for his contribution to this work. References 1. : Transsearch: What are translators looking for?

The reduction of the variants to display for each query was quantitatively evaluated with two versions of our merge process, which differ only in the edit distance used to compare various forms. 22 variants per pattern. 88 on average). From these numbers, it can be seen that merging grammatical words dramatically decreases the number of outputs of our system, thereby allowing for the display of more different translations. It often leads to patterns that are easily understandable. For example, our system merges the sequences mani` ere g´ en´ erale, de mani` ere g´ en´ erale, une mani` ere g´ en´ erale and d’une mani` ere g´ en´ erale into the pattern [de]?

According to this method, 4 526 of the 5 000 most frequent queries submitted by users to the system actually occured in our translation memory; of these 2 130 had a translation either in the bilingual phrase dictionary (713) or in a classical bilingual word dictionary (the remaining). From the memory, we retrieved a maximum of 5 000 pairs of sentences for each of those 2 130 queries, leading to a set of 1 102 357 pairs of sentences, with an average of 517 pairs of sentences per query. 5 different transpots, and a maximum of 37.

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