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Robotics is on the cusp of dramatic transformation. more and more complicated robots with extraordinary autonomy are discovering new purposes, from clinical surgical procedure, to development, to domestic prone. by contrast heritage, the algorithmic foundations of robotics have gotten extra an important than ever, so one can construct robots which are quick, secure, trustworthy, and adaptive.
Evolutionary Computing: AISB Workshop Sheffield, UK, April 3–4, 1995 Selected Papers
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Springer (2003) 223–241. 20. , Evans, D. A: Automatic Transliteration for Japanese-to-English Text Retrieval. In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2003) 353–360. 21. , Hull, D. , Evans, D. : Towards Effective Strategies for Monolingual and Bilingual Information Retrieval: Lessons Learned from NTCIR-4. ACM Transactions on Asian Language Information Processing. (to appear) 22. , Vines, P: Using the web for automated translation extraction in cross-language information retrieval.
19. , Evans, D. : Resolving Translation Ambiguity Using Monolingual Corpora. , Gonzalo, J. (eds): Advances in Cross-Language Information Retrieval: Third Workshop of the Cross-Language Evaluation Forum, CLEF 2002, Rome, Italy, September 19–20, 2002. Lecture Notes in Computer Science, Vol 2785. Springer (2003) 223–241. 20. , Evans, D. A: Automatic Transliteration for Japanese-to-English Text Retrieval. In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2003) 353–360.
Headline generation can be obtained as a weighted combination of the content and structure model log probabilities shown in formula (3). The system was trained on the 3 months Mainichi Shimbun articles((27,133 articles from Jan. to Mar. 1999) for Japanese corpus. We estimate α, β and γ in formula (3) using 5 cross-validation1. Fig. 1 illustrates sample output using Mainichi Shimbun corpus. Numbers to the right are log probabilities of the word sequence. 2 Tracking by Hierarchical Classification In the TDT tracking task, the number of labeled positive training stories is small (at most 16 stories) compared to the negative training stories.