遗产
发表于 2025-3-25 05:24:46
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Magnificent
发表于 2025-3-25 11:32:17
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FLIP
发表于 2025-3-25 14:28:14
The Importance of a Battle Plantors were asked to choose a correct sentence from a multiple choice list to ensure the high-quality of corpus. The results obtained so far showed that crowdsourcing for constructing CMSC with an evaluation mechanism could be more effective than traditional experiments requiring expertise.
隼鹰
发表于 2025-3-25 16:17:51
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Gobble
发表于 2025-3-25 20:25:50
Average Reward Stochastic Gamesin the keywords of evidence and facts. Calculating the degree of association can work out the connection points of evidence chain relational model. Tabular display and graphical display of evidence chain relational model can be realized.
Negligible
发表于 2025-3-26 00:33:05
Andrey V. Shevandrin,Alla E. Kalinination Algorithm (DADC). Based on the error of prediction, both algorithms can adaptively adjust the cycle of data collection. Performance evaluation verifies that the proposed algorithms have high performance in terms of accuracy and effectiveness.
六边形
发表于 2025-3-26 08:19:22
Matthias Jeger,Urs Haegler,Roland Theisslation results show that the proposed algorithm improved the coverage quality, and completed the barrier coverage with less node moving distance and lower energy consumption, and achieved the expected coverage requirements and objectives.
NUDGE
发表于 2025-3-26 08:46:55
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Parallel
发表于 2025-3-26 12:48:28
Utilizing Crowdsourcing for the Construction of Chinese-Mongolian Speech Corpus with Evaluation Mectors were asked to choose a correct sentence from a multiple choice list to ensure the high-quality of corpus. The results obtained so far showed that crowdsourcing for constructing CMSC with an evaluation mechanism could be more effective than traditional experiments requiring expertise.
chlorosis
发表于 2025-3-26 19:44:02
A Framework of Mobile Context-Aware Recommender System,tern, in order to find both the user’s long-term behavior pattern and the new trend of his recent behavior, to predict user’s next behavior. Lastly, we discuss the difficulties and future development trend of mobile context-aware recommendation system.