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Titlebook: Her-vor-bringungen; ?sthetische Erfahrun Beatrice Nunold Book 2003 Springer Fachmedien Wiesbaden 2003 Bense, Max.Bildwissenschaft.Fiktion.H

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41#
發(fā)表于 2025-3-28 15:01:48 | 只看該作者
Beatrice Nunoldctive methods that compute a Gr?bner basis of an ideal, we need to endow the underlying ring with certain additional constructive properties. Two such properties we consider in detail, are . and .. A computable Noetherian ring with such properties will be referred to as a ..
42#
發(fā)表于 2025-3-28 21:57:16 | 只看該作者
Beatrice Nunold the constructive algebraic methods to differential algebra. However, the concept languished in near oblivion until the seventies when the Chinese mathematician Wu Wen-Tsün [209–211] realized its power in the case where Ritt’s techniques are specialized to commutative algebra. In particular, he exhi
43#
發(fā)表于 2025-3-29 01:41:44 | 只看該作者
Beatrice Nunoldose to the industry is the capability to estimate costs, especially when switching from one provider to another. In this paper we introduce an agreement-based scheduling algorithm, aimed to bring an adaptive fault tolerant system. For the agreement protocol we proposed a 3-Tier structure of resource
44#
發(fā)表于 2025-3-29 05:31:25 | 只看該作者
Beatrice Nunoldrtually anyone has the potential to plug in valuable information, which brings a lot of benefits such as low cost and high immediacy, particularly in some location-based services (LBS). On the other side, there also exist many problems need to be solved in crowdsourcing. For example, the quality con
45#
發(fā)表于 2025-3-29 09:40:08 | 只看該作者
Beatrice Nunoldlations. Here a novel parallel social influence model is proposed to face to these challenges. In this paper, we firstly propose impact factors named Social Network Centricity and Weibo Heat Trend, describe a general algorithm named ActionRank to calculate the user influence based on these factors a
46#
發(fā)表于 2025-3-29 11:30:33 | 只看該作者
(NGCF) has the problem of insufficient feature extraction of user vector and item vector. In addition, it uses the linear combination of the final embedding vectors of user and item to calculate the inner product, which is difficult to accurately obtain the user-item prediction score. In this artic
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