BIAS
发表于 2025-3-23 12:58:24
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superfluous
发表于 2025-3-23 17:53:35
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削减
发表于 2025-3-23 21:57:23
https://doi.org/10.1007/978-3-030-59592-0artificial intelligence; bandwidth; computer networks; computer systems; databases; Human-Computer Intera
植物群
发表于 2025-3-24 00:45:48
978-3-030-59591-3Springer Nature Switzerland AG 2020
马笼头
发表于 2025-3-24 03:27:13
Services Computing – SCC 2020978-3-030-59592-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
Narcissist
发表于 2025-3-24 07:32:58
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松软
发表于 2025-3-24 11:21:16
Web Service Composition by Optimizing Composition-Segment Candidatesbuilding a web service dependency graph. Experimental results on both Web Service Challenge 2009’s datasets and substantial datasets randomly generated show that the proposed method outperforms the state-of-art while achieving a much ideal tradeoff among all the objectives with better performance.
我正派
发表于 2025-3-24 18:03:21
Collaborative Learning Using LSTM-RNN for Personalized Recommendation sequence-to-sequence recommendations. Our proposed model builds on the strength of collaborative filtering while preserving individual user preferences for personalized recommendation. We conduct experiments using Movielens (.) dataset to evaluate our proposed model and empirically demonstrate that
HAUNT
发表于 2025-3-24 22:42:02
An Attention Model for Mashup Tag Recommendationsubsequently recommend top-N words with highest attention weights as tags. Our model is based on the intuition that not every word in a mashup description is equally relevant in identifying its functional aspects. Therefore, determining the relevant sections involves modeling the interactions of the
一窝小鸟
发表于 2025-3-25 02:33:26
On the Diffusion and Impact of Code Smells in Web Applicationss to monitor the existence and spread of such anti-patterns. In this paper, we specifically target web apps built with PHP being the most used server-side programming language. We conduct the first empirical study to investigate the diffuseness of code smells in Web apps and their relationship with