Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in various tasks. However, effectively evaluating these MLLMs on face perception remains largely unexplored. To address this gap, we i...
Entity resolution (ER) is the problem of identi- fying and grouping different manifestations of the same real world object. Algorithmic approaches have been developed where most tasks offer superior performance unde...
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Entity resolution (ER) is the problem of identi- fying and grouping different manifestations of the same real world object. Algorithmic approaches have been developed where most tasks offer superior performance under super- vised learning. However, the prohibitive cost of labeling training data is still a huge obstacle for detecting duplicate query records from online sources. Furthermore, the unique combinations of noisy data with missing elements make ER tasks more challenging. To address this, transfer learning has been adopted to adaptively share learned common structures of similarity scoring problems between multiple sources. Al- though such techniques reduce the labeling cost so that it is linear with respect to the number of sources, its random sam- piing strategy is not successful enough to handle the ordinary sample imbalance problem. In this paper, we present a novel multi-source active transfer learning framework to jointly select fewer data instances from all sources to train classi- fiers with constant precision/recall. The intuition behind our approach is to actively label the most informative samples while adaptively transferring collective knowledge between sources. In this way, the classifiers that are learned can be both label-economical and flexible even for imbalanced or quality diverse sources. We compare our method with the state-of-the-art approaches on real-word datasets. Our exper- imental results demonstrate that our active transfer learning algorithm can achieve impressive performance with far fewerlabeled samples for record matching with numerous and var- ied sources.
To accelerate the selection process of feature subsets in the rough set theory (RST), an ensemble elitist roles based quantum game (EERQG) algorithm is proposed for feature selec- tion. Firstly, the multilevel eli...
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To accelerate the selection process of feature subsets in the rough set theory (RST), an ensemble elitist roles based quantum game (EERQG) algorithm is proposed for feature selec- tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles' performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec- tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Finally, the en- semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which will greatly improve the fea- sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.
Privacy preservation is a crucial problem in resource sharing and collaborating among multi-domains. Based on this problem, we propose a role-based access control model for privacy preservation. This scheme avoided th...
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Design patterns add more reliability, flexibility and reusability to a software system. Taking advantage of design patterns is usually beneficial to software design and makes software development relatively easier. Th...
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With the development of high-performance computing and the expansion of large-scale multiprocessor sys-tems,it is significant to study the reliability of *** fault diagnosis is of practical value to the reliabilityana...
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With the development of high-performance computing and the expansion of large-scale multiprocessor sys-tems,it is significant to study the reliability of *** fault diagnosis is of practical value to the reliabilityanalysis of multiprocessor *** this paper,we design a linear time diagnosis algorithm with the multiprocessor sys-tem whose threshold is set to 3,where the probability that any node is correctly diagnosed in the discrete state can be ***,we give the probabilities that all nodes of a d-regular and d-connected graph can be correctly diag-nosed in the continuous state under the Weibull fault distribution and the Chi-square fault *** prove thatthey approach to 1,which implies that our diagnosis algorithm can correctly diagnose almost all nodes of the graph.
Translation model containing translation rules with probabilities plays a crucial role in statistical machine translation. Conventional method estimates translation probabilities with only the consideration of cooccur...
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Translation model containing translation rules with probabilities plays a crucial role in statistical machine translation. Conventional method estimates translation probabilities with only the consideration of cooccurrence frequencies of bilingual translation units, while ignoring document-level context information. In this paper, we extend the conventional translation model to a topic-triggered one. Specifically, we estimate topic-specific translation probabilities of translation rules by leveraging topical context information, and online score selected translation rules according to topic posterior distributions of translated sentences. As compared with the conventional model, our model allows for more fine-grained distinction among different translations. Experiment results on large data set demonstrate the effectiveness of our model.
Text categorization has been widely studied for years. However, conventional plain text categorization approaches which work good in plain text behave poor when they are simply applied to enriched format texts. An cat...
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With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. Ho...
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With the startup of the Golden Agriculture Project, the step of being-information of agriculture is becoming rapid. And the transformation and share of data is indispensable to the being-information of agriculture. How to implement data combination, data transformation and data receiving applications are the important means to complete the information share safely and enhance the efficiency. The paper starts with searching of methods to implement data interchange, and introduce some of the methods, points of the techniques, etc. Basing on this, the paper also introduces the detail requirement analyses, system design and detail implementation of the system. According to the requirement and trait of the project, a data interchange system is researched and completed. And a data interchange model based on message-oriented middleware (MOM) is presented in this paper, which builds a middleware between the province and the ministry taking part in data interchange. The system has traits as follows: 1. keeping the data safe and credible while it is transformed. 2. having excellent transplantable and applied capability. 3. doesn't need intervention of workman in the process of data interchange. 4. applying the data interchange between databases of different structure. 5. being simple to be developed and applied. MOM TongLink/Q offers interfaces for application development, and it completes the data transformation through the internet. The integration adapters developed do the data management, which are developed based on the Frame for Applications Integration TongIntegrator. This method offers a new approach to resolve the question of data interchange. Now the system has been successfully applied in the data interchange project of Ministry of Agriculture.
In automated trust negotiation(ATN), strangers build trust relationship by disclosing attributes credentials alternately. In the recent study of ATN, there was no rigorous formal definition of ATN abstract model, and ...
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