Signatures of knowledge for Boolean circuits under standard assumptions

Baghery, Karim; González, Alonso; Pindado, Zaira; Ràfols, Carla

doi:10.1016/j.tcs.2022.03.006

Cited by 2 publications

(1 citation statement)

References 39 publications

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“…However, the current standard document service systems are mostly at the document granularity, which can not meet the knowledge needs of users. Based on the above considerations, it is important to combine optical character recognition, natural language processing, information visualization, information retrieval and other technologies to build a knowledge level oriented standard document information service system, which provides users with standard knowledge services such as knowledge extraction, knowledge map, and knowledge search [8][9][10]. To a certain extent, it improves the quality of standard knowledge information services and improves the user experience.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Design of Standard Knowledge Service System based on Deep Learning

Zhou

Lin

et al. 2022

EAI Endorsed Scal Inf Syst

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The development of information technology has changed the mode of communication of social information, and this change has put forward new requirements on the contents, methods and even objects of information science research. Knowledge service in the information service process can extract knowledge and information content from various explicit and implicit knowledge resources according to people’s needs, build knowledge networks, and provide knowledge content or solutions for users’ problems. Hence, it is very important to investigate how to analyze and design the advanced standard knowledge service system based on deep learning. To this end, we firstly introduce the typical deep learning networks of convolutional neural network (CNN) for the knowledge service system, and then employ the CNN to implement the knowledge classification based on deep learning. Finally, some simulation results on the knowledge service system are presented to validate the proposed studies in this paper.

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Section: Introductionmentioning

confidence: 99%