Abstract
With the rapid development of the Internet, it has become an indispensable part of human daily life. Network culture is one of the forms of network information expression, and humans can obtain various information from it. The formation of multiculturalism is inseparable from the effective dissemination of online culture. The information of these cultures not only has an impact on the individual’s life but also brings many changes to the society. It is very valuable to be able to quickly detect and disseminate positive factors in the network culture. In view of this situation, this paper first introduces the classification technology of culture and the introduction of semantic association in network text. With the help of semantic association information in network text, this paper proposes a fusion video of convolutional neural network algorithm for football scenes. Cultural factors in the event are tested. The training text is used for initialization learning, and the training module is used to effectively extract the network text features. Based on the convolutional neural network, a detection model of wonderful events was established, which achieved the correct detection of goals, corner kicks, penalty kicks, and red and yellow cards. It can quickly provide useful cultural information to human beings, enabling such cultures to spread rapidly. The experimental results demonstrate the effectiveness of the proposed method.
Similar content being viewed by others
References
Lee DH, Im S, Taylor CR (2008) Voluntary self-disclosure of information on the Internet: a multimethod study of the motivations and consequences of disclosing information on blogs. J Psychol Market 25(7):692–710
Bowman SL, Atanasov N, Daniilidis K, Pappas GJ (2017) Probabilistic data association for semantic SLAM. IEEE Internation-al Conference on Robotics & Automation, https://doi.org/10.1109/ICRA.2017.7989203
Mo YH, Zhong C, Tang JH (2011) Functional-trust based security data aggregation method in wireless sensor networks. J Chin Comput Syst 32(1):80–84
Wang YB, You ZH, Li X (2017) PCVMZM: using the probabilistic classification vector machines model combined with a Zernike moments descriptor to predict protein-protein interactions from protein sequences. Int J Mol Sci 18(5):1029
Heather F, Doherty NF (2003) The application of information security policies in large UK-based organizations: an exploratory investigation. J Inf Manag Comput Secur 11(3):106–114
Unnikrishnan S, Singh A (2010) Resources, conservation and recycling. J Resourc Conserv Recycl 54(10):630–640
Yin HY, Lefticariu L, Wei JC (2015) Water inrush risk zoning and classification during coal seam mining in the Jiangzhuang coal mine, Shandong province. J China Min Magazine 24(10):149–154
Chen Y, Zhao D, Lv L, D C (n.d.) A visual attention based convolutional neural network for image classification. Intelligent Control & Automation
Mark W, Eric L, Lee AKC (2015) Leveraging anatomical information to improve transfer learning in brain–computer interfaces. J Neural Eng 65(5):1107–1116
Magrabi F, Ong MS, Runciman W, Enrico C (2012) Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc 19(1):45–53
Thompson T, Sowunmi O, Misra S, Fernandez-Sanz L, Crawford B, Soto R (2017) An expert system for the diagnosis of sexually transmitted diseases ESSTD. J Intell Fuzzy Syst 33(4):2007–2017
Bardsiri AK (2018) A new combinatorial framework for software services development effort estimation. Int J Comput Appl 40(1):14–24
Gao W, Zhu L, Guo Y, Wang K (2017) Ontology learning algorithm for similarity measuring and ontology mapping using linear programming. J Intell Fuzzy Syst 33(5):3153–3163
Lam SW, Jimenez CR, Boven EL (2014) Breast cancer classification by proteomic technologies: current state of knowledge. J Cancer Treat Rev 40(1):129–138
Rafi M, Shaikh MS, Farooq A (2010) Document clustering based on topic maps. J Int Comput Appl 12(1):24–28
Wu Z, Zhou YD, Shi ZZ, Zhang aCS (2016) Cyborg intelligence: recent progress and future directions. IEEE Intell Syst 31(6):44–50. https://doi.org/10.1109/mis.2016.105
Gao W, Wang W (2017) A tight neighborhood union condition on fractional (g, f,n′,m)-critical deleted graphs. Colloq Math-Warsaw 149(2):291–298
Hentschel R, Leyh C, Petznick A (2018) Current cloud challenges in Germany: the perspective of cloud service providers. J Cloud Comput 7(1)
Zhang Q, Wang H (Feb. 2017) Speech emotion recognition model based on kernel canonical correlation analysis and support vector machine. J Nanjing Univ Sci Technol 41(2):193–218
Zheng Y (1993) Calculation of oxygen isotope fractionation in hydroxyl-bearing silicates. J Earth Planet Sci Lett 120(5):1079–1091
Tai KS, Socher R, Manning CD (2015) Improved semantic representations from tree-structured long short-term memory networks. J Comput Sci 5(1):15–1150
Maturana D, Scherer S (2015) VoxNet: a 3D convolutional neural network for real-time object recognition. IEEE/RSJ International Conference on Intelligent Robots & Systems, pp. 922–928. https://doi.org/10.1109/IROS.2015.7353481
Dan CC, Meier U, Gambardella LM, Schmidhuber J (2011) Convolutional neural network committees for handwritten character classification. International Conference on Document Analysis & Recognition, pp. 1135–1139
Mi C, Wang J, Mi W, Huang Y, Zhang Z, Yang Y, Jiang J, Octavian P (2019) Research on regional clustering and two-stage SVM method for container truck recognition. Discrete Contin Dynam Syst 12(4–5):1117–1133
Moorthy T, Gopalakrishnan S (2017) IO and data management for infrastructure as a service FPGA accelerators. J Cloud Comput 6(1)
Jia W, Peng H (2008) Local and global preserving based semi-supervised dimensionality reduction method. J Softw 19(11):2833–2842
Datta S, Pihur V, Datta S (2010) An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional da-ta. J BMC Bioinformatics 11(1):Dce
Dai J, Xu Q (Jan. 2013) Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification. J Appl Soft Comput 13(1):211–221
Zhang M, Lu ZT (2010) Image segmentation based on mutual information. Chin J Comput 2(4):71–74
Schnabel K, Asendorpf JB, Greenwald A (2008) Understanding and using the implicit association test: V. measuring semantic aspects of trait self-concepts. J Euro J Personality 22(8):695–706
Kim KK, Karunanayaka P, Privitera MD, Hollandbe SK, Szaflarskiabcd JP (2011) Semantic association investigated with fMRI and independent component analysis. J Epilepsy Behav 20(4):613–622
Dewasurendra M, Vajravelu K (2018) On the method of inverse mapping for solutions of coupled systems of nonlinear differential equations arising in nanofluid flow, heat and mass transfer. Appl Math Nonlinear Sci 3(1):1–14
Hubert L, Arabie P (2012) Assessing drug target association using semantic linked data. J Plos Comput Biol 8(7):193–218
Viswanathan V, Krishnamurthi I (2012) Finding relevant semantic association paths through user-specific intermediate entities. J Human-centric Comput Inform Sci 2(1)
Liu F, Liu Y, Jin D, Jia X, Wang T (2018) Research on workshop-based positioning technology based on internet of things in big data background. Complexity:7875460
Yang A, Li S, Ren C, Liu H, Han Y, Liu L (2018) Situational awareness system in the smart campus. IEEE ACCESS 6:63976–63986
Mai J, Fan Y, Shen Y (2009) A neural networks-based clustering collaborative filtering algorithm in E-commerce recommendation system. International Conference on Web Information Systems & Mining, pp. 616–619
Hoseini AA, Zavareh Z, Lundell F, Anderson HI (2014) Rod-like particles matching algorithm based on SOM neural network in dispersed two-phase flow measurements. J Exp Fluids 55(4):1–12
Tang DQ, Zhu LI (2009) Research of frequent subgraph mining algorithm. J Comput Eng 35(9):52–54
Turney PD, Pantel P (2010) From frequency to meaning: vector space models of semantics. J Artif Intell Res 37(1):141–188
Laliberté F, Nelson WW, Lefebvre P, Schein JR, Rondeau-Leclaire J, Duh MS (2012) Impact of daily dosing frequency on adherence to chronic medications among nonvalvular atrial fibrillation patients. J Adv Ther 29(8):675–690
Tu J, Liu M, Liu H (2018)Skeleton-based human action recognition using spatial temporal 3D convolutional neural networks, Proc. 2018 IEEE International Conference on Multimedia and Expo (ICME), https://doi.org/10.1109/ICME.2018.8486566
Wang H, Cruz-Roa A, Basavanhally A, Gilmore H, Shih N (Oct. 2014) Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features. J Med Imaging 1(3):193–218
Yang A, Yang X, Wu W et al (2019) Research on feature extraction of tumor image based on convolutional neural network. IEEE Access 7(1):24204–24213
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ding, Y., Yuan, N. Logic detection method in network culture communication based on semantic relevance. Pers Ubiquit Comput 24, 287–298 (2020). https://doi.org/10.1007/s00779-019-01267-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-019-01267-4