Qian PJ, Chen YY, Kuo JW, Zhang YD, Jiang YZ, Zhao KF, Helo RA, Friel H, Baydoun A, Zhou FF et al (2019) mDixon-based synthetic CT generation for PET attenuation correction on abdomen and pelvis jointly using transfer fuzzy clustering and active learning-based classification. Qian PJ, Zhou JX, Jiang YZ, Liang F, Zhao KF, Wang ST, Su KH, Muzic RF (2018) Multi-view maximum entropy clustering by jointly leveraging inter-view collaborations and intra-view-weighted attributes. IEEE Trans Syst Man Cybern B Cybern 42(3):672–687 Qian PJ, Chung FL, Wang ST, Deng ZH (2012) Fast graph-based relaxed clustering for large data sets using minimal enclosing ball. Navajas J, Niella T, Garbulsky G, Bahrami B, Sigman M (2018) Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds. Mlzuyama H, Kamada E (2008) Prediction-market-based demand forecasting through dispersed knowledge aggregation. Miotto O, Tan TW, Brusic V (2008) Rule-based knowledge aggregation for large-scale protein sequence analysis of influenza A viruses. J Ambient Intell Humaniz Comput 11(1):119–138 Mezni H, Arab SA, Benslimane D, Benouaret K (2020) An evolutionary clustering approach based on temporal aspects for context-aware service recommendation. López-Ramírez P, Molina-Villegas A, Siordia OS (2019) Geographical aggregation of microblog posts for LDA topic modeling.
Lin SC, Chen YC, Yu CY (2006) Application of wiki collaboration system for value adding and knowledge aggregation in a digital archive project. Liang K, Wang C, Zhang YY, Zou WF (2018) Knowledge aggregation and intelligent guidance for fragmented learning. Li J, Huang GM, Fan CL, Sun ZL, Zhu HT (2019) Key word extraction for short text via Word2Vec, Doc2Vec, and TextRank. IEEE Trans Neural Syst Rehabil Eng 25(12):2270–2284 Jiang YZ, Wu DR, Deng ZH, Qian PJ, Wang J, Wang GJ, Chung FL, Choi KS, Wang ST (2017) Seizure classification from EEG signals using transfer learning, semi-supervised learning and TSK fuzzy system. Jiang YZ, Chung FL, Wang ST, Deng ZH, Wang J, Qian PJ (2014) Collaborative fuzzy clustering from multiple weighted views. IEEE Trans Parallel Distrib Syst 30(9):2090–2100 Ji SH, Satish N, Li S, Dubey PK (2019) Parallelizing word2vec in shared and distributed memory.
Gadomer Ł, Sosnowski ZA (2019) Knowledge aggregation in decision-making process with C-fuzzy random forest using OWA operators. Neural Comput Appl 32(11):6611–6618įu K, Li J, Zhang Y, Shen HZ, Tian YH (2020) Model-guided multi-path knowledge aggregation for aerial saliency prediction. Strateg Manag J 41(11):1983–2014ĭu TT, Wen GQ, Cai ZG, Zheng W, Tan ML, Li YD (2018) Spectral clustering algorithm combining local covariance matrix with normalization. Nat Lang Eng 23(1):155–162ĭavis JP, Aggarwal VA (2020) Knowledge mobilization in the face of imitation: microfoundations of knowledge aggregation and firm-level innovation. To solve the problems, this research extracts keywords from the articles published on the WeChat platform as article tags and proposes a framework for knowledge aggregation on the WeChat platform based on tag clustering.īaayen H (1992) Statistical models for word frequency distributions: a linguistic evaluation.
How to extract the knowledge that users need from articles in different fields to help users find valuable knowledge quickly and effectively, in addition to how to realize domain knowledge resource retrieval and navigation, are important issues facing the current WeChat platform to carry out knowledge services. To save users' effective reading time and improve users' reading efficiency, the articles published on the platform can be preprocessed to enable quick matching between readers and articles. Since the articles published on the WeChat platform do not have corresponding keywords or tags, readers cannot quickly acquire knowledge, nor can they realize navigation and query of knowledge resources. However, with the increase in the number of posts, readers spend considerable time and energy. With the increase in the number of visits to the WeChat Official Accounts Platform (referred to as WeChat platform), the number of scientific research published by the platform has also increased rapidly. Tags are similar to keywords, which can express and convey the main ideas or key knowledge of the article.
As an important part of social networks, tags are widely used.