{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:47Z","timestamp":1740120227883,"version":"3.37.3"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2019,9]]},"abstract":"<jats:p> Traditional pattern recognition is based on \u201coptimal partition\u201d and the goal is to find an optimal classification interface based on the distribution of each category in high-dimensional space, thus has its inherent shortcomings and deficiencies. While topology pattern recognition can effectively compensate for the shortcomings of traditional pattern recognition, topological pattern recognition is based on \u201ccognition\u201d and the goal is to find the appropriate cover according to the \u201ccomplex set cover\u201d in high-dimensional space to achieve cognitive effect. Topological pattern recognition can effectively consummate the characteristics of high error rate, low recognition rate and repetitive training in the existing recognition system with low training sample number. At present, topology pattern recognition has been applied in many areas of social life. However, one problem that can\u2019t be ignored is that topological pattern recognition requires a long training time and low fault tolerance rate. Therefore, this paper proposes an improved multidimensional\u2013multiresolution topological pattern recognition, and applies it to text classification and recognition. The results show that the improved multidimensional\u2013multiresolution topological pattern recognition method can effectively reduce the training time of text classification and improve the classification efficiency. <\/jats:p>","DOI":"10.1142\/s0218001419500162","type":"journal-article","created":{"date-parts":[[2018,12,27]],"date-time":"2018-12-27T04:48:52Z","timestamp":1545886132000},"page":"1950016","source":"Crossref","is-referenced-by-count":1,"title":["A Text Classification Algorithm Based on Improved Multidimensional\u2013Multiresolution Topological Pattern Recognition"],"prefix":"10.1142","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7890-8164","authenticated-orcid":false,"given":"Zhichao","family":"Li","sequence":"first","affiliation":[{"name":"School of Political Science and Public Administration, East China University of Politlcal Science and Law, Shanghai 201620, China"}]},{"given":"Jilin","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China"}]}],"member":"219","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"S0218001419500162BIB001","first-page":"487","volume-title":"Proc. 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