{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T12:03:08Z","timestamp":1757592188702,"version":"3.41.2"},"reference-count":19,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T00:00:00Z","timestamp":1617062400000},"content-version":"vor","delay-in-days":88,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Intelligent communication processing in English aims to obtain effective information from unstructured text data using various text processing techniques. Text vector representation and text similarity calculation are important fundamental tasks in the whole field of natural language processing. In response to the shortcomings of existing sentence vector representation models and the singularity of text similarity algorithms, improved models and algorithms are proposed based on a thorough study of related domain technologies. This paper presents an in\u2010depth and comprehensive study of text vectorization representation and text similarity calculation algorithms in the field of natural language processing. The existing text vectorized representation models and text similarity computation algorithms are described, and their shortcomings are summarized to provide a basis for the background and significance of this paper, as well as to provide ideas for improvement directions. It is experimentally verified that the sentence vector model proposed in this paper achieves higher accuracy than the SIF sentence vector model for text classification tasks. In the task of text similarity computation, it achieves better results in three evaluation metrics: accuracy, recall, and F1 value. The algorithm also improves the computational efficiency of the model to a certain extent by removing feature words with low feature contribution. The algorithm first improves the deficiencies of the traditional word\u2010shift distance algorithm by defining multifeature fusion weights and realizes a text similarity calculation algorithm based on multifeature weighted fusion with better similarity calculation results. Then, a linear weighting model is constructed to further combine the similarity calculation results of the hierarchical pooled IIG\u2010SIF sentence vectors to realize the multimodel fusion text similarity calculation algorithm.<\/jats:p>","DOI":"10.1155\/2021\/5575417","type":"journal-article","created":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T22:35:08Z","timestamp":1617143708000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Design and Implementation of English Intelligent Communication Platform Based on Similarity Algorithm"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7377-0204","authenticated-orcid":false,"given":"Yujie","family":"Chai","sequence":"first","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,3,30]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.22159\/ajpcr.2017.v10s1.19757"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/jsen.2016.2624314"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2018.2868380"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsp.2017.2712121"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.32604\/iasc.2020.013929"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10554-020-01878-6"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.3991\/ijet.v13i10.9457"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.3991\/ijet.v12i12.7963"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.14445\/22315373\/ijmtt-v53p556"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-018-9523-8"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-179991"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-179792"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-169367"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-189052"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-179788"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-179946"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4207"},{"key":"e_1_2_9_18_2","first-page":"2204","article-title":"Research on the development and application of English intelligent translation human-machine interface system","volume":"63","author":"Song W.","year":"2020","journal-title":"Solid State Technology"},{"key":"e_1_2_9_19_2","first-page":"1950","article-title":"Study on schema theory applied in college English esp curriculum based on intelligent optimization algorithm","volume":"63","author":"Zhao C.","year":"2020","journal-title":"Solid State Technology"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/5575417.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/5575417.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/5575417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T21:45:45Z","timestamp":1723239945000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/5575417"}},"subtitle":[],"editor":[{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":19,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/5575417"],"URL":"https:\/\/doi.org\/10.1155\/2021\/5575417","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"type":"print","value":"1076-2787"},{"type":"electronic","value":"1099-0526"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-02-06","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-03-19","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-03-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"5575417"}}