{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:07:12Z","timestamp":1787011632831,"version":"build-2736575974"},"reference-count":21,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJWIS"],"published-print":{"date-parts":[[2020,8,13]]},"abstract":"\n Purpose<\/jats:title>\n The purpose of constructing the technology\/function matrix is to analyze the patents in the target domain. The extraction of technology words is an important part of the construction of technology\/function matrix. This algorithm is used to solve the problem of low efficiency of traditional Chinese process patents technology words extraction.<\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n The authors propose a Chinese process patents technology words extraction method based on the improved term frequency\u2013inverse document frequency (TF-IDF) algorithm to help technicians obtain the technology words in the target domain. According to the characteristics of Chinese process patents technology words, the TF value of candidate technology words is divided into four parts, and the corpus of IDF value calculation of candidate technology words is selected.<\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n Through the test of Chinese process patents in the domain of path planning, this study shows that the method is feasible and practical. It can help users quickly and accurately obtain the technology words of Chinese process patents in the target domain.<\/jats:p>\n <\/jats:sec>\n \n Practical implications<\/jats:title>\n With the increasing number of patents on the network-based patent information platform, patent analysis of massive Chinese process patents has become a research focus. The method proposed in this paper can facilitate users to extract technology words from massive Chinese process patents for patent analysis.<\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n This paper aims to improve the efficiency of Chinese process patents technology words extraction. The authors hope that the proposed method can reduce the labor and time cost of Chinese process patents technology words extraction.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/ijwis-06-2020-0033","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T04:03:45Z","timestamp":1597118625000},"page":"315-329","source":"Crossref","is-referenced-by-count":2,"title":["Web-based methodology for extracting technology words in Chinese process patents"],"prefix":"10.1108","volume":"16","author":[{"given":"Yuexin","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gongchang","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","reference":[{"key":"key2020100707571032100_ref001","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1145\/3368567.3368572","article-title":"Authorship clustering using TF-IDF weighted Word-Embeddings","volume-title":"Proceedings of the 11th Forum for Information Retrieval Evaluation","year":"2019"},{"key":"key2020100707571032100_ref002","article-title":"Pre-training tasks for embedding-based large-scale retrieval","year":"2020"},{"issue":"2","key":"key2020100707571032100_ref003","first-page":"251","article-title":"TF-IDF based loop closure detection algorithm for slam","volume":"49","year":"2019","journal-title":"Dongnan Daxue Xuebao"},{"issue":"3","key":"key2020100707571032100_ref004","first-page":"378","article-title":"Chinese fasttext short text classification method integrating TF-IDF and LDA","volume":"37","year":"2019","journal-title":"Journal of Applied Sciences"},{"issue":"12","key":"key2020100707571032100_ref005","first-page":"36","article-title":"Keyword extraction of patent document: an improved approach","volume":"33","year":"2014","journal-title":"Journal of Intelligence"},{"key":"key2020100707571032100_ref006","first-page":"263","article-title":"BNS feature scaling: an improved representation over tf-idf for svm text classification","year":"2008"},{"key":"key2020100707571032100_ref007","unstructured":"Gebre, B.G. 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