Wei Yan, Hong Liu, Yusheng Liu, Jihua Wang, C. Zanni-Merk, D. Cavallucci, Xiaodan Yan, L. Zhang
{"title":"基于TRIZ的创造性设计的潜在语义提取与分析","authors":"Wei Yan, Hong Liu, Yusheng Liu, Jihua Wang, C. Zanni-Merk, D. Cavallucci, Xiaodan Yan, L. Zhang","doi":"10.1504/EJIE.2018.10013866","DOIUrl":null,"url":null,"abstract":"During the development of TRIZ, several knowledge sources have been developed to solve inventive problems. Even though they are about close notions, the level of detail of the descriptions is very dissimilar, making it difficult for the user to operate with them in a systematic way. To cope with this difficulty, we are interested in finding semantic links among these sources, with the goal of assisting the inventive design expert during his activities. Taking into account that all the TRIZ knowledge sources are represented as short texts and directly applying conventional topic models on such short texts may not work well, an extended latent semantic analysis model is proposed to find the missing links among the TRIZ knowledge sources. With the help of these obtained links, several heuristic abstract solutions can be obtained. In order to show this whole process, the resolution of the case of the 'Auguste Piccard's Stratostat' is elaborated in detail. [Received: 11 March 2017; Revised: 21 November 2017; Accepted 30 March 2018]","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Latent semantic extraction and analysis for TRIZ-based inventive design\",\"authors\":\"Wei Yan, Hong Liu, Yusheng Liu, Jihua Wang, C. Zanni-Merk, D. Cavallucci, Xiaodan Yan, L. Zhang\",\"doi\":\"10.1504/EJIE.2018.10013866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"During the development of TRIZ, several knowledge sources have been developed to solve inventive problems. Even though they are about close notions, the level of detail of the descriptions is very dissimilar, making it difficult for the user to operate with them in a systematic way. To cope with this difficulty, we are interested in finding semantic links among these sources, with the goal of assisting the inventive design expert during his activities. Taking into account that all the TRIZ knowledge sources are represented as short texts and directly applying conventional topic models on such short texts may not work well, an extended latent semantic analysis model is proposed to find the missing links among the TRIZ knowledge sources. With the help of these obtained links, several heuristic abstract solutions can be obtained. In order to show this whole process, the resolution of the case of the 'Auguste Piccard's Stratostat' is elaborated in detail. [Received: 11 March 2017; Revised: 21 November 2017; Accepted 30 March 2018]\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2018-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1504/EJIE.2018.10013866\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1504/EJIE.2018.10013866","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Latent semantic extraction and analysis for TRIZ-based inventive design
During the development of TRIZ, several knowledge sources have been developed to solve inventive problems. Even though they are about close notions, the level of detail of the descriptions is very dissimilar, making it difficult for the user to operate with them in a systematic way. To cope with this difficulty, we are interested in finding semantic links among these sources, with the goal of assisting the inventive design expert during his activities. Taking into account that all the TRIZ knowledge sources are represented as short texts and directly applying conventional topic models on such short texts may not work well, an extended latent semantic analysis model is proposed to find the missing links among the TRIZ knowledge sources. With the help of these obtained links, several heuristic abstract solutions can be obtained. In order to show this whole process, the resolution of the case of the 'Auguste Piccard's Stratostat' is elaborated in detail. [Received: 11 March 2017; Revised: 21 November 2017; Accepted 30 March 2018]
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.