本文關(guān)鍵詞： 知識聚類 小家電產(chǎn)品 形態(tài)意象 聚類分析　出處：《陜西科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：在大數(shù)據(jù)時代背景下,知識聚類對知識的匯集起著重要作用;它是現(xiàn)在科技迅速發(fā)展的產(chǎn)物,對于知識的管理與收集有積極意義。同時,也是搜索數(shù)據(jù)對象之間,價值聯(lián)系的關(guān)鍵因素。在產(chǎn)品形態(tài)設(shè)計中,運用知識聚類方法可以直接、快速的將知識聚合、集合。物質(zhì)產(chǎn)品的不斷豐富,人們的需求已經(jīng)從物質(zhì)層面的滿足上升到精神層面的滿足。人性化的產(chǎn)品不僅必須具有良好的功能、界面、操作方式等技術(shù)特征,更需要考慮產(chǎn)品的外觀形態(tài)乃至感性因素,以滿足消費者的心理需求。在成熟的市場競爭中,不同品牌下同類產(chǎn)品的同質(zhì)化趨向更加明顯,僅僅依賴產(chǎn)品實用功能方面的創(chuàng)新,已經(jīng)無法滿足消費者的青睞,在這種情況下,個性化和時尚化逐漸成為消費者是否購買該產(chǎn)品的決定性因素。這就需要設(shè)計師在諸多的設(shè)計情報中挖掘使用者對產(chǎn)品的直覺印象,即產(chǎn)品意象。正確的產(chǎn)品意象會使產(chǎn)品滿足于用戶需求,進而滿足市場需求。本文以小家電產(chǎn)品電熱水壺為例,運用知識聚類的方法與技術(shù)對其造型形態(tài)進行研究。知識聚類、感性意象、形態(tài)分析以及統(tǒng)計分析是本論文的理論基礎(chǔ)。本論文主要分為三個部分。第一,感性意象知識的獲取。運用知識聚類盡可能多的聚合產(chǎn)品樣本與意象詞匯;運用形態(tài)分析法,分析歸納產(chǎn)品的形態(tài)要素;對其進行意象試驗評價,收斂意象詞匯個數(shù);最終得到代表性感性意象詞匯。第二,產(chǎn)品形態(tài)要素與感性意象的關(guān)聯(lián)性分析。運用多元線性回歸分析,建立起形態(tài)要素與感性意象之間的聯(lián)系,歸納得到每一種意象所對應(yīng)的形態(tài)要素,并繪制組合示意圖。第三,案例設(shè)計應(yīng)用。通過用戶調(diào)研明確產(chǎn)品定位,確定產(chǎn)品風(fēng)格意象,選擇產(chǎn)品形態(tài)示意圖,對選擇后的方案進行方案細化并建立三維模型,完成產(chǎn)品形態(tài)設(shè)計。在論文中,運用語義差異法對產(chǎn)品形態(tài)與意象詞匯進行調(diào)研;用因子分析、聚類分析收斂意象詞匯個數(shù);用多元回歸分析法,分析產(chǎn)品意象與代表性詞匯之間的關(guān)聯(lián)性。本論文以知識聚類為導(dǎo)向,運用知識聚類的技術(shù)和方法,與小家電產(chǎn)品意象形態(tài)設(shè)計相結(jié)合。將兩個不同領(lǐng)域的學(xué)科結(jié)合運用,知識聚類對產(chǎn)品感性意象挖掘以及對產(chǎn)品意象知識的獲取有重要的指導(dǎo)意義;同時與產(chǎn)品形態(tài)設(shè)計有機的結(jié)合起來,可為以后的產(chǎn)品意象形態(tài)設(shè)計提供理論基礎(chǔ),進而提高設(shè)計效率和成本開發(fā)。
[Abstract]:Under the background of big data era, knowledge clustering plays an important role in the collection of knowledge. It is the product of the rapid development of science and technology, and has a positive significance for the management and collection of knowledge. At the same time, it is also the key factor of the value relationship between the search data objects. Knowledge clustering method can be used directly and quickly to aggregate and aggregate knowledge. People's needs have risen from the material level of satisfaction to the spiritual level of satisfaction. Humanized products must not only have good functions, interfaces, operating methods and other technical characteristics. More need to consider the appearance of products and even emotional factors to meet the psychological needs of consumers. In the mature market competition, the homogeneity of similar products under different brands is more obvious. Only rely on the product functional innovation, has been unable to meet the needs of consumers, in this case. Personalization and fashion have gradually become the decisive factor for consumers to buy the product, which requires designers to tap the user's intuitive impression of the product in a lot of design information. That is, product image. The correct product image will make the product meet the needs of users, and then meet the market demand. This paper takes the electric kettle of small household appliances as an example. Knowledge clustering, perceptual imagery, morphological analysis and statistical analysis are the theoretical basis of this paper. This paper is divided into three parts. First. Acquisition of perceptual image knowledge. Using knowledge clustering to aggregate product samples and image vocabulary as much as possible; The morphological analysis method is used to analyze and induce the morphological elements of the product. The number of image words is converged. Finally get the representative perceptual image vocabulary. Second product form elements and perceptual image correlation analysis. Using multiple linear regression analysis to establish the relationship between morphological elements and perceptual images. Get the corresponding morphological elements of each image, and draw a combination of schematics. Third, case design application. Through user research to identify product positioning, determine product style image, choose product form map. In this paper, the semantic difference method is used to investigate the product morphology and image vocabulary. The number of image words converged by factor analysis and cluster analysis; This paper uses multiple regression analysis to analyze the relationship between product image and representative vocabulary. This paper is guided by knowledge clustering and applies the technology and method of knowledge clustering. Combining with the image form design of small household appliances, the knowledge clustering has important guiding significance to the product perceptual image mining and the acquisition of product image knowledge by combining the two disciplines in different fields. At the same time, the combination of product form design and product form design can provide the theoretical basis for the future product image form design, and then improve the design efficiency and cost development.
【學(xué)位授予單位】：陜西科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM925.55

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