| In the process of product innovation design, some users are very familiar with the background of the product and are very interested in the product innovation design. They usually can propose some critical comments which can provide large amounts of technical supports for the product innovation design, thus how to interact with the users sufficiently and obtain the real demands of the consumers quickly, comprehensively and efficiently is an important segment when an enterprise conducts product innovation design. It becomes a key link in the development practice of online product that how to obtain customers’ demand and to know exactly and generally the present market demand information. The questionnaire survey belongs to traditional survey methods, but due to the limit of human cost and time cost, the informants are only a part of the customers, there are also some non-prospective customers involved. In addition, the result of research relates to the quality of the questionnaires. Actually, questionnaire survey has to overcome the following problems:(1) Owing to the limitation of cost and time, the quantity of questionnaires has been restricted; (2) Because of the various states of the art and the degrees of acquaintance of products of informants, the outcome often departures the reality. Meanwhile the level of knowledge personal preferences could not be identified and predicted, the questionnaires cannot be designed pointed. To complete the questionnaires the respondents fill out the questionnaires optionally or without a warrant which leads to the survey data to be useless. With the development of Web2.0, user-generated content offers a brand-new accessing channel to obtain customer demands in the internet environment. As an important user data, online review is a pointed product evaluation which is composed freely by customers according to their auto scope, appearing in e-commerce website or in online products review in form of texts. Online reviews are positive or negative feedback information of products from customers after the products access to market. The reviews have huge amounts of data, a rich content and an extensive coverage area, and has reference value for enterprises to design products, and also for customers to have a purchase decision.Based on the above consideration, this paper research on the basis of theories and methods of product design, the user demand acquisition, data mining and Online Reviews content mining, etc. then proposed an Interactive Online user requirements acquisition method based on analysis framework of IQ-COR (Interactive Questionnaire-based on Customers professional classification with Online Reviews),which is based on Online Reviews and users specialization degree of classification and personalized needs professional classification of Online Interactive access and mining, and focus on four key problem in which the first problem ID section and determine the key attributes in user classification. Second problem is the user specialization degree classification based on key attributes and the content of Online Reviews mining. Third problem is the designing of interactive content based on user specialization degree and key attributes. Forth problem is designing a method to generate personalized interaction questionnaire based on the user specialization degree and Online Reviews Mining. This article main research content includes the following aspects:1. Put forward the acquisition method of products’ key indicators based on effective reviews of online products. According to the expected attribute set and association attributes set of products and the attribute value of existing products in field of expected products, using Euclidean distance to judge the similarity between the existing products and expected products, one can select an effective set of products. Reviews of effective products are effective reviews. Aiming at effective reviews, the product key indicator extracted, using the technology "LTP" which is developed by Harbin Institute of Technology, is determinant attribute.2. This paper brings forward a method of user specialization degree classification based on key attributes and online comment on content mining. In the first place consult the list of associated word of How Net to structure lists of different degrees of specialization. By judging the relation between the object of customers’ online review and effective set of products, one can distinguish if the customer is an effective customer. According to the customers’ reviews and list of degrees of specialization one can distinguish the customers’ degree of specialization in a key indicator. At last the enterprise could offer an individual mutual content, which is a corresponding mutual content between a key indicator of a customer’s concerned product and the degree of specialization of this indicator.3. This paper brings forward an interactive content design method based on key attributes and online product comments mining and a generation method for personalized interactive questionnaires based on the different specialization level of users. In the acquisition of users’demands phase, we judge the specialization level of users according to their online comments, and produce the contents of the personalized users’acquisition questionnaires.4. Based on the customer demand obtained online, in this article it has been used a rule mining method based on genetic algorithm. In the beginning of rule mining, rules are generated to be used in simple chromosome design. In the second stage of rule mining, using the whole set of rules to confirm the considered rule mutual solution. At last get a product designing scheme which is useful for the work of design department and its designers.At the ending of this article, according to reach contents, the prototype of "online survey system on demands of smartphones’ customer" has been designed, the associated functions, the development environment and the related technological choice have been introduced and the system working sketches has been given. |
PDF Full Text Request