面向旅游企业的客户定向性信息分析的研究

发布时间：2018-05-17 08:00

本文选题：web2.0 + 旅游企业　；参考：《合肥工业大学》2013年硕士论文

【摘要】：近年来，随着旅游业的快速发展，旅游产业已经成为我国的支柱性产业之一。在我国产业结构中的地位也越来越重要。因此加强对旅游业智能化的研究显得尤为重要。此外，随着客户规模的不断壮大，游客对旅游产品或服务偏好的多样化和个性化，使得对于旅游企业的客户定向性信息分析的需求也逐渐变强。如果一家旅游企业希望在最短的时间内为客户提供尽量优质的旅游产品或服务，那么就需要对客户在产品和服务等方面定向性信息做进一步研究。本文针对旅游信息的不确定性和多样性等特征，以web2.0为核心的社交媒体（Social Media）作为研究平台，以客户发表的关于产品和服务的信息为研究对象，从海量的用户生成内容（User-generated Content，UGC）中抽取大量对企业具有重要价值的信息，为旅游企业的客户定向性信息分析提供了丰富的原料库。文中的具体研究内容主要围绕以下几个展开： (1)根据web内容的特点，在前人研究的基础上，提炼面向旅游企业的客户定向性信息分析的体系结构，并在这个体系结构的基础之上，划分出面向旅游企业的客户定向性信息分析系统的功能模型，以促进旅游企业积极改善和创新符合大众需求的旅游产品或服务。 (2)以某个特定的旅游产品或服务为研究对象，以该旅游产品或服务的特征抽取为研究目标，结合web2.0环境下客户对旅游产品和服务的偏好信息，研究基于旅游行业本体知识库的产品特征提取，提出句型匹配模式的产品或服务特征提取的方法。 (3)结合客户发表于互联网上的信息，运用结构分析和概念模型方法，构建面向旅游企业的客户定向性信息分析的情感模型，，并在此模型的基础上，对模型的各要素信息进行抽取，并计算情感强度，最终实现面向旅游企业的客户定向性信息分析。最后，对上述技术和方法进行可行性验证，结合面向旅游企业的客户定向性信息分析体系结构，设计并开发面向旅游企业的客户定向性信息分析原型系统，基本实现了系统的大部分主要功能，同时给出系统运行效果图，从而验证了本文提出方法的有效性。
[Abstract]:In recent years, with the rapid development of tourism, tourism industry has become one of the pillar industries in China. The position in our country industrial structure also becomes more and more important. Therefore, it is particularly important to strengthen the research on intelligent tourism. In addition, with the growing scale of customers, tourists' preference for tourism products or services is diversified and individualized, which makes the demand for customer-oriented information analysis of tourism enterprises become stronger and stronger. If a tourism enterprise wants to provide customers with as high quality tourism products or services as possible in the shortest time, it needs to further study the orientation information of customers in products and services. In view of the uncertainty and diversity of tourism information, this paper takes web2.0 as the core social media as the research platform, and takes the information about products and services published by customers as the research object. A large amount of information which is of great value to enterprises is extracted from massive user-generated content (UGCC), which provides a rich raw material base for the analysis of customer-oriented information of tourism enterprises. The specific research contents in this paper mainly focus on the following: 1) according to the characteristics of web content, on the basis of previous studies, the paper abstracts the architecture of customer-oriented information analysis for tourism enterprises, and based on this architecture, The functional model of the customer-oriented information analysis system for tourism enterprises is divided to promote tourism enterprises to actively improve and innovate tourism products or services that meet the needs of the public. (2) taking a particular tourism product or service as the research object, taking the feature extraction of the tourism product or service as the research goal, and combining the customer preference information of the tourism product and service under the web2.0 environment, Product feature extraction based on ontology knowledge base of tourism industry is studied, and a method of product or service feature extraction based on sentence pattern matching pattern is proposed. Based on the information published by customers on the Internet and the method of structure analysis and conceptual model, the emotional model of customer-oriented information analysis for tourism enterprises is constructed. The information of each element of the model is extracted, and the emotional intensity is calculated. Finally, the customer-oriented information analysis for tourism enterprises is realized. Finally, the feasibility of the above technologies and methods is verified, and a customer-oriented information analysis prototype system for tourism enterprises is designed and developed based on the architecture of customer-oriented information analysis for tourism enterprises. The main functions of the system are basically realized, and the running effect diagram of the system is given, which verifies the effectiveness of the proposed method.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F592.6;G353.1

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