【摘要】：隨著我國經(jīng)濟和科技的迅猛發(fā)展,互聯(lián)網(wǎng)技術(shù)的日益進步,人們生活水平的逐漸提高,人們對能夠滿足個人興趣和偏好的自助游的需求也隨之增大。由于互聯(lián)網(wǎng)中充斥著大量信息,用戶在網(wǎng)上查找旅游相關(guān)信息時難以獲得自己需要的有效旅游信息。旅游推薦系統(tǒng)作為解決這一問題的方法成為學(xué)者關(guān)注的熱點,如何向用戶推薦能夠滿足其個性化旅游需求的相關(guān)旅游資訊成為研究旅游推薦的關(guān)鍵點。目前的旅游推薦系統(tǒng)通常存在冷啟動和數(shù)據(jù)稀疏的問題,并且推薦內(nèi)容都是以旅游產(chǎn)品為主,一些為用戶推薦旅游目的地的系統(tǒng)也存在推薦的旅游目的地咨詢單一,不夠豐富的情況。本文著重考慮用戶的興趣,構(gòu)建以游記為主的案例庫,采用基于案例推理的方法構(gòu)建旅游目的地個性化推薦模型,為用戶提供滿足其個性化需求且內(nèi)容豐富的旅游目的地信息,并在一定程度上解決了數(shù)據(jù)稀疏和冷啟動的問題。本文的主要研究工作如下:(1)構(gòu)建了適合基于案例推理方法的旅游目的地模型和案例用戶偏好模型。從"螞蜂窩"網(wǎng)站中獲取用戶、游記等信息形成基本案例庫,并利用構(gòu)建的用戶旅游偏好算法得到案例用戶旅游偏好度。根據(jù)用戶偏好度和改進的K-Means算法對案例用戶按照旅游目的地類型進行分類,形成各種旅游目的地類型子案例庫。在檢索案例時,只用檢索待推薦用戶所屬類型的旅游目的地類型子案例庫,使檢索效率得到有效提高。(2)構(gòu)建了案例屬性權(quán)重算法,利用調(diào)查問卷中用戶對旅游要素的評價和案例屬性權(quán)重算法對案例屬性權(quán)重進行確定。(3)構(gòu)建了改進的信任度算法,將信任度引入基于案例推理的旅游目的地個性化推薦系統(tǒng)中,并構(gòu)建了加入信任度的案例相似度算法,提高推薦結(jié)果的準確度。(4)將基于案例推理的方法運用到旅游目的地個性化推薦系統(tǒng)中,利用Mathematica軟件對相關(guān)算法進行構(gòu)建和表示,根據(jù)用戶數(shù)據(jù)進行實例驗證,初步實現(xiàn)了旅游目的地和案例游記的推薦。本文將基于案例推理技術(shù)、用戶旅游興趣和信任度的結(jié)合,對旅游者實現(xiàn)了個性化的旅游目的地和游記的推薦。既滿足了用戶的個性化需求,又為用戶提供了豐富的旅游信息。通過實例推薦和實證結(jié)果,證明了推薦算法的有效性和準確度。本文的研究對個性化旅游目的地推薦系統(tǒng)提供了一定的參考價值。
[Abstract]:With the rapid development of economy and science and technology in our country, with the increasing progress of Internet technology and the gradual improvement of people's living standards, the demand for self-help travel which can meet personal interests and preferences is also increasing. Because the Internet is full of a lot of information, it is difficult for users to obtain the effective tourism information they need when they look up tourism-related information on the Internet. As a method to solve this problem, tourism recommendation system has become the focus of scholars' attention. How to recommend relevant tourism information to users to meet their personalized tourism needs has become the key point of tourism recommendation research. At present, the tourism recommendation system usually has the problems of cold start and sparse data, and the recommendation content is mainly tourism products, and some systems that recommend tourism destination for users also have a single recommended tourism destination consultation. A situation that is not rich enough. This paper focuses on the interest of users, constructs a case base based on travel notes, and constructs a personalized recommendation model of tourism destination based on case-based reasoning, which provides users with rich tourism destination information to meet their personalized needs. To a certain extent, the problems of sparse data and cold start are solved. The main research work of this paper is as follows: (1) the tourism destination model and case user preference model suitable for case-based reasoning are constructed. The basic case base is formed by obtaining the information of users and travel notes from the "polar cell" website, and the tourism preference degree of the case users is obtained by using the constructed user tourism preference algorithm. According to the user preference and the improved K-Means algorithm, the case users are classified according to the type of tourism destination, and the subcase base of various types of tourism destination is formed. In the retrieval of cases, only the tourism destination type subcase base of the type to be recommended is searched, so that the retrieval efficiency can be effectively improved. (2) the case attribute weight algorithm is constructed. The evaluation of tourism elements in the questionnaire and the algorithm of case attribute weight are used to determine the case attribute weight. (3) an improved trust algorithm is constructed. The trust degree is introduced into the personalized recommendation system of tourism destination based on case-based reasoning, and the case similarity algorithm with trust degree is constructed. Improve the accuracy of recommendation results. (4) the method of case-based reasoning is applied to the personalized recommendation system of tourism destination, and the related algorithms are constructed and represented by Mathematica software, and the examples are verified according to the user data. The recommendation of tourist destination and case travel notes has been preliminarily realized. Based on case-based reasoning technology, the combination of users' tourism interest and trust, this paper realizes the recommendation of personalized tourism destination and travel notes for tourists. It not only meets the personalized needs of users, but also provides users with rich tourism information. The effectiveness and accuracy of the recommendation algorithm are proved by example recommendation and empirical results. The research in this paper provides a certain reference value for personalized tourism destination recommendation system.
【學(xué)位授予單位】：海南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F592

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