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基于社交網(wǎng)絡(luò)模型的智能個人知識庫構(gòu)建

發(fā)布時間:2018-10-31 19:39
【摘要】:近些年來,人工智能技術(shù)快速發(fā)展,極大地促進了技術(shù)創(chuàng)新,以及推動了人類社會的發(fā)展。智能助手是隨著人工智能的發(fā)展而興起的一種新型的行動代理軟件,受到了學術(shù)界和工業(yè)界廣泛的關(guān)注。用戶的興趣具有動態(tài)性和易變性,為了提供智能化、個性化的服務(wù),智能助手首要解決的兩個問題是如何學習和適應(yīng)用戶興趣。為了有效解決這兩個問題,本文提出一種通過構(gòu)建智能個人知識庫來學習和適應(yīng)用戶興趣的方案。本文的主要的研究內(nèi)容包括以下幾點:第一,深度調(diào)研智能助手的發(fā)展現(xiàn)狀與研究熱點,分析智能助手未來的發(fā)展趨勢。深入了解開源智能助手項目Lucida及其工作原理。第二,分析維基百科的知識網(wǎng)絡(luò)結(jié)構(gòu),并以其作為基礎(chǔ)數(shù)據(jù)源,構(gòu)建語義實體網(wǎng)絡(luò)。以該語義實體網(wǎng)絡(luò)作為通用知識庫,提出基于社交網(wǎng)絡(luò)模型構(gòu)建智能個人知識庫的方法。首先,提出面向用戶興趣的個人知識庫的概念,并設(shè)計個人知識庫的結(jié)構(gòu)模型與構(gòu)建流程;其次,描述用戶興趣量化建模方法;然后,提出基于語義實體網(wǎng)絡(luò)的結(jié)構(gòu)特征及文本特征的實體綜合表征模型,并利用改進的基于內(nèi)容的協(xié)同過濾算法和排序?qū)W習算法進行用戶興趣知識挖掘;最后,設(shè)計了個人知識庫的自適應(yīng)演化算法。第三,探索個人知識庫在問答系統(tǒng)中的應(yīng)用,分別從準確性和時效性兩個方面,評測本課題構(gòu)建的個人知識庫原型。發(fā)現(xiàn)本課題所構(gòu)建的個人知識庫在一定程度上可以幫助理解用戶的查詢意圖,提高問答的精確性;并且可以大大減少智能問答系統(tǒng)的響應(yīng)時間,提高問答的時效性。驗證了本課題提出的基于社交網(wǎng)絡(luò)模型構(gòu)建智能個人知識庫方法的有效性。
[Abstract]:In recent years, the rapid development of artificial intelligence technology has greatly promoted technological innovation and the development of human society. Intelligent assistant is a new kind of mobile agent software, which is developed with the development of artificial intelligence. The interest of users is dynamic and changeable. In order to provide intelligent and personalized services, the first two problems solved by intelligent assistants are how to learn and adapt to the interests of users. In order to solve these two problems effectively, this paper proposes a scheme to learn and adapt to the interests of users by constructing an intelligent personal knowledge base. The main research contents of this paper are as follows: first, the development status and research focus of intelligent assistant in depth investigation, and analyze the development trend of intelligent assistant in the future. Learn more about open source intelligent helper project Lucida and how it works. Secondly, the knowledge network structure of Wikipedia is analyzed and used as the basic data source to construct semantic entity network. Taking the semantic entity network as a general knowledge base, a method of constructing intelligent personal knowledge base based on social network model is proposed. Firstly, the concept of personal knowledge base oriented to user interest is proposed, and the structure model and construction flow of personal knowledge base are designed, secondly, the quantitative modeling method of user interest is described. Then, an entity synthesis representation model based on semantic entity network and text feature is proposed, and the improved content-based collaborative filtering algorithm and ranking learning algorithm are used to mine user's interest knowledge. Finally, an adaptive evolutionary algorithm of personal knowledge base is designed. Thirdly, it explores the application of personal knowledge base in Q & A system, and evaluates the prototype of personal knowledge base from two aspects of accuracy and timeliness. It is found that the personal knowledge base constructed in this paper can help to understand the user's query intention to a certain extent, improve the accuracy of the question and answer, and greatly reduce the response time of the intelligent question answering system and improve the timeliness of the question and answer system. The validity of the intelligent personal knowledge base method based on social network model is verified.
【學位授予單位】:南昌大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TP18

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