本文選題：群體決策　切入點(diǎn)：文本情感分析　出處：《湖南科技大學(xué)》2015年碩士論文

【摘要】：決策是人們在生活中進(jìn)行政治、經(jīng)濟(jì)活動遇到的在多個(gè)可行方案中選擇一個(gè)最合理的方案的行為。由于個(gè)人掌握信息的不全面性,僅依靠個(gè)人的智慧進(jìn)行決策是不合理的。群體決策依靠群體的智慧對問題進(jìn)行決策,增加了決策結(jié)果的可靠性,信服力以及可執(zhí)行性。群體決策支持系統(tǒng)(GDSS)是在群體決策過程中為決策提供支持的系統(tǒng)。智能決策支持系統(tǒng)結(jié)合了人工智能(Artificial Intelligence)與決策支持系統(tǒng)(DSS),使DSS能充分運(yùn)用人類的智慧,通過邏輯推理來幫助解決復(fù)雜的決策問題。由于機(jī)器學(xué)習(xí),數(shù)據(jù)挖掘,自然語言處理等人工智能技術(shù)的研究不斷深入,更多的智能化方法被應(yīng)用到?jīng)Q策支持系統(tǒng)中,決策支持系統(tǒng)的智能化程度得到明顯提高。雖然智能決策支持系統(tǒng)的研究和應(yīng)用取得較大進(jìn)展,但仍然存在一些問題,其中包括:1.群體決策過程中決策者的觀點(diǎn)一般是基于自然語言的,不便于量化和計(jì)算;2.群體決策的過程一般沒有可視化展示;3.對方案的支持或者反對力度的計(jì)算不夠科學(xué);4.較少考慮如何對群體決策過程中觀點(diǎn)的分歧和矛盾進(jìn)行消除。為此,我們需要對群體決策者的決策意見量化、決策過程可視化、計(jì)算方案支持或反對力度智能化、以及消除決策者的意見分岐和矛盾進(jìn)行研究。本文在詳細(xì)分析和研究目前智能群體決策支持系統(tǒng)的研究現(xiàn)狀以及存在的問題基礎(chǔ)上,主要做了以下工作:1.針對智能群體決策中決策者的觀點(diǎn)不能智能的量化問題,本文提出了利用自然語言處理等技術(shù)對決策者觀點(diǎn)進(jìn)行智能分析,推理出決策者的意見。2.針對智能群體決策中決策者的意見量化不夠精確的問題,本文運(yùn)用了模糊推理對群體決策者的意見進(jìn)行精確的量化,并且考慮了決策者之間的親密和疏遠(yuǎn)關(guān)系以及決策者的權(quán)重值,使決策的結(jié)果更加準(zhǔn)確同時(shí)增加了決策結(jié)果的可信度。3.利用百度的Echarts對方案的決策過程等進(jìn)行可視化展示。利用自然語言處理決策者的觀點(diǎn)不僅能使決策者的文本觀點(diǎn)進(jìn)行量化計(jì)算,而且提高了決策的智能化程度。文中采用的模糊推理對決策者的意見進(jìn)行量化計(jì)算,提高了方案支持或者反對力度的量化精度。在計(jì)算決策者意見時(shí)考慮了決策者的權(quán)重,更加符合決策的實(shí)際。讓決策者間親密、疏遠(yuǎn)關(guān)系參與決策方案的支持或反對力度計(jì)算,極大的減少了決策結(jié)果受決策者情感因素的影響可能性�？梢暬瘺Q策的整個(gè)過程可以使決策者們更加清楚地了解決策結(jié)果產(chǎn)生的整個(gè)過程。
[Abstract]:Decision making is the behavior that people encounter in political and economic activities in life to choose one of the most reasonable options in a number of feasible schemes. Because of the incompleteness of personal information, It is unreasonable to rely only on the wisdom of the individual to make decisions. Group decision making depends on the wisdom of the group to make decisions on problems, which increases the reliability of the decision results. The Group decision support system (GDSs) is a system that provides support for decision making in the process of group decision making. Intelligent decision support system combines artificial Intelligence with decision support system, which enables DSS to make full use of human intelligence. The research of artificial intelligence technology such as machine learning, data mining, natural language processing and other artificial intelligence technology has been deepened, more intelligent methods have been applied to decision support system, and more and more intelligent methods are applied to decision support system, because of the deep research of artificial intelligence technology, such as machine learning, data mining and natural language processing. Although the research and application of intelligent decision support system has made great progress, there are still some problems. This includes: 1.The views of decision makers in the group decision-making process are generally based on natural language. It is not easy to quantify and calculate. 2. The process of group decision making is generally not visualized. The calculation of support or opposition to the scheme is not scientific enough. 4. Less consideration is given to how to eliminate the differences and contradictions in the process of group decision making. We need to quantify the decision-making opinions of the group decision makers, visualize the decision-making process, and intelligently support or oppose the calculation scheme. On the basis of detailed analysis and research on the current research status and existing problems of intelligent group decision support system, The main work is as follows: 1. Aiming at the problem that the decision maker's viewpoint can not be intelligent in the intelligent group decision making, this paper puts forward the intelligent analysis of the decision maker's viewpoint by using natural language processing and other technologies. To solve the problem that the quantification of the opinion of the decision maker in intelligent group decision-making is not accurate enough, this paper uses fuzzy reasoning to quantify the opinion of the group decision maker accurately. And taking into account the closeness and alienation of decision makers and the weight of decision makers, Making the decision results more accurate and increasing the credibility of the decision results .3.Using Baidu's Echarts to visualize the decision-making process and so on. Using natural language to deal with the views of the decision makers can not only make the text of the decision makers. This view carries out quantitative calculations, The fuzzy reasoning is used to quantify the opinion of the decision maker, and the quantification accuracy of the program support or opposition is improved. The weight of the decision maker is taken into account in the calculation of the decision maker's opinion, and the weight of the decision maker is taken into account in the calculation of the decision maker's opinion. More in line with the realities of decision making. Involve decision makers in the calculation of support or opposition to decision-making programs by closeness, estrangement, It greatly reduces the possibility that the decision results are influenced by the decision makers' emotional factors, and the whole process of visual decision making can make the decision makers understand the whole process of the decision results more clearly.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP311.52

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 魏慧玲;文本情感分析在產(chǎn)品評論中的應(yīng)用研究[D];北京交通大學(xué);2014年

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本文編號：1687297