本文選題：眾包服務(wù) + 模糊需求��； 參考：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：近年來(lái)眾包服務(wù)市場(chǎng)持續(xù)受到人們的關(guān)注,發(fā)展如火如荼,其發(fā)展模式也有了一定的變化。從傳統(tǒng)的以服務(wù)需求方為主導(dǎo)的市場(chǎng)模式演變?yōu)橐怨┣箅p方各自為主導(dǎo)的服務(wù)市場(chǎng)模式。本文以服務(wù)供求方為主導(dǎo)的新型眾包市場(chǎng)為研究背景,分析用戶的模糊需求,挖掘用戶的需求模式,并根據(jù)用戶的需求為用戶匹配相應(yīng)的服務(wù),對(duì)眾包服務(wù)市場(chǎng)中的服務(wù)進(jìn)行衡量,縮小用戶搜索的可選服務(wù)集,解決新型眾包服務(wù)市場(chǎng)中供求雙方信息不平衡以及需求匹配困難的問(wèn)題,為下一步的精確推薦提供可靠地基礎(chǔ),具有重要意義。本文構(gòu)建了表達(dá)服務(wù)供求關(guān)系的需求圖譜。需求圖譜是通過(guò)分析眾包服務(wù)市場(chǎng)中的交易數(shù)據(jù),提取市場(chǎng)中的用戶,服務(wù)提供商和服務(wù)以及之間的關(guān)系來(lái)構(gòu)建的,為面向用戶的需求查詢以及服務(wù)的匹配提供了研究基礎(chǔ)。在眾包服務(wù)市場(chǎng)中,用戶對(duì)于服務(wù)的需求多是模糊的文字描述,傳統(tǒng)的搜索僅能做到字符串的匹配無(wú)法真正了解用戶的需求。本文提出了用戶模糊需求的處理方法,分步采用局部敏感哈希算法、關(guān)鍵字匹配以及引導(dǎo)式問(wèn)答方法來(lái)明確分析用戶的多重查詢需求,并將其轉(zhuǎn)化為查詢子圖在構(gòu)建的需求圖譜上進(jìn)行搜索,使得用戶的多重查詢需求能夠一次性滿足。文章提出了GSR4FR子圖匹配算法和組合服務(wù)的篩選規(guī)則算法,并對(duì)服務(wù)的質(zhì)量進(jìn)行了統(tǒng)一的衡量。其中GSR4FR算法同改進(jìn)前的Nema算法相比,搜索時(shí)間有了大幅度提升,平均服務(wù)搜索質(zhì)量結(jié)果較好。組合服務(wù)篩選規(guī)則算法則是根據(jù)用戶的歷史購(gòu)買行為信息的挖掘得到的,經(jīng)實(shí)驗(yàn)結(jié)果證明行之有效。在新型的眾包服務(wù)市場(chǎng)中,用戶的需求是模糊而復(fù)雜的,因?yàn)槿祟惖恼Z(yǔ)言本身具有一定的模糊性,在此基礎(chǔ)上進(jìn)行的需求匹配的過(guò)程也是較為困難的。本文嘗試著采用處理用戶模糊需求和構(gòu)建需求圖譜的方法來(lái)進(jìn)行用戶的需求匹配,并提出了相對(duì)應(yīng)的子圖匹配算法來(lái)匹配合適的服務(wù)以及組合服務(wù)篩選規(guī)則算法來(lái)篩選組合服務(wù)的優(yōu)先級(jí)別,在新的領(lǐng)域問(wèn)題上融合了不同的解決方法,并取得了一定的成果。最后本文基于課題所研究的內(nèi)容開(kāi)發(fā)了基于用戶需求圖譜的服務(wù)匹配插件工具,以圖形化界面的形式驗(yàn)證了研究?jī)?nèi)容。
[Abstract]:In recent years, the crowdsourcing service market has been paid more and more attention. From the traditional service demand-oriented market model to the service market model led by both supply and demand. Based on the research background of the new crowdsourcing market, which is dominated by service supply and demand, this paper analyzes the fuzzy needs of users, excavates the demand patterns of users, and matches the corresponding services for users according to the needs of users. To measure the services in the crowdsourcing service market, to reduce the optional service set searched by users, to solve the problems of the imbalance of information between the supply and demand sides and the difficulty of matching demand in the new crowdsourcing service market. It is of great significance to provide a reliable basis for the next accurate recommendation. This paper constructs a demand map to express the relationship between supply and demand of services. The requirement map is constructed by analyzing the transaction data in the crowdsourcing service market and extracting the relationship among the users, service providers and services in the market. It provides a research basis for the user-oriented requirement query and service matching. In the crowdsourcing service market, the user's demand for the service is mostly fuzzy text description, the traditional search can only achieve string matching can not really understand the user's needs. In this paper, we propose a method to deal with the user's fuzzy requirements. The local sensitive hashing algorithm, keyword matching and guided question answering method are used to analyze the multiple query requirements of the user step by step. The query subgraph is transformed into a query subgraph which can be searched on the constructed requirement graph, so that the multiple query requirements of the user can be satisfied at one time. In this paper, a GSR4FR subgraph matching algorithm and a selection rule algorithm for composite services are proposed, and the quality of service is evaluated uniformly. Compared with the improved Nema algorithm, the search time of GSR4FR algorithm is greatly improved, and the average quality of service search results are better. The algorithm of composite service filtering rule is based on the user's historical purchase behavior information mining, and the experimental results show that it is effective. In the new crowdsourcing service market, the needs of users are fuzzy and complex, because the human language itself has a certain degree of fuzziness, and the process of requirement matching on this basis is also more difficult. In this paper, we try to use the method of dealing with the user's fuzzy requirements and constructing the requirement map to match the user's requirements. The corresponding subgraph matching algorithm is proposed to match the appropriate service and the composite service filter rule algorithm to filter the priority level of composite service. Different solutions are combined in the new domain problem and some achievements have been achieved. Finally, a service matching plug-in tool based on user requirement graph is developed based on the content studied in this paper, and the research content is verified in the form of graphical interface.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.3

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本文編號(hào)：1859505