發(fā)布時(shí)間：2018-08-10 19:32

【摘要】：隨著集群式供應(yīng)鏈的發(fā)展,企業(yè)節(jié)約成本和提高效率的方法不再局限于企業(yè)自身的能力和資源,單供應(yīng)鏈上的核心企業(yè)不僅需要整合鏈條上下游的資源,還需要關(guān)注不同單供應(yīng)鏈之間跨鏈協(xié)作的競合關(guān)系,以提高鏈條之間信息的交流和反饋市場的速度。配件供應(yīng)是汽車產(chǎn)業(yè)鏈中的重要一環(huán),不同用戶角色均有掌握配件相關(guān)信息的需求,本文通過構(gòu)建配件跨鏈商品庫和實(shí)現(xiàn)搜索系統(tǒng)來解決現(xiàn)有配件管理系統(tǒng)中存在的問題。首先根據(jù)平臺(tái)各企業(yè)數(shù)據(jù)庫的物理結(jié)構(gòu)特點(diǎn)設(shè)計(jì)了配件跨鏈商品庫,并利用針對需要提高響應(yīng)速度的配件庫優(yōu)化問題,對物化視圖技術(shù)進(jìn)行了研究,根據(jù)常用的統(tǒng)計(jì)查詢語句,運(yùn)用譜系聚集方法歸納查詢集合,利用考慮了查詢成本和維護(hù)成本的物化權(quán)重公式,選擇合適的查詢語句進(jìn)行物化,用定時(shí)刷新物化視圖保證了數(shù)據(jù)的準(zhǔn)確性和有效性。針對用戶搜索需求,搜集信息建立配件常用詞匯表,采用基于同義詞詞林的詞語相似度計(jì)算方法,對用戶輸入的關(guān)鍵詞進(jìn)行擴(kuò)展,并運(yùn)用基于全文檢索和模式圖的關(guān)系數(shù)據(jù)庫關(guān)鍵詞搜索方法,先通過全文索引找到包含用戶輸入關(guān)鍵詞的元組集,再用關(guān)鍵詞元組集擴(kuò)展配件庫模式圖得到擴(kuò)展模式圖,并運(yùn)用改進(jìn)后的候選網(wǎng)絡(luò)生成算法,融合詞語相似度,提出對元組連接樹的排序機(jī)制,將元組連接樹按順序轉(zhuǎn)化為SQL語句,交由數(shù)據(jù)庫執(zhí)行,最終將結(jié)果以二維表的形式展示給用戶。同時(shí)對改進(jìn)后的候選網(wǎng)絡(luò)生成算法和原算法進(jìn)行實(shí)驗(yàn),從查全率、查準(zhǔn)率和F1值三方面對算法效果進(jìn)行比較分析。本文以企業(yè)配件庫中配件銷售業(yè)務(wù)數(shù)據(jù)的分析程作為示例,利用譜系的聚集過程圖對常用復(fù)雜查詢語句進(jìn)行歸納,創(chuàng)建了提高配件庫響應(yīng)速度的物化視圖。系統(tǒng)使用SQLserver數(shù)據(jù)庫和C#語言進(jìn)行開發(fā),采用基于B/S模式的三層架構(gòu),設(shè)計(jì)實(shí)現(xiàn)了基于產(chǎn)業(yè)鏈協(xié)同平臺(tái)的配件搜索系統(tǒng)。
[Abstract]:With the development of cluster supply chain, the methods of saving cost and improving efficiency are no longer limited to the ability and resources of the enterprise itself. The core enterprises in the single supply chain need not only integrate the upstream and downstream resources of the chain. It is also necessary to pay attention to the competition and cooperation between different single supply chains in order to improve the speed of information exchange and feedback market. Spare parts supply is an important part in automobile industry chain. Different user roles have the need to master the relevant information of accessories. This paper solves the problems existing in the existing parts management system by constructing the cross-chain commodity library of accessories and realizing the search system. First of all, according to the physical structure of each enterprise database of the platform, the cross-chain commodity library of accessories is designed, and the materialized view technology is studied according to the optimization problem of spare parts library which needs to improve the response speed, and according to the commonly used statistical query statements, The method of pedigree aggregation is used to induce the query set and the materialized weight formula considering the query cost and maintenance cost is used to materialize the query statements. The accuracy and validity of the data are guaranteed by refreshing the materialized view periodically. According to the users' search needs, the common vocabulary of accessories is established by collecting information, and the words similarity calculation method based on synonym forest is adopted to expand the keywords input by users. Using the search method of relational database key words based on full-text retrieval and schema graph, we first find the tuple set containing user input keywords through full-text index, and then use keyword tuple set extension component library schema diagram to get the extended schema map. Using the improved candidate network generation algorithm, combining the word similarity, the sorting mechanism of the tuple join tree is proposed, and the tuple join tree is transformed into SQL statements in order, which is executed by the database. Finally, the results are presented to the user in the form of a two-dimensional table. At the same time, the improved candidate network generation algorithm and the original algorithm are experimented, and the results of the algorithm are compared and analyzed from three aspects: recall rate, precision rate and F1 value. This paper takes the analysis process of spare parts sales business data in the enterprise accessories library as an example, sums up the common complex query statements by using the aggregate process diagram of the pedigree, and creates a materialized view to improve the response speed of the accessories library. The system uses SQLserver database and C # language to develop, adopts the three-tier architecture based on B / S mode, designs and implements the accessory search system based on the industrial chain cooperation platform.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.3;F274

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 葛唯益;宗士強(qiáng);尹文科;;一種基于預(yù)先索引的關(guān)系數(shù)據(jù)庫關(guān)鍵詞搜索方法[J];計(jì)算機(jī)科學(xué);2016年04期

2 田久樂;趙蔚;;基于同義詞詞林的詞語相似度計(jì)算方法[J];吉林大學(xué)學(xué)報(bào)(信息科學(xué)版);2010年06期

3 林子雨;楊冬青;王騰蛟;張東站;;基于關(guān)系數(shù)據(jù)庫的關(guān)鍵詞查詢[J];軟件學(xué)報(bào);2010年10期

4 王璇;符卓;符瑛;吳曉玲;占洪波;;集群式供應(yīng)鏈競合博弈研究[J];物流工程與管理;2009年02期

5 付琦;孫冉;;集群式供應(yīng)鏈自組織演進(jìn)中的競合關(guān)系研究[J];商場現(xiàn)代化;2008年20期

6 徐海濤,鄭寧;數(shù)據(jù)倉庫中物化視圖選擇的一種混合算法[J];計(jì)算機(jī)工程與設(shè)計(jì);2005年10期

7 文繼軍,王珊;SEEKER:基于關(guān)鍵詞的關(guān)系數(shù)據(jù)庫信息檢索[J];軟件學(xué)報(bào);2005年07期

8 李嵐;中國IT集群發(fā)展研究[J];中外管理導(dǎo)報(bào);2002年10期

9 楊建梅,馮廣森;東莞臺(tái)資IT企業(yè)集群產(chǎn)業(yè)結(jié)構(gòu)剖析[J];中國工業(yè)經(jīng)濟(jì);2002年08期

相關(guān)博士學(xué)位論文 前1條

1 黎繼子;集群式供應(yīng)鏈及其管理研究[D];華中農(nóng)業(yè)大學(xué);2006年

相關(guān)碩士學(xué)位論文 前2條

1 賀琳;集群式供應(yīng)鏈中跨鏈間的庫存策略研究[D];清華大學(xué);2011年

2 王沖;集群式供應(yīng)鏈跨鏈庫存協(xié)作模型研究[D];大連海事大學(xué);2008年

，

本文編號：2175985