機(jī)票票價預(yù)測系統(tǒng)設(shè)計與實現(xiàn)
[Abstract]:With the rapid development of society, people's living standard is improving constantly. In people's daily business activities or related daily travel, airplane travel has become the first choice for more and more users because of its convenient speed. At the same time, with the rapid development of Internet services, people can easily book to travel air tickets from the Internet whenever and wherever they are connected. Many airline passengers may think that the earlier the plane ticket, the higher the fare concession. Is that really the case?. In fact, in many cases, perhaps the closer the plane takes off, the lower the ticket price. In order to help customers to book the required flights at the lowest price in their daily life, we have developed the ticket prediction system. The rationale for the system is that there are many websites that currently offer airline reservations, and nearly all travel-related websites offer the service, except for the airline's official website. Well, through the web crawler, we regularly obtain the relevant ticket prices from these websites, and make a statistical analysis of the price of these tickets, through such a huge amount of data and the price situation of the previous tickets, To predict the relevant ticket prices, and then return them to the user to help them choose when to buy the ticket price. Since we only focus on a specific area of ticket pricing, general search engines such as Baidu and Google are not good enough to meet our requirements. We need to be more professional. More targeted and accurate search scheme, this is the vertical search technology. At the same time, because of the huge amount of data designed by our system, we use the current mainstream HBase distributed database as the backstage support database to provide us with data processing functions. Before the development of the system, as the main developer of the system, the system needs to meet the needs of users and the final need to have the necessary functions for a system analysis, with clear system goals. Then the system architecture design, functional structure design, database design, detailed design and so on. The system uses Netbeans integrated development environment, Java as the development language, and the B / S architecture. The functions of each module are coded step by step. Through the realization of this air ticket prediction system, the author also has a further understanding and understanding of big data's handling mode. Through practice, the former goal has been realized. It satisfies the original intention of the development and can provide help for the booking time after the user. It is of great practical significance.
【學(xué)位授予單位】:大連理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:TP311.52
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 張斌;周爾寧;;基于Nutch的分布式紡織垂直搜索引擎研究[J];電腦知識與技術(shù);2009年21期
2 楊麗萍;;網(wǎng)頁正文提取技術(shù)的分析與研究[J];計算機(jī)光盤軟件與應(yīng)用;2012年22期
3 張健沛,劉洋,楊靜,代坤;搜索引擎結(jié)果聚類算法研究[J];計算機(jī)工程;2004年05期
4 強(qiáng)士卿;程光;;基于流的哈希函數(shù)比較分析研究[J];南京師范大學(xué)學(xué)報(工程技術(shù)版);2008年04期
5 嚴(yán)良達(dá);;基于Lucene搜索引擎的設(shè)計與實現(xiàn)[J];寧波職業(yè)技術(shù)學(xué)院學(xué)報;2009年02期
6 李曉明,鳳旺森;兩種對URL的散列效果很好的函數(shù)[J];軟件學(xué)報;2004年02期
7 林子雨;賴永炫;林琛;謝怡;鄒權(quán);;云數(shù)據(jù)庫研究[J];軟件學(xué)報;2012年05期
8 丁振國;吳寶貴;辛友強(qiáng);;基于Bloom Filter的大規(guī)模網(wǎng)頁去重策略研究[J];現(xiàn)代圖書情報技術(shù);2008年03期
9 孫皓;董守斌;;基于標(biāo)簽密度的自適應(yīng)正文提取方法[J];鄭州大學(xué)學(xué)報(理學(xué)版);2009年01期
10 張俊;李魯群;周熔;;基于Lucene的搜索引擎的研究與應(yīng)用[J];計算機(jī)技術(shù)與發(fā)展;2013年06期
,本文編號:2224154
本文鏈接:http://sikaile.net/kejilunwen/sousuoyinqinglunwen/2224154.html