本文選題：數(shù)據(jù)挖掘 + 搜索引擎��； 參考：《吉林大學(xué)》2012年碩士論文

【摘要】：在當(dāng)今這個(gè)信息膨脹的時(shí)代，網(wǎng)絡(luò)上的網(wǎng)頁(yè)數(shù)量是非常大的，而且仍在飛速增加。如果想要在網(wǎng)絡(luò)上得到我們所需要信息，，搜索引擎能幫助我們得到所需要的相關(guān)信息，但是搜索到的大部分信息并不是我們真正要找的，而且也需要鑒別搜索引擎提供的信息的準(zhǔn)確程度。所以在這種情況下，想要獲取信息的最好方式就是通過(guò)權(quán)威網(wǎng)頁(yè)。當(dāng)用戶使用搜索引擎在因特網(wǎng)上搜索時(shí)，權(quán)威網(wǎng)頁(yè)能直接提供給我們所需要的信息，這樣搜索結(jié)果的效率和質(zhì)量將會(huì)有很大的提高。 本篇論文研究基于社會(huì)網(wǎng)絡(luò)分析方法的網(wǎng)絡(luò)數(shù)據(jù)挖掘，包括對(duì)相關(guān)技術(shù)的研究以及從網(wǎng)絡(luò)資源中挖掘權(quán)威網(wǎng)頁(yè)。 本篇論文的目的是從網(wǎng)絡(luò)資源中發(fā)掘權(quán)威網(wǎng)頁(yè)。這樣可以幫助人們找出權(quán)威網(wǎng)頁(yè)，讓人們可以更準(zhǔn)確的得到有用信息，這里所用到的方法是通過(guò)社會(huì)網(wǎng)絡(luò)分析方法來(lái)分析相關(guān)網(wǎng)頁(yè)間的關(guān)系。 我們做了一些相關(guān)技術(shù)的研究，包含數(shù)據(jù)挖掘、數(shù)據(jù)挖掘技術(shù)、Web數(shù)據(jù)的特征、網(wǎng)絡(luò)挖掘、搜索引擎、Google、權(quán)威網(wǎng)頁(yè)、社會(huì)網(wǎng)絡(luò)分析、點(diǎn)度中心性和社會(huì)網(wǎng)絡(luò)分析軟件UCINET6等。這些理論研究的目的是為論文中做的實(shí)驗(yàn)提供理論基礎(chǔ)。 論文中實(shí)驗(yàn)所用的主要方法是點(diǎn)度中心性。點(diǎn)度中心性是一種社會(huì)網(wǎng)絡(luò)分析方法，它被用來(lái)分析網(wǎng)頁(yè)之間的關(guān)系。權(quán)威網(wǎng)頁(yè)可以被認(rèn)為是一個(gè)網(wǎng)頁(yè)，該網(wǎng)頁(yè)被其它網(wǎng)頁(yè)引用了很多次，所以這個(gè)網(wǎng)頁(yè)是值得信賴的，并且具有較高的可接受度。在本論文所做的實(shí)驗(yàn)中，通過(guò)社會(huì)網(wǎng)絡(luò)分析軟件UCINET6來(lái)計(jì)算各個(gè)網(wǎng)頁(yè)的度（Degree），從而找到幾個(gè)權(quán)威網(wǎng)頁(yè)。實(shí)驗(yàn)結(jié)果驗(yàn)證了本論文論證的觀點(diǎn)的合理性，通過(guò)論文提出的原理和方法，可以找到適當(dāng)?shù)臋?quán)威網(wǎng)頁(yè)。另外有一些擴(kuò)展的工作可以在本論文的基礎(chǔ)上今后逐步完善，比如相關(guān)性計(jì)算、移除重復(fù)鏈接、擴(kuò)展數(shù)據(jù)集等。
[Abstract]:In this era of information inflation, the number of web pages on the network is very large, and is still growing rapidly. If we want to get the information we need on the Internet, search engines can help us get the relevant information we need, but most of the information we search is not really what we are looking for. It is also necessary to identify the accuracy of the information provided by the search engine. So in this case, the best way to get information is through authoritative web pages. When users use search engines to search on the Internet, authoritative web pages can directly provide the information we need, so the efficiency and quality of search results will be greatly improved. This paper studies the network data mining based on the social network analysis method, including the research of related technologies and the mining of authoritative web pages from the network resources. The purpose of this paper is to explore the authoritative web pages from the network resources. This can help people to find authoritative web pages, so that people can get useful information more accurately. The method used here is to analyze the relationship between relevant web pages through the method of social network analysis. We have done some research on related technologies, including data mining, data mining technology and web data features, web mining, search engine Google, authoritative web pages, social network analysis, point centrality and social network analysis software UCINET6. The purpose of these theoretical studies is to provide a theoretical basis for the experiments in this paper. The main method used in the experiment is pointwise centrality. Point centrality is a social network analysis method, which is used to analyze the relationship between web pages. An authoritative page can be regarded as a page that has been quoted many times by other pages, so the page is trustworthy and has a high acceptability. In the experiment of this paper, the social network analysis software UCINET6 is used to calculate the degree of each web page, and several authoritative web pages are found. The experimental results verify the rationality of the argument in this paper. Through the principle and method proposed in the paper, we can find the appropriate authoritative web page. In addition, some extended work can be improved gradually on the basis of this paper, such as correlation calculation, removing duplicate links, extending data sets and so on.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP311.13

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 高明;關(guān)聯(lián)規(guī)則挖掘算法的研究及其應(yīng)用[D];山東師范大學(xué);2006年

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