本文關(guān)鍵詞： 關(guān)鍵詞廣告 預(yù)算分配策略 模糊優(yōu)化 自適應(yīng)變異粒子群算法差分進(jìn)化算法　出處：《廣西大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：關(guān)鍵詞廣告是一種在線營(yíng)銷方式,因操作簡(jiǎn)單、預(yù)算可控以及廣告效益較高等優(yōu)點(diǎn)而得到了廣泛的推廣,迅速成為了廣告商推廣產(chǎn)品、投放廣告的主要營(yíng)銷手段之一,同時(shí)也是近來(lái)國(guó)內(nèi)外學(xué)者研究的熱點(diǎn)之一.本文在已有研究的基礎(chǔ)上,針對(duì)廣告商投放廣告時(shí)常選擇的三個(gè)組合:單搜索引擎多關(guān)鍵詞、多搜索引擎單關(guān)鍵詞以及多搜索引擎多關(guān)鍵詞,展開(kāi)了系列的關(guān)鍵詞廣告預(yù)算分配策略的研究.(一)研究了單搜索引擎多關(guān)鍵詞多階段廣告預(yù)算分配策略,在總預(yù)算限制下建立了以最大化廣告收益、最小化無(wú)效點(diǎn)擊為雙目標(biāo)的單引擎多關(guān)鍵詞多階段的廣告預(yù)算分配模型,給出了模糊優(yōu)化雙目標(biāo)預(yù)算分配模型的解法.實(shí)例驗(yàn)證了該模型的有效性與合理性.(二)研究了多搜索引擎單關(guān)鍵詞多階段廣告預(yù)算分配策略,以單位收益所花費(fèi)的競(jìng)價(jià)成本最小為單個(gè)搜索引擎的目標(biāo)函數(shù),構(gòu)建了多搜索引擎多階段的廣告預(yù)算分配優(yōu)化模型.針對(duì)模型易于陷入局部最優(yōu)的缺陷,研究了用于求解該模型的自適應(yīng)變異粒子群算法,探討了在多個(gè)搜索引擎上競(jìng)價(jià)時(shí)的動(dòng)態(tài)預(yù)算分配策略.實(shí)驗(yàn)表明,該方法具有更好的全局收斂性和實(shí)時(shí)性,有效地提高了廣告商的廣告收益.(三)研究了多搜索引擎多關(guān)鍵詞多階段廣告預(yù)算分配策略,以每收益花費(fèi)的成本和每預(yù)算產(chǎn)生的無(wú)效點(diǎn)擊最小為目標(biāo),建立多搜索引擎多關(guān)鍵詞多階段的預(yù)算分配模型,采用了搜索能力較強(qiáng)的改進(jìn)差分進(jìn)化算法(IDE)對(duì)模型進(jìn)行求解.實(shí)例驗(yàn)證,該算法具有較強(qiáng)的搜索能力以及較快的收斂速度.
[Abstract]:Keyword advertising is an online marketing method, which has been widely promoted because of its advantages of simple operation, controllable budget and high advertising efficiency. It has quickly become one of the main marketing means for advertisers to promote products and place advertisements. At the same time, it is also one of the hot spots of scholars at home and abroad recently. Based on the existing research, this paper focuses on the three combinations that advertisers often choose: single search engine and multiple keywords. Multi-search engine single keyword and multi-search engine multi-keyword, launched a series of keyword advertising budget allocation strategy. (1) single search engine multi-keyword multi-stage advertising budget allocation strategy, An ad budget allocation model with single engine, multi-keyword and multi-stage, which maximizes advertising revenue and minimizes invalid clicks, is established under the limit of total budget. In this paper, the solution of fuzzy optimization model for double objective budget allocation is given. The effectiveness and rationality of the model are verified by an example. (2) the multi-search engine single keyword and multi-stage advertising budget allocation strategy is studied. Taking the minimum bidding cost per unit income as the objective function of a single search engine, a multi-search engine multi-stage advertising budget allocation optimization model is constructed. The adaptive mutation particle swarm optimization algorithm for solving the model is studied, and the dynamic budget allocation strategy for bidding on multiple search engines is discussed. The experimental results show that the proposed method has better global convergence and real-time performance. Effectively improve the advertising revenue of advertisers. (3) study the multi-search engine multi-keyword multi-stage advertising budget allocation strategy, aiming at the cost per revenue and the minimum of invalid clicks per budget. A multi-search engine multi-keyword multi-stage budget allocation model is established and the improved differential evolution algorithm (IDE) is used to solve the model. The example shows that the algorithm has strong searching ability and fast convergence speed.
【學(xué)位授予單位】：廣西大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.3;TP18

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