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Survey of algorithms for assigning advertisement to search keywords

机译:为搜索关键字分配广告的算法概述

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One of the big surprises of the 21 century has been the ability of all sorts of interesting applications to support themselves through advertising, rather than subscription. While radio and television have managed to use advertising as their primary revenue source, most media, newspapers and magazines had to use a hybrid approach, combining revenue from advertising and subscriptions. By far the most profitable venue for on-line advertising has been search, and much of the effectiveness of search advertising comes from the “adwords” model of matching search queries to advertisements. This paper is to survey of algorithms for optimizing the way this assignment is done. The algorithms used are of an unusual type; they are greedy and they are “on-line” in a particular technical sense to be discussed. This paper discusses these two algorithmic issues - greediness and on-line algorithms - in general, before tackling the adwords problem. A second interesting on-line advertising problem involves selecting items to advertise at an on-line store. This problem involves “collaborative filtering,” where it try to find customers with similar behaviour in order to suggest they buy things that similar customers have bought.
机译:21世纪的一大惊喜是各种有趣的应用程序能够通过广告而非订阅来支持自己。虽然广播电视已经设法将广告作为主要收入来源,但大多数媒体,报纸和杂志都不得不采用混合方式,将广告和订阅的收入相结合。到目前为止,在线广告最赚钱的地方是搜索,搜索广告的大部分效率来自将搜索查询与广告匹配的“ adwords”模型。本文旨在研究用于优化分配方式的算法。所使用的算法属于非常规类型;他们很贪婪,并且在特定的技术意义上是“在线的”,需要讨论。在解决adwords问题之前,本文通常讨论这两个算法问题-贪婪性和在线算法。第二个有趣的在线广告问题涉及选择要在在线商店做广告的商品。这个问题涉及“协作过滤”,它试图找到行为相似的顾客,以建议他们购买相似顾客购买的商品。

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