【摘要】：隨著科技的進步和社會的發(fā)展,網絡經營和網上消費越來越受到廣告經營者和消費者的青睞,互聯(lián)網廣告在經濟社會領域中發(fā)揮著不可替代的作用。但是帶來巨大便利的同時也帶來了很多問題：虛假宣傳、夸大療效、保證治愈等誤導、欺騙消費者的現象。因此對互聯(lián)網廣告進行有效的監(jiān)督和監(jiān)管具有非常重要的意義。 本文面向工商監(jiān)管領域,對網絡違法文本廣告智能識別的關鍵技術進行研究與實現。不同類別的違法廣告有不同的處理方式,首先使用改進的文本分類算法對文本廣告進行分類。通過挖掘維基百科知識,向文檔中添加語義特征,改善向量空間模型的效果。然后基于擴充的維基百科語義特征,提出新的文檔相似度計算方法,通過聚類過程為置信度高的未標注樣本打上標記,以此來擴充標注樣本的數量,提高廣告文本分類效果。 在違法廣告的識別上,針對包含禁用詞類型的廣告,對傳統(tǒng)的關鍵詞匹配技術進行改進,提出基于上下文的邏輯關鍵詞匹配技術。針對包含違法描述句子型的廣告,結合廣告文本較短以及語義缺失等特點,提出基于潛在概率語義分析的違法廣告識別模型。實驗表明,本文提出的算法可以提高違法廣告識別的效果。 設計并實現了工商違法廣告智能識別系統(tǒng)。闡述了系統(tǒng)目標與總體設計,并介紹了違法廣告識別模型的訓練過程,系統(tǒng)數據的獲取以及系統(tǒng)提供給用戶的任務管理和違法報告管理平臺。
[Abstract]:With the progress of science and technology and the development of society, network management and online consumption are more and more favored by advertising operators and consumers. Internet advertising plays an irreplaceable role in the economic and social fields. But it brings a lot of problems at the same time: false propaganda, exaggerating curative effect, ensuring cure and misleading, deceiving consumers. Therefore, the effective supervision and supervision of Internet advertising has very important significance. This paper focuses on the research and realization of the key technology of intelligent identification of network illegal text advertising in the field of industrial and commercial supervision. Different types of illegal advertisements have different processing methods. Firstly, the improved text classification algorithm is used to classify the text advertisements. By mining Wikipedia knowledge, semantic features are added to the document to improve the effect of vector space model. Then, based on the extended Wikipedia semantic features, a new method of document similarity calculation is proposed. Through the clustering process, the unlabeled samples with high confidence are marked, so as to expand the number of labeled samples and improve the classification effect of advertising texts. In the recognition of illegal advertisement, the traditional keyword matching technology is improved for the advertisement containing prohibited word type, and the context-based logical keyword matching technology is proposed. Aiming at the advertisement which contains illegal description sentence pattern, this paper proposes an illegal advertisement recognition model based on latent probability semantic analysis, which combines the characteristics of short advertisement text and semantic missing. Experiments show that the algorithm proposed in this paper can improve the effect of illegal advertising recognition. Design and implement the industry and commerce illegal advertising intelligent identification system. This paper expounds the target and overall design of the system, and introduces the training process of the identification model of illegal advertisement, the acquisition of system data, and the task management and illegal report management platform provided by the system to users.
【學位授予單位】：浙江大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.1

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相關期刊論文 前1條

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本文編號：2442428