• 패션비즈니스
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• 제26권2호
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• pp.1-14
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• 2022

Recently, as the importance of mobile marketing is emphasized, the in-app advertising market, which inserts ads into applications, is growing. The purpose of this study is to verify the interaction effects of need for cognition, contextual consistency, and product involvement on advertising attitude. The experimental design of this study is a three-way mixed design of 2 (consumer need for cognition: high vs low) × 2 (contextual consistency: context match vs context mismatch) × 2 (product involvement: high vs low). The subjects of the survey were 337 men and women in their 20s and 30s Living in Seoul and Gyeonggi-do. SPSS 25.0 statistical program was used to analyze frequency analysis, reliability analysis, t-test, three-way ANOVA, and simple main effect analysis. The analysis results are as follows. First, contextual consistency of mobile fashion ads showed significant effect on advertising attitude. Second, consumer need for cognition and contextual consistency of mobile fashion ads showed significant interaction effect on advertising attitude. Third, contextual consistency of mobile fashion ads and product involvement showed significant interaction effect on advertising attitude. Finally, product involvement and consumer need for cognition showed a significant interaction effect on advertising attitude. Based on the research results, it will help fashion companies to establish effective mobile in-app advertising strategies.

• ETRI Journal
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• 제34권2호
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• pp.292-295
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• 2012

Beyond the simple keyword matching methods in contextual advertising, we propose a rich contextual matching (CM) model adopting a classification method for topic targeting and a query expansion method for semantic ad matching. This letter reports on an investigation into the empirical effects of the CM model by comparing the click-through rates (CTRs) of two practical online news advertising systems. Based on the evaluation results from over 100 million impressions, we prove that the average CTR of our proposed model outperforms that of a traditional model.

• Journal of Information Technology Applications and Management
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• 제19권4호
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• pp.115-135
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• 2012

Currently, smart signage as a new kind of advertisement media has been widely used and has had a significant effect on consumers. In this study, we examine the impact on the attitude towards smart signage advertisement based on the Ducoffe's Web advertisement model. In particular, we investigate how the advertising factors (interaction, informativeness, irritation, and entertainment) as well as the contextual factors (localization, immediacy, and personalization) have effects on the value and attitude towards smart signage advertisement. Furthermore, we examine the moderating effect of individual defensive propensity on the relationship between affecting factors and the advertising value. By analyzing 192 samples from undergraduates, we found that four out of seven factors have significant effects on the value towards smart signage. More specifically, for advertising factors, informativeness and irritation have positive effects on the advertising value. For contextual factors, on the other hand, localization and entertainment have positive effects on the value towards smart signage. Besides, we discovered that the defensive propensity moderate the relationship between localization and the advertising value.

• International Journal of Contents
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• 제7권1호
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• pp.37-44
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• 2011

This research attempts to analyze brand placement in game. Brand placement, being acclaimed as a new beneficiary model in game industry, is raising important mean of advertising. For development of game industry, the interdisciplinary study between game and advertising is indispensible. Therefore, the purpose of this study is to find creative types of brand placement in game for illuminating how advertising works in game contents. The results showed three types of brand placement in game. They are contextual type, prominent type and independent type. Contextual type is one where the brand is present within the game contents without being formally expressed: it plays a passive role. Prominent type is one where the brand is present within the game contents with being formally expressed: it plays an active role. Independent type is one where the brand is present within the game contents with being formally expressed but it is not related with the program: it plays an additional role. The research showed, among these three types, a prominent type is becoming mainstream of brand placement in game. In other words, the prominent type of brand placement is the most effective beneficial alternative in game industry.

• 지능정보연구
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• 제28권4호
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• pp.95-117
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• 2022

인터넷 기술의 발전으로 인해 다양한 미디어가 등장하면서 광고주들은 기업의 광고 전략에 적합한 미디어를 선택하는데 어려움을 경험하고 있다. 전통적인 광고 마케팅 전략을 바탕으로 광고 미디어를 선택하면 소비자의 상황 정보를 효과적으로 반영하는데 어려움이 존재한다. 이러한 상황에서 소비자의 과거 데이터를 분석하여 소비자가 필요하거나 관심 있는 정보를 바탕으로 광고주에게 맞춤형 미디어를 제공하는 추천 시스템이 필요하다. 전통적인 추천 시스템은 정량적 선호도 정보를 기반으로 추천 서비스를 제공하기 때문에 다양한 상황 정보를 반영하기 어려운 문제점이 존재한다. 본 연구에서는 딥러닝을 이용하여 소비자의 미디어 시청 시간, 거주 지역, 나이, 성별 등 상황 정보를 고려하여 광고주에게 맞춤형 미디어를 추천하는 방법론을 제안한다. 본 연구는 한국방송광고진흥공사에서 제공하는 소비자행태조사 데이터를 사용하여 추천 시스템을 구축하였다. 또한, 기존 연구에서 널리 사용되는 여러 벤치마크 모델과 비교하여 추천 성능을 검증하였다. 실험 결과, 본 연구에서 제안하는 소비자의 상황 정보를 반영한 추천 모델이 기존의 벤치마크 모델보다 높은 정확성을 나타내는 것을 확인하였다. 이 연구는 향후 광고주들이 소비자의 여러 상황 정보를 바탕으로 맞춤형 미디어 선택할 때 효과적인 의사결정을 내릴 수 있도록 도움을 주는데 기여를 할 수 있을 것으로 기대한다

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1373-1387
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• 2012

Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ~ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.

• 한국산학기술학회논문지
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• 제11권8호
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• pp.3036-3044
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• 2010

동영상 데이터 서비스가 나날이 증가함에 따라 특정 동영상 장면에 적합한 광고를 보여주거나 추가적인 정보를 제공하려는 요구가 커지고 있다. 장면에 적합한 광고를 보여주기 위하여 동영상의 영상이나 음성 정보를 직접 이용하는 방법은 현재의 기술력으로 한계가 있고, 제목, 카테고리 정보, 요약 등의 메타데이터도 계속해서 변화하는 장면의 내용을 반영하지 못한다. 본 연구는 동영상의 대본 자막에서 추출한 장면의 상황 정보를 이용하여 주어진 동영상 장면에 적합한 광고를 자동으로 부착해 주는 새로운 동영상 문맥 광고 시스템을 제안한다. 대본 자막에서 추출한 상황 정보를 광고 검색에 이용했을 때 높은 성능 향상을 확인할 수 있었고, 이를 이용하여 사용자에게 더 적합한 광고를 보여줄 수 있다.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1052-1070
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• 2017

For the autoencoder (AE) implemented as a construction component, this paper uses the method of greedy layer-by-layer pre-training without supervision to construct the stacked autoencoder (SAE) to extract the abstract features of the original input data, which is regarded as the input of the logistic regression (LR) model, after which the click-through rate (CTR) of the user to the advertisement under the contextual environment can be obtained. These experiments show that, compared with the usual logistic regression model and support vector regression model used in the field of predicting the advertising CTR in the industry, the SAE-LR model has a relatively large promotion in the AUC value. Based on the improvement of accuracy of advertising CTR prediction, the enterprises can accurately understand and have cognition for the needs of their customers, which promotes the multi-path development with high efficiency and low cost under the condition of internet finance.

• 디자인학연구
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• 제16권3호
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• pp.273-280
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• 2003

점화효과(Priming Effect)라 함은 상황효과(Contextual Effect)의 일부로서 "앞서 본 정보에 의해 뒤에 나오는 제품정보의 해석이 영향을 받게되어 제품평가가 달라지는 현상"을 말한다. 점화효과가 다른 상황효과와 구별되는 점은 앞서나온 정보가 제품의 평가에 직접적인 영향을 미치는 것이 아니라 제품정보의 해석에 영향을 미침으로 인해 제품평가에 간접적인 영향을 미친다는 점이다. 위와 같은 이론적 배경을 바탕으로 본 연구에서는 점화효과의 개념을 디자인 분야에 적극적으로 도입하여 온라인 쇼핑몰 디자인에 있어 시각적 이미지들이 제품의 선호도와 선택에 어떠한 영향력을 행사하는지 파악하였다. 디지털카메라를 대상제품으로 '가격과 '크기'에 관한 속성을 점화시킨 웹 페이지를 각각 설계하여 제품에 대한 선호도 차이를 실증분석 하였으며 그 결과 점화된 속성에 따른 제품의 선호도 차이가 유의한 것으로 판명되었다. 따라서 상업용 웹 페이지의 배경화면이 제품의 선택에 영향을 미칠 수 있는 요인이라는 점을 인지하고 이러한 점화효과를 디자인과 접목시켜 온라인상의 광고에도 적극적으로 활용할 수 있기를 기대해본다.있기를 기대해본다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2122-2140
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• 2020

Proper and precise embedding of commercial ads within Webpages requires Ad-hoc analysis and understanding of their content. By the successful implementation of this step, both publishers and advertisers gain mutual benefits through increasing their revenues on the one hand, and improving user experience on the other. In this research work, we propose a novel multi-level context-based ads serving approach through which ads will be served at generic publisher websites based on their contextual relevance. In the proposed approach, knowledge encoded in domain-specific and generic semantic repositories is exploited in order to analyze and segment Webpages into sets of contextually-relevant segments. Semantically-enhanced indexes are also constructed to index ads based on their textual descriptions provided by advertisers. A modified cosine similarity matching algorithm is employed to embed each ad from the Ads repository into one or more contextually-relevant segments. In order to validate our proposal, we have implemented a prototype of an ad serving system with two datasets that consist of (11429 ads and 93 documents) and (11000 documents and 15 ads), respectively. To demonstrate the effectiveness of the proposed techniques, we experimentally tested the proposed method and compared the produced results against five baseline metrics that can be used in the context of ad serving systems. In addition, we compared the results produced by our system with other state-of-the-art models. Findings demonstrate that the accuracy of conventional ad matching techniques has improved by exploiting the proposed semantically-enhanced context-based ad serving model.