相关论文: Forecasting Granular Audience Size for Online Adve…

Streaming process mining deals with the real-time analysis of event streams. A common approach for it is to adopt windowing mechanisms that select event data from a stream for subsequent analysis. However, the size of these windows denotes…

In various web applications like targeted advertising and recommender systems, the available categorical features (e.g., product type) are often of great importance but sparse. As a widely adopted solution, models based on Factorization…

We want to find the optimal strategy for displaying advertisements e.g. banners, videos, in given locations at given times under some realistic dynamic constraints. Our primary goal is to maximize the expected revenue in a given period of…

We present a data-driven algorithm that advertisers can use to automate their digital ad-campaigns at online publishers. The algorithm enables the advertiser to search across available target audiences and ad-media to find the best possible…

With the advent of faster internet services and growth of multimedia content, we observe a massive growth in the number of online videos. The users generate these video contents at an unprecedented rate, owing to the use of smart-phones and…

The rapid increase in the number of online videos provides the marketing and advertising agents ample opportunities to reach out to their audience. One of the most widely used strategies is product placement, or embedded marketing, wherein…

We present a vertical introduction to campaign optimization; that is, the ability to predict the user response to an ad campaign without any users' profiles on average and for each exposed ad. In practice, we present an approach to build a…

In an increasingly customer-centric business environment, effective communication between marketing and senior management is crucial for success. With the rise of globalization and increased competition, utilizing new data mining techniques…

Keyword extraction is a foundational task in natural language processing, underpinning countless real-world applications. One of these is contextual advertising, where keywords help predict the topical congruence between ads and their…

In online advertising markets, budget-constrained advertisers acquire ad placements through repeated bidding in auctions on various platforms. We present a strategy for bidding optimally in a set of auctions that may or may not be…

The last decade has witnessed a tremendous growth in the volume as well as the diversity of multimedia content generated by a multitude of sources (news agencies, social media, etc.). Faced with a variety of content choices, consumers are…

The competition for the attention of users is a central element of the Internet. Crucial issues are the origin and predictability of big hits, the few items that capture a big portion of the total attention. We address these issues…

Personalization is pervasive in the online space as it leads to higher efficiency and revenue by allowing the most relevant content to be served to each user. However, recent studies suggest that personalization methods can propagate…

In this paper, we study the problem of allocating ads to users through the viral-marketing lens. Advertisers approach the host with a budget in return for the marketing campaign service provided by the host. We show that allocation that…

The many metrics employed for the evaluation of search engine results have not themselves been conclusively evaluated. We propose a new measure for a metric's ability to identify user preference of result lists. Using this measure, we…

Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company…

In the research field of big data, one of important issues is how to recover the sequentially changing sets of true features when the data sets arrive sequentially. The paper presents a general framework for online updating variable…

In many learning systems, such as activity recognition systems, as new data collection methods continue to emerge in various dynamic environmental applications, the attributes of instances accumulate incrementally, with data being stored in…

A success factor for modern companies in the age of Digital Marketing is to understand how customers think and behave based on their online shopping patterns. While the conventional method of gathering consumer insights through…

Online conformal prediction has demonstrated its capability to construct a prediction set for each incoming data point that covers the true label with a predetermined probability. To cope with potential distribution shift, multi-model…