With the rapid development of Internet, recommendation system is becoming more and important in people’s life. Click-through rate prediction a crucial task system, which directly determines effect system. Recently, researchers have found that considering user behavior sequence can greatly improve accuracy click-through model. However, existing models usually use click as input model, will make ...

Micro-videos, a new form of videos that are constrained in duration, gain significant popularity recent years. The volume and rate online micro-videos urgently calls for effective recommendation algorithms to help users find their interested ones. Although some previous works have investigated how model users’ historical behaviors predict the click-through micro-videos, they generally based on ...

The standard business model in the sponsored search marketplace is to sell click-throughs to the advertisers. This involves running an auction that allocates advertisement opportunities based on the value the advertiser is willing to pay per click, times the click-through rate of the advertiser. The click-through rate of an advertiser is the probability that if their ad is shown, it would be cl...

Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit (e.g., dislikes) or simply treat non-clicks as feedback, failing learn interests comprehensively. In such situations, users may experience fatigue because of seeing too many similar recommendations. this pa...

The theory of sponsored search has been developing rapidly although with disagreement in scientific circles on answers to some basic questions about sponsored search. This study focuses on two of these questions, namely, if a search engine seeks to maximize profits, 1) what should its pricing policy be and 2) what should its ranking policy be. This paper uses experiments with economically motiv...

This research presents an innovative and unique way of solving the advertisement prediction problem which is considered as a learning problem over the past several years. Online advertising is a multi-billion-dollar industry and is growing every year with a rapid pace. The goal of this research is to enhance click through rate of the contextual advertisements using Linear Regression. In order t...

Annually, web search engine providers spend more and more money on documents ranking in search engines result pages (SERP). Click models provide advantageous information for ranking documents in SERPs through modeling interactions among users and search engines. Here, three modules are employed to create a hybrid click model; the first module is a PGM-based click model, the second module in a d...