An ontology-based approach to Chinese semantic advertising

Abstract

In the web advertising domain, contextual advertising and sponsored search are two of the main advertising channels used to display related advertisements on web pages. A major challenge for contextual advertising is to match advertisements and web pages based on their semantics. When a web page and its semantically related advertisements contain many different words, the performance of the traditional methods can be very poor. In particular, there are few studies presented for Chinese contextual advertising that are based on semantics. To address these issues, we propose an ontology-based approach to Chinese semantic advertising. We utilize an ontology called the Taobao Ontology and populate it by automatically adding related phrases as instances. The ontology is used to match web pages and advertisements on a conceptual level. Based on the Taobao Ontology, the proposed method exploits seven distance functions to measure the similarities between concepts and web pages or advertisements. Then, the similarities between web pages and advertisements are calculated by considering the ontology-based similarities as well as term-based similarities. The empirical experiments indicate that our method is able to match Chinese web pages and advertisements with a relatively high accuracy. Among the seven distance functions, Cosine distance and Tanimoto distance show the best performance in terms of precision, recall, and F-measure. In addition, our method outperforms two contextual advertising methods, i.e., the impedance coupling method and the SVM-based method.