Keyword generation for search engine advertising using semantic similarity between terms

An important problem in search engine advertising is keyword1 generation. In the past, advertisers have preferred to bid for keywords that tend to have high search volumes and hence are more expensive. An alternate strategy involves bidding for several related but low volume, inexpensive terms that generate the same amount of traffic cumulatively but are much cheaper. This paper seeks to establish a mathematical formulation of this problem and suggests a method for generation of several terms from a seed keyword. This approach uses a web based kernel function to establish semantic similarity between terms. The similarity graph is then traversed to generate keywords that are related but cheaper. Categories and Subject Descriptors H.3.1 [Information Systems]: Linguistic processing; J.4 [Computer Applications]: Economics; K.4.4 [Computing Milieux]: Electronic Commerce General Terms Algorithm, Economics Keywords Keyword Generation, Semantic Similarity, Sponsored Search, Search Engine Opti...

• Type: Conference
• Year: 2007
• Where: ACMICEC
• Authors: Vibhanshu Abhishek, Kartik Hosanagar
• Keywords: ACMICEC 2007, ECommerce, Search Engine, Search Engine Advertising, Semantic Similarity