A unified framework for semantics and feature based relevance feedback in image retrieval systems
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
INFORMS Journal on Computing
Dynamics of bid optimization in online advertisement auctions
Proceedings of the 16th international conference on World Wide Web
Keyword generation for search engine advertising using semantic similarity between terms
Proceedings of the ninth international conference on Electronic commerce
Advertising keyword generation using active learning
Proceedings of the 18th international conference on World wide web
A random fuzzy minimum spanning tree problem through a possibility-based value at risk model
Expert Systems with Applications: An International Journal
Journal of Biomedical Informatics
Hi-index | 12.05 |
This paper provides a comprehensive study of the structure of relevant keywords in a search engine using the minimum spanning tree (MST) approach. In the process of constructing MST's, we introduce a novel metric to measure a distance between keywords by applying an integration of the Pearson correlation and the query-based cosine similarity. From this work, we made several meaningful observations about the networks of relevant keywords. First, keyword networks in a search engine exhibit the small-world effect and the scale-free property. Second, only a few among relevant keywords in the order of popularity are positively correlated and there is no significantly positive or negative relationship for the rest of relevant keywords. Third, the degree of searching activity for relevant keywords varies depending on whether they are branded keywords or non-branded keywords as well as the characteristics of product categories. Fourth, the mean correlation coefficient for keyword impressions during slow season increases. Finally, both k"m"a"x and the betweenness centrality for high-involvement products are higher than those for low-involvement products.