Mixture model based contextual image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
| Hi-index | 0.00 |
It is observed that there is an important query requirement missing for search engines. With the wide variation of domain knowledge and user's interest, a user would like to retrieve documents in which one query term is discussed in the context of another term. Based on the existing query mechanisms, what can be specified at most is the co-occurrence of multiple terms in a query. This is insufficient because the co-occurrence of two terms does not necessarily mean that one is discussed in the context of the other. In this paper we propose the context query for web search. A new query operator, called the 'in' operator, is used to specify the context inclusion between two terms. Heuristics rules to identify context inclusion are suggested and implementation of 'in' operator in search engines is proposed. Results show that both the precision and ranking relevance of web search are improved significantly.