Generating summaries of multiple news articles
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Generating natural language summaries from multiple on-line sources
Computational Linguistics - Special issue on natural language generation
Investigating summarization techniques for geo-tagged image indexing
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
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In this paper we investigate what sorts of information humans request about geographical objects of the same type. For example, Edinburgh Castle and the Bodiam Castle are two objects of the same type - castle. The question is whether specific information is requested for the object type castle and how this information differs for objects of other types, e.g. church, museum or lake. We aim to answer this question using an online survey. In the survey we showed 184 participants 200 images pertaining to urban and rural objects and asked them to write questions for which they would like to know the answers when seeing those objects. Our analysis of 7644 questions collected in the survey shows that humans have shared ideas of what to ask about geographical objects. When the object types resemble each other (e.g. church, temple) the requested information is similar for the objects of these types. Otherwise, the information is specific to an object type. Our results can guide tasks involving automatic generation of templates for image descriptions, and their assessment as well as image indexing and organization.