document: Einstein : physicist or vegetarian ? summarizing semantic type graphs for knowledge discovery The Web and , in particular , knowledge-sharing communities such as Wikipedia contain a huge amount of information encompassing disparate and diverse fields . Knowledge bases such as DBpedia or Yago represent the data in a concise and more structured way bearing the potential of bringing database tools to Web Search . The wealth of data , however , poses the challenge of how to retrieve important and valuable information , which is often intertwined with trivial and less important details . This calls for an efficient and automatic summarization method . In this demonstration proposal , we consider the novel problem of summarizing the information related to a given entity , like a person or an organization . To this end , we utilize the rich type graph that knowledge bases provide for each entity , and define the problem of selecting the best cost-restricted subset of types as summary with good coverage of salient properties . We propose a demonstration of our system which allows the user to specify the entity to summarize , an upper bound on the cost of the resulting summary , as well as to browse the knowledge base in a more simple and intuitive manner .
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