In this paper we investigate the co-authorship graph obtained from all papers published at SIGMOD between 1975 and 2002. We find some interesting facts, for instance, the identity of the authors who, on average, are "closest" to all other authors at a given time. We also show that SIGMOD's co-authorship graph is yet another example of a small world---a graph topology which has received a lot of attention recently. A companion web site for this paper can be found at http://db.cs.ualberta.ca/coauthorship.
Many keyword queries issued to Web search engines target information about real world entities, and interpreting these queries over Web knowledge bases can often enable the search system to provide exact answers to queries. Equally important is the problem of detecting when the reference knowledge base is not capable of answering the keyword query, due to lack of domain coverage.In this work we present an approach to computing structured representations of keyword queries over a reference knowledge base. We mine frequent query structures from a Web query log and map these structures into a reference knowledge base. Our approach exploits coarse linguistic structure in keyword queries, and combines it with rich structured query representations of information needs.
An increasing amount of structured data on the Web has attracted industry attention and renewed research interest in what is collectively referred to as semantic search. These solutions exploit the explicit semantics captured in structured data such as RDF for enhancing document representation and retrieval, or for finding answers by directly searching over the data. These data have been used for different tasks and a wide range of corresponding semantic search solutions have been proposed in the past. However, it has been widely recognized that a standardized setting to evaluate and analyze the current state-of-the-art in semantic search is needed to monitor and stimulate further progress in the field. In this paper, we present an evaluation framework for semantic search, analyze the framework with regard to repeatability and reliability, and report on our experiences on applying it in the Semantic Search Challenge 2010 and 2011.
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