Characterizing Machine Agent Behavior through SPARQL Query Mining
نویسنده
چکیده
Mining SPARQL queries to understand the behavior of automated programs (or machine agents) is an important step in designing systems for the semantic web. We present techniques that differ from state-of-the-art SPARQL mining techniques in two ways: 1. Move away from one SPARQL query at a time view to SPARQL user session view 2. Look at the results of SPARQL queries in addition to the query itself. Due to these two approaches, we are able to find two new patterns in SPARQL queries that help us reason better about the underlying program that generated the SPARQL queries. Through a variety of experiments, we show that the patterns found have significant support in all the four datasets provided by the USEWOD committee.
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