Abstract
In this work, we propose an approach that allows to query heterogeneous data sources on the Web in a declarative fashion. Such an approach gives means for a generic way to formulate various information needs, much more powerful than simple keyword queries. Particularly appealing is the ability to combine (join) information from different sources and the ability to compute simple statistics that can be used to select promising information pieces. What might sound like a hopeless effort due to the inherent complexity expressible by SQL-style queries is at second glance not complicated to understand and to use. Already very simple combinations (i.e., joins) of different data sources (i.e., tables) offer a surprisingly large set of interesting use cases. In particular, using sliding window joins that limit the scope of interest to recent information, obtained, for instance, from the live stream of Twitter Tweets. This goes far beyond keyword queries enriched with operators like allintext: or allintitle: or site:, as can be used, for instance, in the Google search engine.
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Notes
While news sites and blogs where crawled continuously over this period of time, the time window in which Tweets where collected comprises only a couple of days in late July 2011.
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This work has been supported by the Excellence Cluster on Multimodal Computing and Interaction (MMCI).
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Pinkel, C., Alvanaki, F. & Michel, S. Sequoia—An Approach to Declarative Information Retrieval. Datenbank Spektrum 12, 101–108 (2012). https://doi.org/10.1007/s13222-012-0087-5
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DOI: https://doi.org/10.1007/s13222-012-0087-5