Samuel D. Popper

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This paper addresses the problem of developing methods to be used in the identification and extraction of meaningful semantic components from large online glossaries. We present two sets of results. First, we report on the algorithm, ParseGloss, which was used to analyze definitions, and extract the main concept, or genus phrase. We ran the system on over(More)
The Digital Government Research Center (DGRC) has completed phase one of the Energy Data Collection (EDC) project. In this paper, we present the results of building and evaluating system components, along with plans for phase two of the project. Phase one focused on data about petroleum products’ prices and volumes, provided by the Energy Information(More)
An obstacle to understanding results across heterogeneous databases is the ability to determine conceptual connections between differing terminologies. In this paper, we present the two step approach which we have used to build a terminological database in order to address this issue. First we automatically built a heterogeneous collection of terms and(More)
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