Oriana Baldizan

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The number of datasets in the Linking Open Data (LOD) cloud as well as LOD-based applications have exploded in the last years. However, because of data source heterogeneity, published data may suffer of redundancy, inconsistencies, or may be incomplete; thus, results generated by LOD-based applications may be imprecise, ambiguous, or unreliable. We(More)
We evaluate the suitability of latent and explicit semantic spaces of documents for Information Retrieval (IR) tasks using a dataset obtained from the Q&A community Stackexchange. In addition, the ability of the latent semantic spaces to reconstruct human relevance judgments is explored. The latent semantic spaces are generated with Latent Dirichlet(More)
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