LSI vs. Wordnet Ontology in Dimension Reduction for Information Retrieval

@inproceedings{Moravec2004LSIVW,
  title={LSI vs. Wordnet Ontology in Dimension Reduction for Information Retrieval},
  author={Pavel Moravec and Michal Kolovrat and V{\'a}clav Sn{\'a}sel},
  booktitle={DATESO},
  year={2004}
}
In the area of information retrieval, the dimension of document vectors plays an important role. Firstly, with higher dimensions index structures suffer the “curse of dimensionality” and their efficiency rapidly decreases. Secondly, we may not use exact words when looking for a document, thus we miss some relevant documents. LSI (Latent Semantic Indexing) is a numerical method, which discovers latent semantic in documents by creating concepts from existing terms. However, it is hard to compute… CONTINUE READING

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