Semantic Space models for classification of consumer webpages on metadata attributes

@article{Chen2010SemanticSM,
  title={Semantic Space models for classification of consumer webpages on metadata attributes},
  author={Guocai Chen and Jim Warren and Patricia Riddle},
  journal={Journal of biomedical informatics},
  year={2010},
  volume={43 5},
  pages={
          725-35
        }
}
To deal with the quantity and quality issues with online healthcare resources, creating web portals centred on particular health topics and/or communities of users is a strategy to provide access to a reduced corpus of information resources that meet quality and relevance criteria. In this paper we use hyperspace analogue to language (HAL) to model the language use patterns of webpages as Semantic Spaces. We have applied machine learning methods, including support vector machine (SVM), decision… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 37 REFERENCES

An analysis of the relative hardness of Reuters-21578 subsets

VIEW 15 EXCERPTS
HIGHLY INFLUENTIAL

Representing abstract words and emotional connotation in a high-dimensional memory space

  • C Burgess, K. Lund
  • Cognitive science proceedings, LEA http:// halucredu/pdfs/Burgess_Lund(1997b)pdf: Lawrence Erlbaum Associates; p
  • 1997
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Empirical distributional semantics: Methods and biomedical applications

VIEW 1 EXCERPT