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README.md

sigir2016-ranking-relevance-understandability

We propose a method that integrates relevance and understandability to rank health web documents. We use a learning to rank approach with standard retrieval features to determine topical relevance and additional features based on readability measures and medical lexical aspects to determine understandability. Our experiments measured the effectiveness of the learning to rank approach integrating understandability on a consumer health benchmark. The findings suggest that this approach promotes documents that are at the same time topically relevant and understandable.

Citation:

@inproceedings{palotti16,
    Author = {Joao Palotti and Lorraine Goeuriot and Guido Zuccon and Allan Hanbury},
    Booktitle = {Proc. of SIGIR},
    Title = {Ranking Health Web Pages with Relevance and Understandability},
    Year = {2016}
}

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Code, data and results for our SIGIR 2016 paper - Ranking Health Web Pages with Relevance and Understandability

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