Can readability enhance recommendations on community question answering sites?
Oghenemaro Anuyah (Boise State University)
Ion Madrazo Madrazo Azpiazu (Boise State University)
David McNeill (Boise State University)
Maria Soledad Pera (Boise State University)
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Abstract
We present an initial examination on the impact text complexity has when incorporated into the recommendation process in community question answering sites. We use Read2Vec, a readability assessment tool designed to measure the readability level of short documents, to inform a traditional content-based recommendation strategy. The results highlight the benefits of incorporating readability information in this process.
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