Separating the wheat from the chaff with machine learning

Mental health coverage parity: separating wheat from chaff.

‘life Wasn’t Meant to Be Easy’: Separating Wheat from Chaff in Technology Aided Learning?

The paper commences by reviewing some of the issues currently being raised with respect to the use of technology in undergraduate mathematics teaching and learning. Selected material from three research projects is used to address a series of questions. The questions relate to the use of symbolic manipulators in tertiary mathematics, to undergraduate student attitudes towards the use of compute...

Estimating excess length of stay due to central line-associated bloodstream infection: separating the wheat from the chaff.

Learning from Other's Mistakes - One Approach to Teaching Information Literacy

Everyone in the academic community is today confronted with an unprecedented problem. One click of the mouse can provide a student with enough source material to construct a doctoral thesis. Thus, the problem is no longer to locate the relevant material; today the difficulty is in separating the wheat from the chaff, or a more apt analogy, finding the few gold nuggets in the mountains of dross....

Separating Wheat from the Chaff - A Relationship Ranking Algorithm

We address the problem of ranking relationships in an automatically constructed knowledge graph. We propose a probabilistic ranking mechanism that utilizes entity popularity, entity affinity, and support from text corpora for the relationships. Results obtained from preliminary experiments on a standard dataset are encouraging and show that our proposed ranking mechanism can find more informati...