Most induction algorithms for building predictive models take as input training data in the form of feature vectors. Acquiring the values of features may be costly, and simply acquiring all values may be wasteful or prohibitively expensive. Active feature-value acquisition (AFA) selects features...

We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm-specific news stories forecasts low firm earnings; (2) firms' stock prices briefly...

Many real-world large datasets correspond to bipartite graph data settings; think for example of users rating movies or people visiting locations. Although some work exists over such bigraphs, no general network-oriented methodology has been proposed yet to perform node classification. In this...