Teacher:In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Teacher: Now, understand the problem? Solve this instance: We describe a graphical representation of probabilistic relationships-an alternative to the Bayesian network-called a dependency network. Like a Bayesian network, a depen dency network has a graph and a probabil ity component. The graph component is a (cyclic) directed graph such that a node's parents render that node independent of all other nodes in the network. The probabil ity component consists of the probability of a node given its parents for each node (as in a Bayesian network) . We identify several ba sic properties of this representation, and de scribe its use in collaborative filtering (the task of predicting preferences) and the visu alization of predictive relationships.
Student:
Dependency Networks for Collaborative Filtering and Data Visualization