RASTA (Rhetorical Structure Theory Analyzer), a system for automatic discourse analysis, reliably, identifies rhetorical relations present m written discourse by examining information available in syntactic and logical form analyses. Since there is a many-to-many relationship between rhetorical relations and elements of linguistic form, RASTA identifies relations by the convergence of a number ...

We deal with embedding a large scale knowledge graph composed of entities and relations into a continuous vector space. TransE is a promising method proposed recently, which is very efficient while achieving state-of-the-art predictive performance. We discuss some mapping properties of relations which should be considered in embedding, such as reflexive, one-to-many, many-to-one, and many-to-ma...

Even though tree-based reliable multicast protocols are known to be most scalable for one-to-many sessions, there is still an open question whether these protocols are also scalable for many-to-many sessions. We analyze and compare two promising multicast protocols-the receiver-initiated protocol with NACK suppression and the tree-based protocol-using a new spatial loss model. The proposed mode...

Multiplayer perceptrons or feed-forward networks are generally trained to represent functions or many-to-one (m-o) mappings. This creates a problem if the training data exhibits the property of many-to-many or almost many-many valued-ness because the model, which generated the data, was many-to-many. Therefore in this paper a modified feed-forward network and training algorithm is considered to...

An overlooked problem in Learning From Demonstration is the ambiguity that arises, for instance, when the robot is equipped with more sensors than necessary for a certain task. Simply trying to repeat all aspects of a demonstration is seldom what the human teacher wants, and without additional information, it is hard for the robot to know which features are relevant and which should be ignored....