Attribute grammars are a formalism for specifying computations on context-free languages. Due to the nonstrictness of the if constructs in attribution equations, it is possible to avoid evaluating certain attribute instances in a syntax tree. A dynamic evaluator can easily avoid such useless computations with a demand-driven approach. However, dynamic evaluators are not efficient because they n...

Attribute clustering has been previously employed to detect statistical dependence between subsets of variables. Clusters of variables can be appropriately used for detecting highly dependent domain variables and then reducing the complexity of learning Bayesian networks. We propose a novel attribute clustering algorithm motivated by research of complex networks, called the Star Discovery algor...

  Laviniu Aurelian Badulescu   University of Craiova, Faculty of Automation, Computers and Electronics, Software Engineering Department     Abstract: One of the major tasks in Data Mining is classification. The growing of Decision Tree from data is a very efficient technique for learning classifiers. The selection of an attribute used to split the data set at each Decision Tree node is ...

Abstract Key message This study details a methodology to automatically detect the positions of and dasometric information about individual Eucalyptus trees from point cloud acquired with portable LiDAR system. Currently, implementation laser scanners (PLS) in forest inventories is being studied, since they allow for significantly reduced field-work time costs when compared traditional inventory...

Attributed tree transducers are abstract models to study properties of attribute grammars. One abstraction which occurs when modeling attribute grammars by attributed tree transducers is that arbitrary trees over a ranked alphabet are taken as input, instead of derivation trees of a context{free grammar. In this paper we show that with respect to the generating power this is not an abstraction,...

The effectiveness of using the semantic attributes of verbs has been shown in various kinds of natural processing systems, such as machine translation systems. The addition of an attribute value is, however, time-consuming and must be performed by hand by an expert on the attribute value. In this paper, two methods for efficiently adding verbal semantic attributes to a Japanese-to-English valen...

We introduce Propositionalized Attribute Taxonomy guided Decision Tree Learner (PAT-DTL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact decision trees. Since taxonomies are unavailable in most domains, we also introduce Propositionalized Attribute Taxonomy Learner (PAT-Learner) that automatically constructs taxono...