Encyclopedia of Life (EOL) has developed TraitBank (http://eol.org/traitbank), a new repository for organism attribute (trait) data. TraitBank aggregates, manages and serves attribute data for organisms across the tree of life, including life history characteristics, habitats, distributions, ecological relationships and other data types. We describe how TraitBank ingests and manages these data ...

An attribute-oriented rough set method for knowledge discovery in databases is described. The method is based on information generalization, which examines the data at various levels of abstraction, followed by the discovery, analysis and simplification of significant data relationships. First, an attribute-oriented concept tree ascension technique is applied to generalize the information; this...

AVT (Attribute Value Tree) can be considered a generalization of AVM (Attribute Value Matrix) used in many Feature Structured Unification grammars (FSUG). In this paper we give some properties of the AVT like: paths in an AVT, exclusive combinations in an AVT, logical interpretation of an AVT, well formed AVT, the equivalence of the AVTs, the ordered AVTs, the AVTs intersection, the AVTs differ...

A decision making approach which combines multi-attribute decision making techniques with expert systems is described in the paper. In this approach, knowledge about a particular decision making problem is represented in the form of tree-structured criteria and decision rules. Decision making is supported by an expert system shell. In the paper, the discussion is mainly concentrated on the part...

An attribute-oriented induction has been developed in the previous study of knowledge discovery in databases. A concept tree as-cension technique is applied in concept generalization. In this paper, we extend the background knowledge representation from an unconditional non-rule-based concept hierarchy to a rule-based concept hierarchy , which enhances greatly its representation power. An eecie...

Advances in LiDAR and unmanned aerial vehicle technology have made high-resolution data available, which can be used for individual tree detection assessing attributes. The accuracy of these assessments is still not clear stands with high species diversity as well leaf-off leaf-on conditions. aim this study was to assess the quality top heights extracted from photogrammetric point clouds canopy...

As the computer technology and computer network technology are developing, the amount of data in information industry is getting higher and higher. It is necessary to analyze this large amount of data and extract useful knowledge from it. Process of extracting the useful knowledge from huge set of incomplete, noisy, fuzzy and random data is called data mining. Decision tree classification techn...

Searching for binary partition of attribute domains is an important task in Data Mining, particularly in decision tree methods. The most important advantage of decision tree methods are based on compactness and clearness of presented knowledge and high accuracy of classification. In case of large data tables, the existing decision tree induction methods often show to be inefficient in both comp...

Certain data is a data whose values are known precisely whereas uncertain data means whose value are not known precisely. But data is always uncertain in real life applications. In data uncertainty attribute value is represented by a set of values. There are two types of attributes in data sets namely, numerical and categorical attributes. Data uncertainty can arise in both numerical and catego...

As a data structure, a tree is an optimal presentation of hierarchical objects. Many irregular and dynamical phenomena studied for example in biology, medical sciences, meteorology, and geomorphology can be modelled as a tree. In addition, objects initially modelled as a graph can sometimes be transformed to a tree, say to a minimum spanning tree. This paper presents new techniques for indexing...