Word embeddings, which often represent such analogic relations as king - man + woman = queen, can be used to change a word's attribute, including its gender. For transferring into queen in this analogy-based manner, we subtract difference vector based on the knowledge that is male. However, developing very costly for words and attributes. In work, propose novel method word attribute transfer re...

Obtaining compact and discriminative features is one of the major challenges in many of the real-world image classification tasks such as face verification and object recognition. One possible approach is to represent input image on the basis of high-level features that carry semantic meaning which humans can understand. In this paper, a model coined deep attribute network (DAN) is proposed to ...

We consider the problem of ordinal classification, in which a value set of the decision attribute (output, dependent variable) is finite and ordered. This problem shares some characteristics of multi-class classification and regression, however, in contrast to the former, the order between class labels cannot be neglected, and, in the contrast to the latter, the scale of the decision attribute ...

A novel information identification model is proposed to support accurate classification tasks with mixtures of categorical and real-valued attributes. This model combines the advantages of rough set theory and cluster validity method to promote the classification quality to the higher levels. Real-valued attribute values are pre-processed by fuzzy c-means clustering method and then analyzed by ...

The natural representation of XML data is to use the underlying tree structure of the data. When analyzing these trees we are ensured that no structural information is lost. These tree structures can be efficiently analyzed due to the existence of frequent pattern mining algorithms that works directly on tree structured data. In this work we describe a classification method for XML data based o...

MOTIVATION A global view of the protein space is essential for functional and evolutionary analysis of proteins. In order to achieve this, a similarity network can be built using pairwise relationships among proteins. However, existing similarity networks employ a single similarity measure and therefore their utility depends highly on the quality of the selected measure. A more robust represent...

Developments in information technology has enabled accumulation of large databases and most of the environmental, agricultural and medical databases consist of large quantity of real time observatory datasets of high dimension space. The curse to these high dimensional datasets is the spatial and computational requirements, which leads to ever growing necessity of attribute reduction techniques...

Rough Set theory, proposed by Pawlak in 1982, is a mathematical tool for classification and analysis of imprecise, uncertain, incomplete or vague information and knowledge. Using various concepts in RST, classification of objects in various classes is done by removing irrelevant and redundant data by using attribute reduction algorithm. Attribute reduction using Rough set theory is one of the k...