In this paper we propose a technique for evaluating similarity of XML Schema fragments. Firstly, we define classes of structurally and semantically equivalent XSD constructs. Then we propose a similarity measure that is based on the idea of edit distance utilized to XSD constructs and enables one to involve various additional similarity aspects. In particular, we exploit the equivalence classes...

The crucial problem for integrating geospatial data is finding the corresponding objects (the counterpart) from different sources. Most current studies focus on object matching with individual attributes such as spatial, name, or other attributes, which avoids the difficulty of integrating those attributes, but at the cost of an ineffective matching. In this study, we propose an approach for ma...

In this paper we propose a solution to the similarity measuring for heterogenous data. The key idea is to consider the similarity of a given attribute-value pair as the probability of picking randomly a value pair that is less similar than or equally similar in terms of order relations defined appropriately for data types. Similarities of attribute value pairs are then integrated into similarit...

Recently, we have witnessed substantial success using the deep neural network in many tasks. Although there still exist concerns about explainability of decision making, it is beneficial for users to discern defects deployed models. Existing explainable models either provide image-level visualization attention weights or generate textual descriptions as post hoc justifications. Different from e...

In data mining and knowledge discovery, similarity between objects is one of the central concepts. A measure of similarity can be user-deened, but an important problem is deening similarity on the basis of data. In this thesis we consider two kinds of similarity notions: similarity between binary valued attributes and between event sequences. Traditional approaches for deening similarity betwee...

Dempster-Shafer evidence theory is widely used in many soft sensors data fusion systems on account of its good performance for handling the uncertainty information of soft sensors. However, how to determine basic belief assignment (BBA) is still an open issue. The existing methods to determine BBA do not consider the reliability of each attribute; at the same time, they cannot effectively deter...

This paper strives to predict fine-grained fashion similarity. In this similarity paradigm, one should pay more attention the in terms of a specific design/attribute between items. For example, whether collar designs two clothes are similar. It has potential value many related applications, such as copyright protection. To end, we propose an Attribute-Specific Embedding Network (ASEN) jointly l...

With respect to the multiple attribute group decision making problems in which the attribute weights are unknown and the attribute values take the form of the intuitionistic linguistic numbers, an expanded technique for order preference by similarity to ideal solution (TOPSIS) method is proposed. Firstly, the definition of intuitionistic linguistic number and the operational laws are given and ...

Attribute reduction is one of the core issues of the rough set theory. The traditional method of attribute reduction was designed based on positive region unchanged, as abandoning processing the incompatible data in the boundary domain, so the classification characteristics of the reduction results are not necessarily best. In this paper, the concept of relative approximate degree is proposed i...