A means to ease selecting preferred music referred to as Personalized Automatic Track Selection (PATS) has been developed. PATS generates playlists that suit a particular contextof-use, that is, the real-world environment in which the music is heard. To create playlists, it uses a dynamic clustering method in which songs are grouped based on their attribute similarity. The similarity measure se...

Our work is motivated by and illustrated with application of association networks in computational biology, specifically in the context of gene/protein regulatory networks. Association networks represent systems of interacting elements, where a link between two different elements indicates a sufficient level of similarity between element attributes. While in reality relational ties between elem...

Relations and relation matrices are important concepts in set theory and intelligent computation. Some general uncertainty measures for fuzzy relations are proposed by generalizing Shannon’s information entropy. Then, the proposed measures are used to calculate the diversity quantity of multiple classifier systems and the granularity of granulated problem spaces, respectively. As a diversity me...

Multi-attribute emergency decision-making problems have the characteristics of incomplete information and shortage response time. Evidence theory can effectively express uncertain in process. However, evidence requires that condition independence is met, evaluation experts often vague. Therefore, an method based on intuitionistic fuzzy sets proposed. First, each expert gives plan. Secondly, pro...

In multi-alternative choice, the attraction, compromise, and similarity effects demonstrate that the value of an alternative is not independent of the other alternatives in the choice-set. Rather, these effects suggest that a choice is reached through the comparison of alternatives. We investigated exactly how alternatives are compared against each other using eye-movement data. The results ind...

Clustering categorical data is more complicated than the numerical clustering because of its special properties. Scalability and memory constraint is the challenging problem in clustering large data set. This paper presents an incremental algorithm to cluster the categorical data. Frequencies of attribute values contribute much in clustering similar categorical objects. In this paper we propose...

The linguistic neutrosophic numbers (LNNs) can express the truth, indeterminacy, and falsity degrees independently by three linguistic variables. Hence, they are an effective tool for describing indeterminate linguistic information under linguistic decision-making environments. Similarity measures are usual tools in decision-making problems. However, existing cosine similarity measures have bee...

Effective manipulation of string data is of fundamental importance to modern database applications. Very often, textual inconsistencies render equality comparisons meaningless and strings have to be matched in terms of their similarity. Previous work has proposed techniques to express similarity operations using declarative SQL statements. However, the non-trivial issue of embedding similarity ...