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According to the accumulation of the electrically stored documents, acquisition of valuable knowledge with remarkable trends of technical terms has drawn the attentions as the topic in text mining. In order to support for discovering key topics appeared as key terms in such temporal textual datasets, we propose a method based on temporal patterns in several data-driven indices for text mining. The...
Information on the web is huge in size and to find the relevant information according to the information need of the user is a big challenge. Information scent of the clicked pages of the past query sessions has been used in the literature to generate web page recommendations for satisfying the information need of the current user. High scent information retrieval works on the bedrock of keyword vector...
In order to handle very large data bases efficiently, the data warehousing system ICE [1] builds so-called rough tables containing information that is abstracted from certain blocks of the original table. In this article we propose a formal description of such rough tables. We also investigate possibilities of mining them for implicational knowledge. The underyling article is an extended version of...
This article introduces the notion of multiset topology (M-topology) and points out the concept of open multisets (mset, for short). Multiset topologies are obtained by using multiset relation. Rough multiset is introduced in terms of lower and upper approximations. We use a multiset topological concept to investigate Pawlaks rough set theory by replaing its universe by multiset. The multiset topology...
Facial recognition is routine for most people; yet describing the process of recognition, or describing a face to be recognized reveals a great deal of complexity inherent in the activity. Eyewitness identification remains an important element in judicial proceedings: it is very convincing, yet it is not very accurate. A study was conducted in which participants were asked to sort a collection...
Gene selection is to select the most informative genes from the whole gene set, which is a key step of the discriminant analysis of microarray data. Rough set theory is an efficient mathematical tool for further reducing redundancy. The main limitation of traditional rough set theory is the lack of effective methods for dealing with real-valued data. However, gene expression data sets are always continuous...
In this paper, we discuss some algebraic structures of the set of all lower( ) and upper( ) approximations defined through the basic map ϕ in the general setting of complete atomic Boolean lattice B. In fact, we prove that if ϕ is extensive and closed, then and are algebraic completely distributive lattices. A...
Finding clusters in large datasets is an interesting challenge in many fields of Science and Technology. Many clustering methods have been successfully developed over the years. However, most of the existing clustering methods need multiple data scans to get converged. Therefore, these methods cannot be applied for cluster analysis in large datasets. Data summarization can be used as a pre-processing...
Fuzzy techniques have been used for handling vague boundaries of arbitrarily oriented clusters. However, traditional clustering algorithms tend to break down in high dimensional spaces due to inherent sparsity of data. We propose a modification in the objective function of Gustafson-Kessel clustering algorithm for projected clustering and prove the convergence of the resulting algorithm. We present...
This paper consists of an extensive survey of various generalized approaches to the lower and upper approximations of a set, the two approximations being first defined by Pawlak while introducing rough set theory. Particularly, relational, covering based and operator based approaches are considered. Categorization of various approaches in terms of implication lattices is shown. Significance of this...
In this paper, we propose two approaches of classification namely, Dynamic Belief Rough Set Classifier (D-BRSC) and Dynamic Belief Rough Set Classifier based on Generalization Distribution Table (D-BRSC-GDT). Both the classifiers are induced from uncertain data to generate classification rules. The uncertainty appears only in decision attribute values and is handled by the Transferable Belief Model...
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