In text mining framework, data-driven indices are used as importance indices of words and phrases. Although the values of these indices are influenced by usages of terms, many conventional emergent term detection methods did not treat these indices explicitly. In order to detect research keys in academic researches, we propose a method based on temporal patterns of technical terms by using seve...

We propose a neural network based saliency analysis to identify important information related to investment decisions. We apply our approach to 753 US stocks and 1960 head-and-shoulders patterns. The results show that variables that are related to technical patterns: membership value and pattern length as well as firm size have the highest saliency coefficients. They are the most relevant ones ...

A symmetric matrix A is said to be sign-nonsingular if every symmetric matrix with the same sign pattern as A is nonsingular. Hall, Li and Wang (2001) showed that the inertia of a signnonsingular symmetric matrix is determined uniquely by its sign pattern. The purpose of this paper is to present an efficient algorithm for computing the inertia of such matrices. The algorithm runs in O(nm) time ...

A fundamental assumption of statistical linguistics is that there are differences worthy of note in the frequency of various units in certain texts. At the same Time, there are differences in frequencies which would not be considered important. The question is, how is an "important" difference tO be determined? The mesolution of this pmoblem has been made more important by the increasing popula...

In an effort to individualize instruction and improve the effectiveness of instructor-learner transactions, education and instructional research has addressed a wide assortment of learner variables and assessed their relationships to instructional methods and environments. Frequently included in this research are analyses of how information is obtained and processed. Identified in the literatur...

Large-scale event systems are becoming increasingly popular in a variety of domains. Event pattern evaluation plays a key role in monitoring applications in these domains. Existing work on pattern evaluation, however, assumes that the occurrence time of each event is known precisely and the events from various sources can be merged into a single stream with a total or partial order. We observe ...