Using Conservative Estimation for Conditional Probability instead of Ignoring Infrequent Case

There are several estimators of conditional probability from observed frequencies of features. In this paper, we propose using the lower limit of confidence interval on posterior distribution determined by the observed frequencies to ascertain conditional probability. In our experiments, this method outperformed other popular estimators.Comment: The 2016 International Conference on Advanced Informatics: Concepts, Theory and Application (ICAICTA2016

Polysemy Detection in Distributed Representation of Word Sense

In this paper, we propose a statistical test to determine whether a given word is used as a polysemic word or not. The statistic of the word in this test roughly corresponds to the fluctuation in the senses of the neighboring words a nd the word itself. Even though the sense of a word corresponds to a single vector, we discuss how polysemy of the words affects the position of vectors. Finally, we also explain the method to detect this effect.Comment: The 9th International Conference on Knowledge and Smart Technology (KST-2017

Analytical solutions for the incompressible viscous flow within a rectangular domain

Analytical solutions of the velocity, pressure and stream function are developed for the slow incompressible viscous fluid in a simple rectangular domain. All solutions can be applied to the boundary integral techniques as typical fundamental solutions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25102/1/0000534.pd

An Interactive Tool for Constrained Clustering with Human Sampling

Abstract-This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process. This tool has some functions such as 2-D visual arrangement of a data set and constraint assignment by mouse manipulation. Moreover, it can execute distance metric learning and kmedoids clustering. In this paper, we show the overview of the tool and how it works, especially in the functions of display arrangement by multi-dimensional scaling and incremental distance metric learning. Eventually we show a preliminary experiment in which human heuristics found through our GUI improve the clustering. This study provides fundamental technologies for interactive clustering of Web page and Web usages. I. INTRODUCTION Constrained clustering is a promising approach for improving the accuracy of clustering by using some prior knowledge about data. As the prior knowledge, we generally use two types of simple constraints about a pair of data. The first constraint is called "must-link" which is a pair of data that must be in the same cluster. The second one is called "cannot-link" which is a pair of data that must be in different clusters. There have been proposed several approaches to utilize these constraints so far. For example, a well-known constrained clustering algorithm the COP-Kmeans [1] uses these constraints as exceptional rules for the data allocation process in a k-means algorithm. A data may not be allocated to the nearest cluster center if the data and a member of the cluster form a cannot-link, or the data and a member of the other cluster form a must-link. Another studies [2], [3], Although the use of constraints is an effective approach, we have some problems in preparing constraints. One problem is the efficiency of the process. Because a human user generally needs to label many constraints with "must-link" or "cannot-link", his/her cognitive cost seems very high. Thus we need an interactive system to help users cut down such an operation cost. The other problem is the effectiveness of the prepared constraints. Many experimental results in recent studies have shown clustering performance does not monotonically improve (sometimes deteriorates) as th

Some general lagrange interpolations over simplex finite elements with reference to derivative singularities

For simplex finite elements, the native Lagrange family with arbitrarily placed nodes is presented in hierarchy-ranking expressions. It includes the well-known complete Lagrange family as well as the mid-edge Lagrange family to be proposed in this paper. This new family enables us to utilize harmonious combinations of interpolations of different orders in finite element analysis. As an application of developed simplex interpolations to fracture mechanics where some derivative singularities are needed, we then describe the semi-radial singularity mapping with examinations of peculiar trial function spaces.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24285/1/0000551.pd

Clustering with Extended Constraints by Co-Training

Abstract-Constrained Clustering is a datamining technique that produces clusters of similar data by using pre-given constraints about data pairs. If we consider using constrained clustering for some practical interactive systems such as information retrieval or recommendation systems, the cost of constraint preparation will be the problem as well as other machine learning techniques. In this paper, we propose a method to complement the lack of constraints by using co-training framework, which extends training examples by leveraging two kinds of feature sets. Our method is based on a constrained clustering ensemble algorithm that integrates a set of clusters produced by a constrained k-means with random ordered data assignment, and runs the same algorithm on two different feature sets to extend constraints. We evaluate our method on a Web page dataset that provides two different feature sets. The results show that our method achieves the performance improvement by using co-training approach

SUPERCONDUCTION AND NORMAL CONDUCTING CHARACTERISTICS OF (YXPR1-X)BA2CU3O7-DELTA THIN-FILMS

The ratio of Yttrium (Y) to Praseodymium (Pr) is varied in (YxPr1-x)Ba2Cu3O7-delta (YPBCO) thin films to consider the relation between superconducting YBa2Cu3O7-delta (YBCO) and insulating PrBa2Cu3O7-delta (PBCO) thin films. The critical temperature (T-c) of the superconducting YPBCO thin film is decreased by substituting more Pr in place of Y, because Pr reduces the carrier density on the CuO2 plane in YPBCO. The electrical characteristic of the YBCO film can be explained by the weakly coupled chain model. The addition of Pr reinforces the superconducting links among the grains in the YPBCO thin film. The normal state YPBCO film shows two types of transport systems. Behavior similar to impurity semiconductors appears at high temperatures and the variable range hopping mechanism governs their conductance at low temperatures