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For the multi-index decision problem with uncertain information, this paper introduces the definition of interval distance of three-parameter interval grey number, proposes the relative degree of grey incidence based on interval distance of three-parameter interval grey number, constructs the grey incidence decision-making model with three-parameter interval grey number, measures the relative degree...
In this paper, we present an impression estimation method for television commercials with a visualization method. Our method estimates the impressions viewers might have of a new proposal for a TV commercial written in text as weighted favorable factors and visualizes the estimated favorable factors. During the production of TV commercials, it is important to create commercials that clearly communicate...
In recent times, there has been significant interest in the machine recognition of human emotions, due to the suite of applications to which this knowledge can be applied. A number of different modalities, such as speech or facial expression, individually and with eye gaze, have been investigated by the affective computing research community to either classify the emotion (e.g. sad, happy, angry)...
We investigate the properties of two particular sets of separable two-qubit states with maximally mixed marginals, named parallel states and antiparallel states respectively. Although these two sets of states are prepared by the same type of quantum operations acting on classically correlated states with equal classical correlations, they share different properties. By comparing two fundamental figures...
spatial co-location pattern mining is an important part of spatial data mining, and the purpose is to discover the coexistence spatial feature sets whose instances are frequently located together in a geographic space. However, it ignores the existence of autocorrelation features that is not associated with surrounding features. For example, “cactus” and “jerusalem artichoke” are two common plants...
There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as face book, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart...
In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple...
This study aimed to investigate the relationship between learning behaviors (hypothesis-making, interpreting graphs, applying formula, conclusion-making and conceptual understanding) and learning achievement on vocational students who use our developed Ubiquitous-Physics (U-Physics) to learn simple pendulum in the experiment. Thus, this study conducted an experiment with participating second grade...
Today smart devices such as smartphones, smartwatches and activity trackers are widely available and accepted in most developed societies. These devices present a broad set of sensors capable of extracting detailed information about different situations of daily life, which, if used for good, have the potential to improve the quality of life not only for individuals but also for the society in general...
Given a collection of event-related documents, event ranking generates a list of ranked events based on the input query. Ranking news events, which takes event related news documents for the generation of ranked events, is both an essential research issue and important component for many security oriented applications, such as public event monitoring, retrieval, detection and mining. Previous related...
In an IoT environment, process analysis becomes more difficult as a process usually spans over a set of autonomous and distributed sensors. This paper consummates our previous service hyperlink model, to encapsulate dependencies among events generated from services. To effectively discover service hyperlinks, we transform the service hyperlink discovery problem into a frequent sequence mining problem...
This research is concerned with the study of Spanish Facebook pages that deal with rare diseases. The objectives of this research are to characterise these pages and to compare them with the priorities of the Decalogue of the Spanish Federation of Rare Diseases (FEDER). This research uses Netvizz to download the data, word clouds in R to perform text mining, TextBlob in Python to perform sentiment...
This paper makes an empirical test on the correlation between financial restatement and audit report lag (ARL) using data of non-financial listed companies in China during the period 2009–2012. The empirical results show that there is a significant positive correlation between financial restatement and ARL. The longer the ARL is, the more likely it is for the company to perform a financial restatement...
The spread of smart meters means that a large amount of power demand information from private houses is being collected around the world. Owing to the development of smart city infrastructure, the use of standardized frameworks for extracting features from power demand information has become vital. In this paper, we propose a novel decomposition approach useful for extracting feature values from power...
Via online social interactions, users in social networks can form their personal attitudes toward other users. Some of the personal social attitudes will be expressed explicitly, which are represented as the signed social links from the initiators to the recipients. In this paper, we will study the "social Attitude exPression prEdiction" (APE) problem, which aims at inferring both the expression...
Traditional methods for hyperspectral image classification typically use raw spectral signatures without considering spatial characteristics. In this work, a classification algorithm based on Gabor features and decision fusion is proposed. First, the adjacent and high correlated spectral bands are intelligently grouped by coefficient correlation matrix. Following that, Gabor features in each group...
The availability of large amounts of information associated with the teaching and learning process challenges researchers to explore this information by using learning analytics to obtain indicators that can contribute to improving the teaching and learning process, particularly in terms of learning outcomes and the relationship students have with the educational institutions they attend. Considering...
Even if land deformation in Sahel-Doukkala may not directly threaten human life, it could lead to serious economic losses. Therefore, the monitoring of this deformation becomes a priority. In this study, PS-InSAR technique was applied in order to extract information regarding land deformation. This method was successful in detecting a considerable amount of PS targets from which the land deformation...
This paper studies design and implementation of precision marketing system on business platform of telecom network package, and proposes the analysis and mining technology based on distributed processing technology, for massive business payment data. Then the mining results are applied to final scheme of precision marketing strategy implementation. The scheme uses K-Means to segment users-based business...
Failing to identify multi-word expression (MWE) may cause serious problems for many Natural Language Processing (NLP) tasks. Previous approaches heavily depend on language specific knowledge and pre-existing natural language processing (NLP) tools. However, many languages (including Chinese language) have less such resources and tools compared to English. An automatically learn effective features...
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