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Despite being important, time and context have yet to be formally incorporated into the process of visually representing the temporal and contextual proximity between keywords in a concept map. In response to the context and time challenges, this study improves automated conventional concept mapping by measuring the temporal and contextual distance between pairs of co-occurring concepts. After generating...
In the current scenario, data is considered to be the biggest assets. One who has maximum relevant data is considered to be rich in the information industry. But only the collection of data is not enough, it needs to be analyzed. This huge amount of data which is termed ass Big Data cannot be analyzed by traditional tools and techniques, rather it requires more advanced Techniques which can make data...
Due to the rapid development of network information, e-commerce has entered the era of big data. From these large data mining the useful information has a high commercial value, especially for short life cycle products, improve it in each stage of life cycle prediction ability, in addition to some of the conventional data mining model depends on the specific data mining platform, and can't realize...
With no limit on time and location [1], the number of users attracted by massive open online course (MOOC) has increased rapidly, and many platforms have been built to provide a variety of courses. All of these trigger an explosive growth in data volume. As we known, people have met big data in many areas and proposed many techniques and methods to deal with them. However, people still have no sense...
Mining useful knowledge from data readily available in today's information systems has been a common challenge in recent years as more and more events are being recorded, and there is need to improve and support many organisational processes in a competitive and rapidly changing environments. The work in this paper shows using a case study of Learning Process — how data from various process domains...
Frequent sequence mining methods often make use of constraints to control which subsequences should be mined, e.g., length, gap, span, regular-expression, and hierarchy constraints. We show that many subsequence constraints—including and beyond those considered in the literature—can be unified in a single framework. In more detail, we propose a set of simple and intuitive "pattern expressions"...
Investigating human mobility patterns and comprehending the social dynamics that govern people movements is of high interest for multiple aspects and reasons. Location-based services, mobile network management, and urban planning are just few of the several applications that benefit fromthis kind of assessment. This work focuses on the stochasticanalysis of spatiotemporal and social network data in...
Social graphs, representing online friendships among users, are one of the fundamental types of data for many applications, such as recommendation, virality prediction and marketing in social media. However, this data may be unavailable due to the privacy concerns of users, or kept private by social network operators, which makes such applications difficult. Inferring users' interests and discovering...
In this paper, we propose a interactive constrained independent topic analysis in text mining. Independent Topic Analysis (ITA) is a method for extracting the independent topics from the document data by using the independent component analysis. In the independent topic analysis, it is possible to extract the most independent topics between each topic. By extracting the independent topic, it is easy...
Constellation's overarching goal is the federation of information from resources within an extreme-scale scientific collaboration to enable the scalable discovery of data and new knowledge pathways. The resource fabric is comprised of petascale supercomputers and storage systems, users, jobs, datasets and lifecycle artifacts. For an extreme-scale supercomputing center, normal operations can generate...
In this study, we focus on extraction of latent topic transition from POS data. POS analysis is conducted to obtain the frequent pattern of customer's behavior. The fundamental method for POS analysis is to conduct market basket analysis. By doing Market basket analysis, the sets of products that are often bought at the same time can be extracted. In market basket analysis, however, the effect of...
In this paper, we aimed to guide about latest development and studies about students' performance analysis and Learning Analytics in Massively Open Online Courses (MOOCs) for researchers related with the topics. For this purpose short review for usage of performance prediction and Learning Analytics in MOOCs is investigated In our study, to help readers get familiar with our topic, firstly literature...
The analysis of clinical pathways from event logs provides new insights about care processes. In this paper, we propose a new methodology to automatically perform simulation analysis of patients' clinical pathways based on a national hospital database. Process mining is used to build highly representative causal nets, which are then converted to state charts in order to be executed. A joint multi-agent...
Modular construction has been a widely used method for industrial construction in Alberta. Heavy piperack modules are prefabricated and assembled offsite and transported to site for installation, which minimizes the impact of Alberta's harsh weather and improves efficiency. Such projects are large in scale, ranging from hundreds of modules to thousands; because of this, project planning often requires...
As a result of the independence and the colonization endured by developing countries, most of their administrative procedures have been inherited from the colonial era. These procedures adapted to the colonizing countries, are complex for the African context. People in charge of their processing are not able to master it, take too much time to put them in practice and consider it as heavy for the...
The development of Internet is permanently increasing the number of documents and the volumes of data available and exchanged through the Web. This documentary information constitutes an interesting source for the decision-making analysis. Therefore, it is essential to provide decision-makers with efficient tools to analyze the textual data enclosed in documents. In this paper, first we present a...
This work proposes a robust model to analyse the structure of horse races based on 2D velocity vector information. This model is capable of detecting scene breaks, classifying the view of the contenders and extracting the trajectory of the contenders throughout the race. The performance of the system is tested over six video clips from two different broadcast sources. The performance analysis shows...
One of the main research problems in heterogeneous transfer learning is to determine whether a given source domain is effective in transferring knowledge to a target domain, and then to determine how much of the knowledge should be transferred from a source domain to a target domain. The main objective of this paper is to solve this problem by evaluating the relatedness among given domains through...
Sentiment analysis of online users has been attracting significant interests in both academics and industry, but is always challenging. In this paper, we propose an effective algorithm that can work with text streams and big text collections, without human supervision. This method is based on the state-of-the-art model, namely Aspect and Sentiment Unification Model (ASUM). Our method has several advantages...
We describe a novel framework for the discovery of underlying topics of a longitudinal collection of scholarly data, and the tracking of their lifetime and popularity over time. Unlike the social media or news data where the underlying topics evolve over time, the topic nuances in science result in new scientific directions to emerge. Therefore, we model the longitudinal literature data with a new...
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