2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA)

28-30 Sept. 2016

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  • [Front cover]

    Publication Year: 2016, Page(s):c1 - c4
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  • [Title page]

    Publication Year: 2016, Page(s): v
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  • [Copyright notice]

    Publication Year: 2016, Page(s): vi
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  • Preface

    Publication Year: 2016, Page(s): vii
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    It is our pleasure to introduce you to the Proceedings of the International Conference on Knowledge Engineering and Applications (ICKEA 2016) held in NTU, Singapore on September 28–30, 2016. Interest in knowledge engineering as well as its applications has remarkably increased in recent years. Novel solutions of complex knowledge technology, such as advanced knowledge technologies, knowledg... View full abstract»

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  • Committees

    Publication Year: 2016, Page(s):viii - ix
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  • Table of contents

    Publication Year: 2016, Page(s):iii - vi
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  • Author index

    Publication Year: 2016, Page(s):261 - 262
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  • A modified Support Vector Clustering method for document categorization

    Publication Year: 2016, Page(s):1 - 5
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (380 KB) | HTML iconHTML

    In this paper, we propose a novel text categorization method based on modified Support Vector Clustering (SVC). SVC is a density based clustering approach, which handles the arbitrary shape clusters effectively. The main drawback of traditional SVC is that it treats unclassified documents as outliers. To overcome this problem, we employed Fuzzy C-Means (FCM) to cluster unclassified documents. The ... View full abstract»

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  • A method for generating fixing rules from constant conditional functional dependencies

    Publication Year: 2016, Page(s):6 - 11
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (893 KB) | HTML iconHTML

    A variety of data dependencies have been proposed for data cleaning, including conditional functional dependencies, editing rules and so on. Fixing rule is a newly proposed class of data dependencies for data repairing with high accuracy. However, to our knowledge, algorithms for automatically designing fixing rules have not been developed. In this paper, a workflow of generating fixing rules has ... View full abstract»

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  • Does information uncertainty moderate the impact of investors' emotion on stock prices?

    Publication Year: 2016, Page(s):12 - 17
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (598 KB) | HTML iconHTML

    Prior studies point out information uncertainty (IU) of a stock comes from investors' overconfidence. However, overconfidence is hard to be measured. After our collections and reviews of prior studies regarding IU, we propose stock returns are affected by investors' sentiment, and this relation is moderated by IU. We use SentimentAnalyzer system, a text mining technology, to analyze the posts in a... View full abstract»

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  • A novel hybrid method for time series subsequence join

    Publication Year: 2016, Page(s):18 - 22
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB) | HTML iconHTML

    The exact method JOCOR, proposed by Mueen et al., is the first method for joining two time series on subsequence correlation. Although JOCOR requires the time complexity O(n2lgn), where n is the length of the time series, it is still time-consuming even for medium-size time series. In this paper, we propose a hybrid method which can run faster than JOCOR. Our method consists of four mai... View full abstract»

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  • Mining inter-transaction recurring patterns in time series

    Publication Year: 2016, Page(s):23 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (763 KB) | HTML iconHTML

    Mining recurring patterns plays an important role in finding regularities for particular time intervals within a time series. Most existing methods on recurring pattern search typically focus on finding the patterns that exhibit temporal associations among items within a transaction (timestamp). However, present methods for mining recurring patterns are not expressive enough to capture recurring e... View full abstract»

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  • The analysis and design of the job recommendation model based on GBRT and time factors

    Publication Year: 2016, Page(s):29 - 35
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1178 KB)

    In this paper, we first give a comprehensive summary of models and algorithms applied in three online job recommender systems and point out the advantages and disadvantages of these models. Then we introduce a job recommendation model based on Gradient Boosting Regression Tree and time factors (T-GBRT). The T-GBRT model aggregates the time factors into the GBRT to predict personal preferences and ... View full abstract»

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  • WSLA extensions for managing composite semantic Web Services

    Publication Year: 2016, Page(s):36 - 40
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (359 KB) | HTML iconHTML

    Managing Service Level Agreement (SLA) for composite semantic web services is a very complex process, as it involves many complex tasks such as components discovery, provisioning, monitoring, recovery, and coordination. Indeed, managing all these tasks manually is a very cumbersome operation, nevertheless it is time consuming and prone to errors. To overcome such problems, automated SLA management... View full abstract»

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  • Study on Science and Technology Policy trend using text network analysis in Korea

    Publication Year: 2016, Page(s):41 - 45
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (743 KB) | HTML iconHTML

    As the social impact of science and technology is increasing day by day, it is increasing the importance of science and technology policy. The Third Science and Technology Basic Plan, which is to be the basis of Korea Science and Technology Policy, will be established in 2013. There is need to investigate the value-oriented and policy priorities of the Science and Technology Basic Plan. The purpos... View full abstract»

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  • A performance-satisfied and affection-aware MapReduce allocation scheme for intelligent information applications

    Publication Year: 2016, Page(s):46 - 51
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (527 KB) | HTML iconHTML

    Intelligent information applications (e.g. healthcare, business data mining, etc.) usually involve the processing of a huge amount of data. MapReduce can speed up the execution of the application (job) with big data by dividing the job into a number of concurrently running map and reduce tasks in cloud computing systems. With many MapReduce jobs in the systems, it is required to efficiently alloca... View full abstract»

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  • People counting base on head and shoulder information

    Publication Year: 2016, Page(s):52 - 55
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (619 KB) | HTML iconHTML

    This paper presents an application for counting the people who pass through the supervised area. Instead of traditional camera, this study used Kinect 2 to get the depth information of image. The processes of our approach includes preprocessing, candidate detection, tracking, identification and people counting. In the preprocessing stage, the foreground object was sliced by depth information to ma... View full abstract»

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  • An expert system for risk assessment of information system security based on ISO 27002

    Publication Year: 2016, Page(s):56 - 61
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (992 KB) | HTML iconHTML

    Information system security in a company is an important element that every company should pay more attention due to the attacks against the security of the data that may not be inevitable. Probably every company knows how to protect their data even though this paper proposes something new which is more efficient. One of the ways that can be used to determine the security status of the company is ... View full abstract»

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  • Event scheduling with soft constraints and on-demand re-optimization

    Publication Year: 2016, Page(s):62 - 66
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (734 KB) | HTML iconHTML

    With the increased use of today's information technologies, more people are using electronic calendaring systems, such as Outlook, to schedule everyday events. This includes work related items such as meetings as well as personal items such as birthdays and their kids' events. There have been no significant changes to this process. People enter their personal event items on their calendars. If som... View full abstract»

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  • Combining MeSH Thesaurus with UMLS in pseudo relevance feedback to improve biomedical information retrieval

    Publication Year: 2016, Page(s):67 - 71
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (554 KB) | HTML iconHTML

    With the rapid increase in the volume of biomedical publications, developing an efficient search strategy to retrieve relevant biomedical documents that match the user search intention is a tremendous challenge. This paper proposes a novel pseudo relevance feedback technique which combines MeSH terms and UMLS concepts to improve the performance of retrieving biomedical documents from MEDLINE. The ... View full abstract»

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  • E-commerce business strategy analysis and inspiration: Taking Taobao as an example

    Publication Year: 2016, Page(s):72 - 77
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (497 KB) | HTML iconHTML

    Taobao is a network retailer which founded in May 2003 and now is the most popular online retail platform in China with nearly 500 million registered users. More than 60 million people visit Taobao everyday and over 48000 items are sold every minute on this platform. During the expansion progress, Taobao has transformed from a C2C network market into a worldwide E-commerce trading platform includi... View full abstract»

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  • Efficient sentiment classification of Twitter feeds

    Publication Year: 2016, Page(s):78 - 82
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (390 KB) | HTML iconHTML

    Sentiment Analysis encompasses the use of Natural Language Processing together with statistics and machine learning methods for the identification, extraction and characterization of sentiment elements from a body of text. Micro-blog platforms, such as Twitter, allows for the sharing of real-time comments and opinions from millions of users on various topics. This research presents an experiment t... View full abstract»

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  • Correlating tweets with the daily return reversal of the US stock market

    Publication Year: 2016, Page(s):83 - 87
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (925 KB) | HTML iconHTML

    In the stock market, return reversal happens generally due to the fact that investors sell overbought stocks or buy oversold stocks, reversing the stocks' prices. In this paper, we aim at exploring correlations between tweets (posts on Twitter) and the daily return reversal of the US stock market. First, we employ dynamical Bayesian factor graph to depict dynamic interrelationships among a compreh... View full abstract»

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  • A supervised method for ranking reviews based on latent structure features

    Publication Year: 2016, Page(s):88 - 92
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB) | HTML iconHTML

    Previous research on reviews ranking has two branches: supervised method and unsupervised method. In this paper, we propose a supervised method to predict the review's importance, and the latent structure features are used to represent the review's writing styles. Our method mainly consists of three stages: Extracting lexical features to represent the review's lexical structure; Using lexical feat... View full abstract»

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  • Evolving long-term dependency rules in lifelong learning models

    Publication Year: 2016, Page(s):93 - 97
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (532 KB) | HTML iconHTML

    Topic models are extensively used for text analysis to extract prominent concepts as topics in a large collection of documents about a subject domain. They are extended with different approaches to suit various application areas. Automatic knowledge-based topic models are recently introduced to specifically meet the processing needs of large-scale data having many subject domains. The model automa... View full abstract»

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