2015 12th Web Information System and Application Conference (WISA)

11-13 Sept. 2015

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  • [Front cover]

    Publication Year: 2015, Page(s): C4
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  • [Title page i]

    Publication Year: 2015, Page(s): i
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  • [Title page iii]

    Publication Year: 2015, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2015, Page(s): iv
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  • Table of contents

    Publication Year: 2015, Page(s):v - ix
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  • Message from General Co-Chairs

    Publication Year: 2015, Page(s): x
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  • Message from Program Chairs

    Publication Year: 2015, Page(s): xi
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  • Conference Organization

    Publication Year: 2015, Page(s): xii
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  • Program Committee

    Publication Year: 2015, Page(s):xiii - xiv
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  • Reviewers

    Publication Year: 2015, Page(s):xv - xvi
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  • A Method for Latent-Friendship Recommendation Based on Community Detection in Social Network

    Publication Year: 2015, Page(s):3 - 8
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (494 KB) | HTML iconHTML

    The paper studies a method for recommendation based on community partition applying for user in social network. Firstly, the largest connected component in friend-relationship complex network are taken as the logic unit, and divide up the largest connected component into non-intersect kernel sub-network, the kernel sub-network based on The maximum complete sub-graph which has the mathematics found... View full abstract»

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  • A Collaborative Filtering Algorithm of Selecting Neighbors Based on User Profiles and Target Item

    Publication Year: 2015, Page(s):9 - 14
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (286 KB) | HTML iconHTML

    Without considering the difference in user profiles and user rated items, traditional User-Based collaborative filtering recommendation algorithm only considers the users' score on the item when calculates the similarity between users. In order to get rid of disadvantages of traditional methods, this paper proposes a collaborative filtering algorithm of selecting neighbors based on user profiles a... View full abstract»

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  • Friend Recommendation Algorithm Based on User Activity and Social Trust in LBSNs

    Publication Year: 2015, Page(s):15 - 20
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (335 KB) | HTML iconHTML

    In LBSNs (Location-based Social Networks), friend recommendation results are mainly decided by the number of common friends or depending on similar user preferences. However, lack of description of semantic information about user activity preferences, insufficiency in building social trust among user relationships and individual score ranking by a crowd or the person from third party of social net... View full abstract»

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  • Recommending Join Queries Based on Path Frequency

    Publication Year: 2015, Page(s):21 - 26
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (185 KB) | HTML iconHTML

    Real databases often consist of hundreds of innerlinked tables, which makes posing a complex join query a really hard task for common users. Join query recommendation is an effective technique to help users formulate better join queries and explore their information demand. In this paper, we propose a novel approach to automatically create join query recommendations based on path frequency. Our ap... View full abstract»

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  • Cross-Platform Instant Messaging System

    Publication Year: 2015, Page(s):27 - 30
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (638 KB) | HTML iconHTML

    Instant Messaging systems are widely used in social software, especially in the mobile Internet era. With the diversified and rapid development of mobile terminal, the systems play an important role in the mobile platform. In this paper, we introduce a kind of technology to implement the cross-platform instant messaging system, which through the HTTP protocol, XMPP protocol, TCP protocol and SSH, ... View full abstract»

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  • A Friend Recommendation Algorithm Based on Multiple Factors in LBSNs

    Publication Year: 2015, Page(s):31 - 36
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (234 KB) | HTML iconHTML

    In location-based social networks, the current friend recommendation algorithms just take a relatively single factor into account without comprehensive evaluations. To solve this problem, we design a framework - Multiple Heterogeneous Social Network (MHSN) according to users' profiles, check-in records and interests. Based on this framework, we propose a friend recommendation model which consider ... View full abstract»

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  • Popular Topic Detection in Chinese Micro-Blog Based on the Modified LDA Model

    Publication Year: 2015, Page(s):37 - 42
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (349 KB) | HTML iconHTML

    Micro-blog has become a symbol of the novel social media, and because of its rapid development in such a short time, many research researchers are full of enthusiasm about it. We take use of Latent Dirichlet Allocation (LDA) Model which has excellent dimension reduction capability and can excavate latent semantic from texts to discover popular topics. We improve the original LDA model to FSC-LDA m... View full abstract»

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  • Social Emotion Analysis System for Online News

    Publication Year: 2015, Page(s):43 - 48
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (480 KB) | HTML iconHTML

    Social emotion analysis of online users has become an important task for mining public opinions, which aims at detecting the readers' emotions evoked by online news articles. In this paper, we focus on building a social emotion analysis system (SEAS) for online news. The system has implemented a text data crawler for mainstream online news websites, the modules of document preprocessing, document ... View full abstract»

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  • Multi-source Emotion Tagging for Online News

    Publication Year: 2015, Page(s):49 - 52
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (184 KB) | HTML iconHTML

    With the rapid growth of social media and online news services, users nowadays can respond to online news by rating subjective emotions such as happiness, surprise or anger actively. Once the user ratings is over a certain range, it begins to show up a tendency of what most people think and feel, which can help us understand the preferences and perspectives of most users, and help news providers t... View full abstract»

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  • Emerging Rumor Identification for Social Media with Hot Topic Detection

    Publication Year: 2015, Page(s):53 - 58
    Cited by:  Papers (3)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (192 KB) | HTML iconHTML

    A rumor is commonly defined as a statement whose true value is unverifiable. As rumor can spread misinformation around people, causing social problems such as panic, and the rapid growth of online social media has made it possible for rumors to spread more quickly, it is important to automatically identify rumors for social media. Existing methods on rumor detection always concentrate on telling r... View full abstract»

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  • SLOF: Identify Density-Based Local Outliers in Big Data

    Publication Year: 2015, Page(s):61 - 66
    Cited by:  Papers (3)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (224 KB) | HTML iconHTML

    With the rapid progress in data mining and outlier detection, outlier detection methods have been widely used in various domains. The density based LOF method is the commonly used outlier detection method. In big data, the size and dimensions of data is very large, and the data is sparse. Those features make the LOF not suitable for big data. According to the features of big data, we propose a nov... View full abstract»

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  • Efficient Top-k Skyline Computation in MapReduce

    Publication Year: 2015, Page(s):67 - 70
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (169 KB) | HTML iconHTML

    Skyline is widely used in multi-objective decisionmaking, data visualization and other fields. With the rapid increasing of data volume, skyline of big data has also attracted more and more attention. However, skyline of big data has its own shortcomings. When the dimension increases, skyline results will be numerous, and we would like to select k points from the result sets. In this paper, we pro... View full abstract»

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  • A Nearby Vehicle Search Algorithm Based on HBase Spatial Index

    Publication Year: 2015, Page(s):71 - 74
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    Aiming to solve the nearby vehicle query problem in huge traffic data in the intelligent transportation field, we propose a nearby vehicle search algorithm based on HBase spatial index. Our algorithm builds an HBase spatial index model. It first takes column-oriented data as storage medium of huge traffic data. To build spatial index, it maps two dimensional traffic data of spatial location inform... View full abstract»

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  • Distributed Storage and Analysis of Massive Urban Road Traffic Flow Data Based on Hadoop

    Publication Year: 2015, Page(s):75 - 78
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (169 KB) | HTML iconHTML

    Because of the traditional methods failing to solve the efficient storage and analyze the problems with rapid growth of the massive traffic flow data, This paper adopts the distributed database HBase of Hadoop to store huge amounts of the urban road traffic flow data. By applying the distributed computing framework of MapReduce, statistical analysis of the traffic flow data is carried out. The exp... View full abstract»

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  • Towards Model Based Approach to Hadoop Deployment and Configuration

    Publication Year: 2015, Page(s):79 - 84
    Cited by:  Papers (2)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (382 KB) | HTML iconHTML

    Hadoop is an open source software framework of distributed processing of big data. There are many kinds of services in Hadoop ecosystem, such as HDFS, Map-Reduce, HBase, Hive, Yarn, Flume, Spark, Storm, Zookeeper, and so on, which increase the complexity of deployment and configuration. It takes plenty of time to construct a Hadoop cluster. Although there are some management tools which help admin... View full abstract»

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