2017 14th Web Information Systems and Applications Conference (WISA)

11-12 Nov. 2017

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  • [Title page i]

    Publication Year: 2017, Page(s): i
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  • [Title page iii]

    Publication Year: 2017, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2017, Page(s): iv
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  • Table of contents

    Publication Year: 2017, Page(s):v - ix
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  • Message from General Chairs

    Publication Year: 2017, Page(s): x
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  • Message from Program Committee Chairs

    Publication Year: 2017, Page(s): xi
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  • Conference Organization

    Publication Year: 2017, Page(s): xii
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  • Program Committee

    Publication Year: 2017, Page(s):xiii - xv
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  • A Precise Marketing Algorithm Based on Topic Community for New Media Platform

    Publication Year: 2017, Page(s):1 - 6
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (354 KB) | HTML iconHTML

    New media platforms, including the network community, microblogging, WeChat, live show platform, have become the main platforms and channels for information dissemination and diffusion, at the same time, these platforms are also favored by the majority of merchants, and how to use these new media platforms for precise marketing is an urgent problem. This paper proposes a precise marketing algorith... View full abstract»

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  • A Domain-Independent Multi-modifier Entity Search Method

    Publication Year: 2017, Page(s):7 - 12
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (395 KB) | HTML iconHTML

    Entity search is a new search pattern that return related entities to users rather than amounts of web pages containing mass and messy information. It is also a challenging research topic because it is difficult to understand the meaning of users' input and identify the entities from the messy web pages. In this paper, we propose an entity search pattern based on online encyclopedias and define it... View full abstract»

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  • Efficient Time Series Classification via Sparse Linear Combination

    Publication Year: 2017, Page(s):13 - 18
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (193 KB) | HTML iconHTML

    Time series classification presents a specific machine learning challenge due to the ordering of variables. Recent studies show that the simple nearest neighbor classifier with elastic distance measures is hard to beat and many researchers focus on alternative distance measures. Unlike nearest neighbor classifier try to find a training sample which has the minimum distance with test instance, we u... View full abstract»

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  • Research on Short-Time Prediction of Dynamical Local Replanning Route Guidance Method Based on HMM

    Publication Year: 2017, Page(s):19 - 22
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (595 KB) | HTML iconHTML

    The insufficient real-time responses, accuracy and intelligence have become key issues in the practical application of traffic guidance information services. This paper addresses these issues by proposing a new dynamic route guidance method. It firstly establishes a concurrent global route search method. By using this method, multiple relative static shortest routes can be searched, and then the s... View full abstract»

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  • A Method of the Association Statistics between the Cause of Action and the Statutes

    Publication Year: 2017, Page(s):23 - 26
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (528 KB) | HTML iconHTML

    This paper presents a method of the association statistics between the cause of action and the statute. According to the close relationship between the cause of action and the statute in the written judgment, this paper puts forward the statistical analysis of the cause of action and the statute. The method mainly includes the pretreatment of semi-structured written judgments, reading information ... View full abstract»

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  • Microblogging User Tag Prediction Based on Bayesian

    Publication Year: 2017, Page(s):27 - 32
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (756 KB) | HTML iconHTML

    In the social network, to users, the tag is an important basis to mark and classify the resource. The tag of microblogging users can be used for advertising and network marketing. This paper presents a method based on naive Bayesian to predict the user tag. We use the user's basic attributes and some popular public tags as the features in Bayesian to predict whether a public tag belongs to a user.... View full abstract»

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  • Improving Search Result Clustering by Enriching Snippets with Word2Vec Model

    Publication Year: 2017, Page(s):33 - 37
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (521 KB) | HTML iconHTML

    Search Result Clustering (SRC) is an approach to solve the problems of web search engines under user's broad or ambiguous queries and no clues to find exact information in a long returned list. SRC groups the returned list and outputs a semantic structured organization to help users to find the desired information quickly. In a general way, the search engine results consist of concise information(... View full abstract»

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  • Research on Anomaly Pattern Detection in Hydrological Time Series

    Publication Year: 2017, Page(s):38 - 43
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (430 KB) | HTML iconHTML

    The abnormal patterns in hydrological time series play an important role in the analysis and decision-making. Aiming at the problems that the amount of hydrological data is large and there is a lot of “noise” in this data, which lead to the high time complexity of traditional anomaly detection algorithm, we propose anomaly pattern detection based on density for hydrological time series. Firstly, t... View full abstract»

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  • Caching-Aware Techniques for Query Workload Partitioning in Parallel Search Engines

    Publication Year: 2017, Page(s):44 - 49
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (615 KB) | HTML iconHTML

    In this work, we propose efficient query workload partition techniques to reduce processing times of queries in parallel search engines. Existing methods cannot offer both high cache hit ratios and caching-aware load balance of the system. Aiming to solve this problem, we propose effective solutions to capture tradeoff between the cache hit ratio and load balance to reduce the total query processi... View full abstract»

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  • Online Map Matching Algorithm Using Segment Angle Based on Hidden Markov Model

    Publication Year: 2017, Page(s):50 - 55
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (333 KB) | HTML iconHTML

    The Global Positioning System(GPS) is used to find a specific point on the real earth although GPS positioning technology is becoming more and more mature, GPS always exists with equipment inherent errors or measurement methods errors. so map matching step is a very important preprocessing for lots of applications, such as traffic flow control, taxi mileage calculation, and finding some people. Ho... View full abstract»

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  • Mining Frequent Intra-Sequence and Inter-Sequence Patterns Using Bitmap with a Maximal Span

    Publication Year: 2017, Page(s):56 - 61
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (336 KB) | HTML iconHTML

    Frequent intra-sequence pattern mining and inter-sequence pattern mining are both important ways of association rule mining for different applications. However, most algorithms focus on just one of them, as attempting both is usually inefficient. To address this deficiency, FIIP-BM, a Frequent Intra-sequence and Inter-sequence Pattern mining algorithm using Bitmap with a maxSpan is proposed. FIIP-... View full abstract»

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  • Mining Frequent Patterns for Item-Oriented and Customer-Oriented Analysis

    Publication Year: 2017, Page(s):62 - 67
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (263 KB)

    Frequent pattern mining can well extract insight from transaction patterns, and it is a desired capability for fully understanding the customer's purchase behavior. However, most of the algorithms are focus on the transverse relationship and the longitudinal analysis is missed. To address this defect, FP-ICA, a Frequent Pattern mining algorithm for Item-oriented and Customer-oriented Analysis is p... View full abstract»

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  • Topic Analysis and Influential Paper Discovery on Scientific Publications

    Publication Year: 2017, Page(s):68 - 73
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (1001 KB) | HTML iconHTML

    With the development of scientific research, scientific publications are valuable resources for new-comers in the research field. But massive scientific publications make it a challenge for researchers diving into a new research field. As a good practice to this problem, topics are put forward to organize publications. In this paper, we propose two modified LDA topic models as solutions to topic a... View full abstract»

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  • Building Top-k Consistent Results for Web Table Augmentation

    Publication Year: 2017, Page(s):74 - 79
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (487 KB) | HTML iconHTML

    Web table augmentation enables users to augment attributes based on key column and other known information. For table augmentation, most of systems return a single result which could not meet the users' needs of selection and validation. Furthermore, previous works only consider the entity-attribute binary tables with the first column corresponding to the entity name and the second to an attribute... View full abstract»

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  • Extracting Log Patterns Based on Association Analysis for Power Quality Disturbance Detection

    Publication Year: 2017, Page(s):80 - 83
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (280 KB) | HTML iconHTML

    To detect anomalies according to system log is a hot topic recently. For the harmonic monitoring system of the power grid, the common practice of anomaly detection is to conduct machine learning. The learning model is trained with the historical anomaly data, and used for online detection. The premise of this method is to predefine a set of indicators as the input features of the machine learning ... View full abstract»

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  • A Proactive Data Service Model to Encapsulating Stream Sensor Data into Service

    Publication Year: 2017, Page(s):84 - 89
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (572 KB) | HTML iconHTML

    Abnormality Detection in power plant is a typical IoT application which aims to identify anomalies in these routinely collected monitoring sensor data; intend to help detect possible faults in the equipment. However, on the development of abnormality detection, we find that there are three challenges. The first one is the lack of cooperation between sensors. It means that the physical sensors cann... View full abstract»

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  • An IoT System Design for Blind

    Publication Year: 2017, Page(s):90 - 92
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (242 KB) | HTML iconHTML

    In this paper, we propose and design a IOT system that includes wearing glass and walking assistant for the blind people to guide them in daily life. Both the wearing glass design and walking assistant design falls into the scope of internet of things(IOT) design. Firstly, both the wearing glass and walking assistant are illuminated in function design and layout design. Secondly, the diagram of al... View full abstract»

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