2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)

9-10 July 2017

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  • [Front cover]

    Publication Year: 2017, Page(s): 1
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  • [Title page]

    Publication Year: 2017, Page(s):1 - 3
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  • Table of contents

    Publication Year: 2017, Page(s):v - vii
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  • Preface

    Publication Year: 2017, Page(s):ix - x
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  • Preface to the special session on multimodal affective analysis for human-machine interfaces and learning environments

    Publication Year: 2017, Page(s):xi - xii
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  • Preface to the special session on personalized delivery of cultural heritage content

    Publication Year: 2017, Page(s): xiii
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  • SMAP steering committee

    Publication Year: 2017, Page(s): xv
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  • SMAP programme committee

    Publication Year: 2017, Page(s):xvii - xviii
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  • SMAP initiative and character

    Publication Year: 2017, Page(s): xix
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  • Conceptualization of social big data: Keynote

    Publication Year: 2017, Page(s):xxi - xxii
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (336 KB)

    Nowadays, much of the social interaction is mediated by the various forms of the social online services. This has led to emergence of extensive amounts of human-generated data with the rich semantics and large potential for diverse personal, commercial and societal applications. In this paper, we will provide the conceptualization of Social Big Data from three perspectives: at first, we will defin... View full abstract»

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  • Efficient big data analysis on a single machine using apache spark and self-organizing map libraries

    Publication Year: 2017, Page(s):1 - 5
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (183 KB) | HTML iconHTML

    Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers wit... View full abstract»

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  • Detecting genuinely read parts of web documents

    Publication Year: 2017, Page(s):6 - 11
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (635 KB) | HTML iconHTML

    In this paper, we propose a method for detecting genuinely read parts of documents based on gaze data from eye tracker. This work deals with the possibilities of identifying user interaction with (web-based) documents. Our algorithm takes into account user's eye fixation information and maps their coordinates onto word-level elements. These are then processed with respect to their relative word di... View full abstract»

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  • Using social networks to predict changes in health: Extended abstract

    Publication Year: 2017, Page(s):12 - 13
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (406 KB) | HTML iconHTML

    Social networking sites not only have billions of users but detailed content about each individual's daily life. This detailed information about a person's life could be exploited to allow individuals to learn more about themselves. In this paper, we introduce the concept of using social networks to foresee changes in an individual's health. We develop a new model that can predict if a person has ... View full abstract»

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  • A survey on political event analysis in Twitter

    Publication Year: 2017, Page(s):14 - 19
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (122 KB) | HTML iconHTML

    This short survey paper attempts to provide an overview of the most recent research works on the popular politics domain within the framework of the Twitter social network. Given both the political turmoil that arouse at the end of 2016 and early 2017, and the increasing popularity of social networks in general, and Twitter, in particular, we feel that this topic forms an attractive candidate for ... View full abstract»

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  • Sentiment analysis of social network posts in Slovak language

    Publication Year: 2017, Page(s):20 - 25
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (794 KB) | HTML iconHTML

    In this paper we tackle the issue of sentiment analysis of social network posts in a not well targeted language - Slovak. There is a significant lack of research in this area for minor languages, as they often introduce additional language-specific issues for text processing. In case of Slovak, common issues are high flection, complex morphology and syntax. User-generated content of social network... View full abstract»

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  • Visual pollution localization through crowdsourcing and visual similarity clustering

    Publication Year: 2017, Page(s):26 - 31
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1247 KB) | HTML iconHTML

    Nowadays, many cities and communes suffer from advertisements appearing on aesthetically inappropriate or illegal places. This contamination of public space is called visual pollution. The first step in the fight against visual pollution is localization of physical advertising media (e.g., billboards) as accurately as is possible. One of the ways is to use volunteer effort through outdoor crowdsou... View full abstract»

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  • Customer language processing: Extended abstract

    Publication Year: 2017, Page(s):32 - 33
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    The research presented is the first working step towards the goal of developing a domain-independent method for sentiment analysis of German customer feedback in social media. The approach proposes to apply the concept of natural language processing (NLP) to customer language processing (CLP). In this context we hypothesize an indifference in annotator ability in assigning customer reviews of tang... View full abstract»

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  • Towards adaptive brain-computer interfaces: Improving accuracy of detection of event-related potentials

    Publication Year: 2017, Page(s):34 - 39
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1024 KB) | HTML iconHTML

    Electroencefalography (EEG) has a wide range of applications in human-computer interaction and in adaptation and personalization of the interfaces. It can be used either as a sensor, e.g., for emotion detection, or as an input device that allows to take actions based on the brain's response to the presented stimuli. For the latter, it is crucial to be able to reliably detect event-related potentia... View full abstract»

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  • Predicting the evolution of communities in social networks using structural and temporal features

    Publication Year: 2017, Page(s):40 - 45
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (409 KB) | HTML iconHTML

    During the last years, there is increasing interest in analyzing social networks and modeling their dynamics at different scales. This work focuses on predicting the future form of communities, which represent the mesoscale structure of networks, while the communities arise as a result of user interaction. We employ several structural and temporal features to represent communities, along with thei... View full abstract»

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  • Forecasting elections from VAA data: What the undecided would vote?

    Publication Year: 2017, Page(s):46 - 52
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (299 KB) | HTML iconHTML

    In many Voting Advice Applications (VAAs) a supplementary question concerning the voting intention of a VAA user is included. The data that are collected through this question can serve a variety of purposes, election forecast being one of them. However, it appears that the majority of VAA users who answer this question select safe choices such as “I prefer not to say” and “I ... View full abstract»

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  • Feature extraction for tweet classification: Do the humans perform better?

    Publication Year: 2017, Page(s):53 - 58
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (270 KB) | HTML iconHTML

    Sentiment analysis of Twitter data became a research trend the last decade. Thanks to the Twitter API, massive amounts of tweets, relating to a topic of interest, can be collected in real time. Performing sentiment analysis of these tweets can be used to conduct social sensing and opinion mining. For instance, forecasting elections is a primary area in which sentiment analysis of tweets has been e... View full abstract»

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  • A density based algorithm for community detection in hyper-networks

    Publication Year: 2017, Page(s):59 - 64
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (368 KB) | HTML iconHTML

    We propose an efficient community detection algorithm for networks that comprise more than one entities, such as users, tags and items, with ternary or higher relations between them. Such networks are also known as multi-partite and can be used for representing social tagging systems but also the activity in streaming media. Detecting communities in multi-paritite networks entails different challe... View full abstract»

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  • Personalized query expansion utilizing multi-relational social data

    Publication Year: 2017, Page(s):65 - 70
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (775 KB) | HTML iconHTML

    Social tagging systems have been widely used as a way to annotate and categorize Web resources. However, users often use unrestricted vocabulary to tag and describe resources. On the contrast, annotators of Web documents may use very different words to describe the same concept. In the past few years, numerous personalized query expansion methods have been proposed to tackle the vocabulary mismatc... View full abstract»

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  • Affect state recognition for adaptive human robot interaction in learning environments

    Publication Year: 2017, Page(s):71 - 75
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (216 KB) | HTML iconHTML

    Previous studies of robots used in learning environments suggest that the interaction between learner and robot is able to enhance the learning procedure towards a better engagement of the learner. Moreover, intelligent robots can also adapt their behavior during a learning process according to certain criteria resulting in increasing cognitive learning gains. Motivated by these results, we propos... View full abstract»

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  • High-performance and lightweight real-time deep face emotion recognition

    Publication Year: 2017, Page(s):76 - 79
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (928 KB) | HTML iconHTML

    Deep learning is used for all kinds of tasks which require human-like performance, such as voice and image recognition in smartphones, smart home technology, and self-driving cars. While great advances have been made in the field, results are often not satisfactory when compared to human performance. In the field of facial emotion recognition, especially in the wild, Convolutional Neural Networks ... View full abstract»

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