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

Visual pollution localization through crowdsourcing and visual similarity clustering 基于众包和视觉相似聚类的视觉污染定位

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022662

Zuzana Kucharikova, Jakub Simko

{"title":"Visual pollution localization through crowdsourcing and visual similarity clustering","authors":"Zuzana Kucharikova, Jakub Simko","doi":"10.1109/SMAP.2017.8022662","DOIUrl":"https://doi.org/10.1109/SMAP.2017.8022662","url":null,"abstract":"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 crowdsourcing. Smart mobile devices can support this process through localization sensors. However, these sensors are inaccurate enough on their own, plus, the media are not located exactly where the volunteers capture them. Therefore, the media localization is presently inaccurate. This paper presents a work-in-progress method to improve the localization of physical advertisement media. As input, the method takes captured media images along with spatial information about the device. The images are then clustered based on their locations, to form sets corresponding to the true physical media. Then, using visual analysis of the images and spatial orientation of devices, the method computes expected location of the physical media.","PeriodicalId":441461,"journal":{"name":"2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125826023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Sentiment analysis of social network posts in Slovak language 斯洛伐克语社交网络帖子的情感分析

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022661

Rastislav Krchnavy, Marián Simko

引用次数: 13

High-performance and lightweight real-time deep face emotion recognition 高性能、轻量级的实时深度人脸情感识别

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022671

Justus Schwan, E. Ghaleb, E. Hortal, S. Asteriadis

引用次数: 12

A survey on political event analysis in Twitter 推特上的政治事件分析调查

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022660

Michalis Korakakis, E. Spyrou, Phivos Mylonas

{"title":"A survey on political event analysis in Twitter","authors":"Michalis Korakakis, E. Spyrou, Phivos Mylonas","doi":"10.1109/SMAP.2017.8022660","DOIUrl":"https://doi.org/10.1109/SMAP.2017.8022660","url":null,"abstract":"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 fellow data mining researchers that came into sight over the last few months. Herein, we start by presenting a brief overview of our motivation and continue with basic information on the Twitter platform, which constitutes two clearly identifiable components, namely as an online news source and as one of the most popular social networking sites. Focus is then given to research works dealing with sentiment analysis in political topics and opinion polls, whereas we continue by reviewing the Twittersphere from the computational social science point of view, by including behavior analysis, social interaction and social influence identification methods and by discerning and discriminating its useful types within the social network, thus envisioning possible further utilization scenarios for the collected information. A short discussion on the identified conclusions and a couple of future research directions concludes the survey.","PeriodicalId":441461,"journal":{"name":"2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128192876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Using social networks to predict changes in health: Extended abstract 利用社会网络预测健康变化:扩展摘要

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022659

Karen S. Jung, O. Tonguz

引用次数: 0

Towards adaptive brain-computer interfaces: Improving accuracy of detection of event-related potentials 面向自适应脑机接口:提高事件相关电位检测的准确性

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-09 DOI: 10.1109/SMAP.2017.8022664

Róbert Móro, Patrik Berger, M. Bieliková

{"title":"Towards adaptive brain-computer interfaces: Improving accuracy of detection of event-related potentials","authors":"Róbert Móro, Patrik Berger, M. Bieliková","doi":"10.1109/SMAP.2017.8022664","DOIUrl":"https://doi.org/10.1109/SMAP.2017.8022664","url":null,"abstract":"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 potentials (ERPs), which can be a hard task because of the noise in the signal, especially when using affordable consumer-oriented devices, such as Emotiv Epoc. In the paper, we present a method of EEG signal processing and classification for detection of ERP P300 wave. We particularly focus on the adaptive channel selection and propose to use genetic algorithm combined with linear discriminant analysis to determine the optimal subset of electrodes for signal processing for each individual user. We evaluated our proposed method on a standard data set outperforming the existing approaches even with decreasing size of a training set. In addition, we conducted a user study with Emotiv Epoc device on a standard P300 Speller task in order to compare the results of our method and to find out, whether this device is suitable for P300 detection.","PeriodicalId":441461,"journal":{"name":"2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116909698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Feature extraction for tweet classification: Do the humans perform better? 推文分类的特征提取:人类表现更好吗?

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-01 DOI: 10.1109/SMAP.2017.8022667

N. Tsapatsoulis, Constantinos Djouvas

{"title":"Feature extraction for tweet classification: Do the humans perform better?","authors":"N. Tsapatsoulis, Constantinos Djouvas","doi":"10.1109/SMAP.2017.8022667","DOIUrl":"https://doi.org/10.1109/SMAP.2017.8022667","url":null,"abstract":"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 extensively applied the last few years. Sentiment analysis of Twitter data presents important challenges compared to the similar task of text classification. Tweets are limited to 140 characters; thus, the conveyed message is compressed and often context-dependent. The tweets are informal and unstructured, usually lacking grammatical soundness and use of a standard lexicon. On the other hand, tweets are usually annotated by their authors regarding their topic and sentiment with the aid of hashtags and emoticons. Identifying appropriate features for sentiment analysis of tweets remains an open research area since text indexing methods face the sparseness problem while POS tagging methods fail due to the lack of grammatical structure of tweets. Character based features, i.e., n-grams of characters, are currently getting popular because they are language independent. However, their effectiveness remains quite low. In this paper, we argue that tokens used by humans for sentiment analysis of tweets are probably the best feature set one can use for that purpose. We compare several automatically extracted features with the features (tokens) used by humans for tweet classification, under a machine learning framework. The results show that the manually indicated tokens combined with a Decision Tree classifier outperform any other feature set-classification algorithm combination. The manually annotated dataset that was used in our experiments is publicly available for anyone who wishes to use it.","PeriodicalId":441461,"journal":{"name":"2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115414358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Efficient big data analysis on a single machine using apache spark and self-organizing map libraries 使用apache spark和自组织地图库在单机上进行高效的大数据分析

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-01 DOI: 10.1109/SMAP.2017.8022657

David Andresic, Petr Šaloun, Ioannis Anagnostopoulos

引用次数: 1

Customer language processing: Extended abstract 客户语言处理:扩展抽象

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-01 DOI: 10.1109/SMAP.2017.8022663

A. Metzmacher, V. Heinrichs, B. Falk, R. Schmitt

引用次数: 2

Exploiting relevant dates to promote serendipity and situational curiosity in cultural heritage experiences 利用相关日期促进文化遗产体验中的意外发现和情境好奇心

2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) Pub Date : 2017-07-01 DOI: 10.1109/SMAP.2017.8022673

Ahmed Dahroug, Martín López Nores, J. Pazos-Arias, Silvia González-Soutelo, S. Reboreda-Morillo, Angeliki Antoniou

{"title":"Exploiting relevant dates to promote serendipity and situational curiosity in cultural heritage experiences","authors":"Ahmed Dahroug, Martín López Nores, J. Pazos-Arias, Silvia González-Soutelo, S. Reboreda-Morillo, Angeliki Antoniou","doi":"10.1109/SMAP.2017.8022673","DOIUrl":"https://doi.org/10.1109/SMAP.2017.8022673","url":null,"abstract":"Cultural heritage is typically not on the people's top lists when searching for entertainment activities. Publicized temporary exhibitions can draw many visitors to a museum, urged by the opportunity of seeing certain items, but in general there are no particular stimuli and the visits are postponed once and again, if not forever. In this paper, we argue that it is possible to instigate curiosity in relation to dates, periods and events that are relevant to the potential visitors and connected to the cultural heritage items in direct or subtle ways. Likewise, proper reasoning about dates can improve the experiences of actual visitors, by promoting serendipitous learning, increasing retention and revealing that subsequent visits may drive them around the venue following new appealing narratives. We present the outline of a recommender system grounded on rich semantic modeling of relevant dates in the user profiles, in the cultural heritage knowledge bases and in an almanac of important days, connected to keywords and/or historical events and characters. We also explain how this system is going to be used in the pilot experiments of the CROSSCULT EU project, starting in September 2017.","PeriodicalId":441461,"journal":{"name":"2017 12th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125658561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2