{"title":"How do metrics of link analysis correlate to quality, relevance and popularity in wikipedia?","authors":"Raíza Hanada, Marco Cristo, M. G. Pimentel","doi":"10.1145/2526188.2526198","DOIUrl":"https://doi.org/10.1145/2526188.2526198","url":null,"abstract":"Many links between Web pages can be viewed as indicative of the quality and importance of the pages they pointed to. Accordingly, several studies have proposed metrics based on links to infer web page content quality. However, as far as we know, the only work that has examined the correlation between such metrics and content quality consisted of a limited study that left many open questions. In spite of these metrics having been shown successful in the task of ranking pages which were provided as answers to queries submitted to search engines, it is not possible to determine the specific contribution of factors such as quality, popularity, and importance to the results. This difficulty is partially due to the fact that such information is hard to obtain for Web pages in general. Unlike ordinary Web pages, the quality, importance and popularity of Wikipedia articles are evaluated by human experts or might be easily estimated. Thus, it is feasible to verify the relation between link analysis metrics and such factors in Wikipedia articles, our goal in this work. To accomplish that, we implemented several link analysis algorithms and compared their resulting rankings with the ones created by human evaluators regarding factors such as quality, popularity and importance. We found that the metrics are more correlated to quality and popularity than to importance, and the correlation is moderate.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122081497","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}
{"title":"Similarity evaluation in XML schema and XLink","authors":"Marta Mota, Paulo Caetano da Silva, Sidney Viana","doi":"10.1145/2526188.2526222","DOIUrl":"https://doi.org/10.1145/2526188.2526222","url":null,"abstract":"XML SCHEMA is a standard defined by W3C widely used in the specification of XML elements. Another standard by W3C is XML Linking Language (XLink), a language that specifies how elements should be declared in XML documents in order to define links between two or more resources. XLink and XML Schema are emerging Internet standards applied in varying contexts such as XBRL Language. Similarity evaluation is an important process in data management and serves as support for one of its core activity: duplicate detection. Thus, the classification of XML elements according to the similarity between them is becoming increasingly useful in the area of XML data management. This paper presents a process for similarity evaluation between XML elements defined with the use of XML Schema and XLink and an experiment. The experiment applies the proposed process to the context of the XBRL concepts, an example of XML elements created with extensive use of XML Schema and XLink.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130209996","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}
{"title":"Multimodal late fusion bag of features applied to scene detection","authors":"Bruno Lorenço Lopes, R. Goularte","doi":"10.1145/2526188.2526202","DOIUrl":"https://doi.org/10.1145/2526188.2526202","url":null,"abstract":"Recent advances in technology have increased the availability of video data, creating a strong requirement for efficient systems to manage those materials. To make efficient use of video information, first, the data has to be automatic segmented into smaller, manageable and understandable units, like scenes. This paper presents a new, multimodal video scene segmentation technique. The proposed approach is to combine Bag of Features based techniques (visual and aural) in order to explore the latent semantic obtained by them in complementary way, improving scene segmentation. The results achieved showed to be promising.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129789309","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}
P. Rego, Fabrício D. A. Lemos, Windson Viana, Fernando A. M. Trinta, J. Souza
{"title":"MapReduce performance evaluation for knowledge-based recommendation of context-tagged photos","authors":"P. Rego, Fabrício D. A. Lemos, Windson Viana, Fernando A. M. Trinta, J. Souza","doi":"10.1145/2526188.2530537","DOIUrl":"https://doi.org/10.1145/2526188.2530537","url":null,"abstract":"Recommendation systems are a subclass of information filtering systems that aims at helping users in retrieving information. Recently, contextual information proved to be effective in improving the quality of results of Recommender Systems. However, Context-aware Recommender Systems still suffer performance issues for real-time recommendation, mainly due to the amount of items that should be considered for recommendation. In this paper, we present an evaluation of using MapReduce and its integration with a mobile system for implementing a knowledge-based algorithm for context-aware recommendation. To be effective, this photo recommendation algorithm should work with a large set of images annotated with contextual information. The MapReduce algorithm parallelizes the processing required to generate the recommendation results and so improved the system performance. The results of performance analysis showed, for instance, that cloud-based version of the reccomendation reaches a speedup of 7x with a image base with more than 41 million photos.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133410797","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}
{"title":"MoveRC: attention-aware remote control","authors":"D. A. Chagas, E. Furtado","doi":"10.1145/2526188.2526235","DOIUrl":"https://doi.org/10.1145/2526188.2526235","url":null,"abstract":"The progress of information technology has made objects continuously acquire new resources and communication skills, therefore we have to change the way we interact with them. As the mainstream media of the twentieth century, television has also followed this trend. TV is changing from a passive medium, from which the viewer only receives information, into an active media, with which there is interaction facilitated by the option of choice, participation and even creating new content. However, the experience of interactive television is often barred by the problems inherent to dealing with the remote control. Especially, when it comes to a task, that is too complex to be done with a standard remote control: the task of putting data in text format into the TV. This paper presents an ongoing research that addresses the input of text data in digital television proposing an attention-aware system.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131921317","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}
{"title":"Enhancing the accuracy of ratings predictions of video recommender system by segments of interest","authors":"A. Dias, Leandro Krug Wives, V. Roesler","doi":"10.1145/2526188.2526201","DOIUrl":"https://doi.org/10.1145/2526188.2526201","url":null,"abstract":"The amount of video content that is available on the web grows at each instant. This fact implicates in an important issue -- video content overload. One way to treat such problem consists on the use of recommender systems. In this sense, this paper proposes a method to enhance the accuracy of the predictions given by video recommender systems by the use of Segments of Interest (SOI). Based on the premise that users tend to like particular segments of a video more than the entire video, and that they are able to mark these segments, these can be used to identify similar people, i.e. the ones who have similar interests about videos. This similarity can be used to enhance the accuracy of the ratings predictions of traditional collaborative video recommender systems. To evaluate this approach, an experimental evaluation was performed. The results showed that the accuracy improvement is directly related with the level of participation of people marking SOI. Thus, as more people collaborate and interact, better will be the recommendation result.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115326516","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}
{"title":"Evaluation of the influence of contextual factors on the interactions with applications for smartphones","authors":"A. H. Kronbauer, Celso A. S. Santos","doi":"10.1145/2526188.2526212","DOIUrl":"https://doi.org/10.1145/2526188.2526212","url":null,"abstract":"The development of methodologies and techniques to evaluate smartphones usability is an emerging topic in the scientific community and triggers discussions about which methodology is most appropriate. The lack of consensus is due to the inherent difficulty on capturing context data in the scenarios where the experiments take place and on relating them to the found results. This work aims to correlate potential usability problems in mobile applications with contextual factors that may occur during users interactions on different devices, such as: environment luminosity, device screen resolution, and the user's activity while interacting with the application. The following methodology was applied to carry out a field experiment: (1) identification of contextual factors that may influence users' interaction; (2) use of UXEProject Infrastructure to support the automatic capture of applications' context data, by monitoring and storing quantitative, subjective and contextual data from applications' use; (3) implementation of experiments with real users, which have different profiles, on using three different mobile applications over an one year period. In this paper, we present and discuss the results obtained during this study.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116536015","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}
{"title":"Video scene segmentation by improved visual shot coherence","authors":"T. H. Trojahn, R. Goularte","doi":"10.1145/2526188.2526206","DOIUrl":"https://doi.org/10.1145/2526188.2526206","url":null,"abstract":"Nowadays, there a increasing interest in video scene segmentation due huge amount of videos available through services like YouTube. Although there are some techniques which obtain relatively good precision and recall values when segmenting the video in scenes, they are somewhat limited because the high computational cost. A well know technique to accomplish video scene segmentation is the shot coherence model, which presents lower precision and recall than state of art methods, like machine learning and multimodality, but stands out for being simple. The improvement of the techniques based on shot coherence models could be beneficial to these state of the art segmentation methods.\u0000 That way, this paper presents a new technique for scene segmentation using shot coherence and optical flow features. The technique is presented and evaluated through a series of precision, recall and F1 values, obtaining results close or even better of those obtained by related works.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121243006","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}
Felipe Moraes, Marisa A. Vasconcelos, Patrick Prado, J. Almeida, Marcos André Gonçalves
{"title":"Polarity analysis of micro reviews in foursquare","authors":"Felipe Moraes, Marisa A. Vasconcelos, Patrick Prado, J. Almeida, Marcos André Gonçalves","doi":"10.1145/2526188.2526195","DOIUrl":"https://doi.org/10.1145/2526188.2526195","url":null,"abstract":"On Foursquare, one of the currently most popular location-based social networks, users can not only share which places (venues) they visit but also leave short comments (tips) about their previous experiences at specific venues. Tips may provide a valuable feedback for business owners as well as for potential new customers. Sentiment or polarity classification provides useful tools for opinion summarization, which can help both parties to quickly obtain a predominant view of the opinions posted by users at a specific venue. We here present what, to our knowledge, is the first study of polarity of Foursquare tips. We start by characterizing two datasets of collected tips with respect to their textual content. Some inherent characteristics of tips, such as short sizes as well as informal and often noisy content, pose great challenges to polarity detection. We then investigate the effectiveness of four alternative polarity classification strategies on subsets of our dataset. Three of the considered strategies are based on supervised machine learning techniques and the fourth one is an unsupervised lexicon-based approach. Our evaluation indicates that effective polarity classification can be achieved even if the simpler lexicon-based approach, which does not require costly manual tip labeling, is adopted.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128094713","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}
{"title":"Modeling, characterizing and recommendation in multimedia web content services","authors":"Diego Duarte, A. Pereira, C. Davis","doi":"10.1145/2526188.2526227","DOIUrl":"https://doi.org/10.1145/2526188.2526227","url":null,"abstract":"Web content has gained much importance lately. One of the most important content types is online video, as demonstrated by the success of platforms such as YouTube. The growth in the volume of available online video is also observed in corporate scenarios, such as TV networks. This paper evaluates a set of corporate online videos hosted by Sambatech, a company that holds the largest platform for online multimedia content distribution in Latin America. We propose a novel analytical approach for video recommendation, focusing on video objects being consumed, and not on consumer profile data. After modeling this service, we characterize the contents from multiple sources, and propose techniques for video recommendation. Experimental results indicate that the proposed method obtains a gain of about 42% in precision for a set of five recommendations, as compared to a baseline that is based only on video metadata.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127448794","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}