Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics最新文献_第2页

GENESIS: a generic RDF data access interface GENESIS:通用的RDF数据访问接口

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106514

Timofey Ermilov, Diego Moussallem, Ricardo Usbeck, A. N. Ngomo

引用次数: 5

A graph based approach to scientific paper recommendation 基于图的科学论文推荐方法

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106479

M. Amami, R. Faiz, Fabio Stella, G. Pasi

引用次数: 34

Machine learning is better than human to satisfy decision by majority 机器学习比人类更能满足多数人的决策

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106520

S. Hirokawa, Takahiko Suzuki, Tsunenori Mine

{"title":"Machine learning is better than human to satisfy decision by majority","authors":"S. Hirokawa, Takahiko Suzuki, Tsunenori Mine","doi":"10.1145/3106426.3106520","DOIUrl":"https://doi.org/10.1145/3106426.3106520","url":null,"abstract":"Government 2.0 activities have become very attractive and popular these days. Using platforms to support the activities, anyone can anytime report issues or complaints in a city with their photographs and geographical information on the Web, and share them with other people. Since a variety of reports are posted, officials in the city management section have to check the importance of each report and sort out their priorities to the reports. However, it is not easy task to judge the importance of the reports. When several officials work on the task, the agreement rate of their judgments is not always high. Even if the task is done by only one official, his/her judgment sometimes varies on a similar report. To remedy this low agreement rate problem of human judgments, we propose a method of detecting signs of danger or unsafe problems described in citizens' reports. The proposed method uses a machine learning technique with word feature selection. Experimental results clearly explain the low agreement rate of human judgments, and illustrate that the proposed machine learning method has much higher performance than human judgments.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78082652","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: 9

Information evolution modeling and tracking in social media 社交媒体中的信息演化建模与跟踪

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106443

E. Shabunina, G. Pasi

引用次数: 0

Haste makes waste: a case to favour voting bots 欲速则不达:一个支持投票机器人的案例

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106532

David Ben Yosef, L. Dery, S. Obraztsova, Zinovi Rabinovich, M. Bannikova

引用次数: 6

AQUAMan: QoE-driven cost-aware mechanism for SaaS acceptability rate adaptation AQUAMan: SaaS可接受率调整的qos驱动的成本意识机制

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106485

A. Najjar, Yazan Mualla, O. Boissier, Gauthier Picard

{"title":"AQUAMan: QoE-driven cost-aware mechanism for SaaS acceptability rate adaptation","authors":"A. Najjar, Yazan Mualla, O. Boissier, Gauthier Picard","doi":"10.1145/3106426.3106485","DOIUrl":"https://doi.org/10.1145/3106426.3106485","url":null,"abstract":"As more interactive and multimedia-rich applications are migrating to the cloud, end-user satisfaction and her Quality of Experience (QoE) will become a determinant factor to secure success for any Software as a Service (SaaS) provider. Yet, in order to survive in this competitive market, SaaS providers also need to maximize their Quality of Business (QoBiz) and minimize costs paid to cloud providers. However, most of the existing works in the literature adopt a provider-centric approach where the end-user preferences are overlooked. In this article, we propose the AQUAMan mechanism that gives the provider a fine-grained QoE-driven control over the service acceptability rate while taking into account both end-users' satisfaction and provider's QoBiz. The proposed solution is implemented using a multi-agent simulation environment. The results show that the SaaS provider is capable of attaining the predefined acceptability rate while respecting the imposed average cost per user. Furthermore, the results help the SaaS provider identify the limits of the adaptation mechanism and estimate the best average cost to be invested per user.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81680932","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

Solving DCSP problems in highly degraded communication environments 解决高降级通信环境下的DCSP问题

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106445

Saeid Samadidana, R. Mailler

{"title":"Solving DCSP problems in highly degraded communication environments","authors":"Saeid Samadidana, R. Mailler","doi":"10.1145/3106426.3106445","DOIUrl":"https://doi.org/10.1145/3106426.3106445","url":null,"abstract":"Although there have been tremendous gains in network communication reliability, many real world applications of distributed systems still face message loss, limitations, delay, and corruption. Yet despite this fact, most Distributed Constraint Satisfaction (DCSP) protocols assume that communication is perfect (messages that are sent will be received) although not ideal (not in a timely manner). As a result, many protocols are designed to exploit this assumption and are severely impacted when applied to real world conditions. This study compares the performance of several leading DCSP protocols including the Distributed Stochastic Algorithm (DSA), Distributed Breakout Algorithm (DBA), Max-Gain Message (MGM) and Distributed Probabilistic Protocol (DPP) to analyse their behaviour in communication degraded environments. The analysis begins by comparing the performance of all of the protocols in a perfect communication environment. We then use a simulated communication degraded environment where messages are probabilistically lost. Finally, we compare their performance by limiting the communication rate, which introduces delay. We show that DBA, once modified with a message timeout, is quite resistant to high message loss while DPP and DSA converge slower onto worse solutions. Our results also show that the setting of timeout value for DBA and MGM is an important factor in the convergence of these algorithms. Under conditions of message delay, DPP and DSA are less affected than DBA and MGM. Overall, DPP and DSA cause considerably less network load.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79800771","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

Using re-ranking to boost deep learning based community question retrieval 利用重新排序促进深度学习社区问题检索

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106442

K. Ghosh, Plaban Kumar Bhowmick, Pawan Goyal

引用次数: 6

MRR MRR

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106444

Vinicius Woloszyn, H. D. Dos Santos, Leandro Krug Wives, Karin Becker

{"title":"MRR","authors":"Vinicius Woloszyn, H. D. Dos Santos, Leandro Krug Wives, Karin Becker","doi":"10.1145/3106426.3106444","DOIUrl":"https://doi.org/10.1145/3106426.3106444","url":null,"abstract":"The automatic detection of relevant reviews plays a major role in tasks such as opinion summarization, opinion-based recommendation, and opinion retrieval. Supervised approaches for ranking reviews by relevance rely on the existence of a significant, domain-dependent training data set. In this work, we propose MRR (Most Relevant Reviews), a new unsupervised algorithm that identifies relevant revisions based on the concept of graph centrality. The intuition behind MRR is that central reviews highlight aspects of a product that many other reviews frequently mention, with similar opinions, as expressed in terms of ratings. MRR constructs a graph where nodes represent reviews, which are connected by edges when a minimum similarity between a pair of reviews is observed, and then employs PageRank to compute the centrality. The minimum similarity is graph-specific, and takes into account how reviews are written in specific domains. The similarity function does not require extensive pre-processing, thus reducing the computational cost. Using reviews from books and electronics products, our approach has outperformed the two unsupervised baselines and shown a comparable performance with two supervised regression models in a specific setting. MRR has also achieved a significantly superior run-time performance in a comparison with the unsupervised baselines.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81794341","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

The Adressa dataset for news recommendation 新闻推荐的addressa数据集

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3109436

J. Gulla, Lemei Zhang, Peng Liu, Özlem Özgöbek, Xiaomeng Su

引用次数: 138