Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics最新文献_第9页

A methodology for community detection in Twitter 一种Twitter社区检测方法

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3117760

Wendel Silva, Á. Santana, F. Lobato, Márcia Pinheiro

{"title":"A methodology for community detection in Twitter","authors":"Wendel Silva, Á. Santana, F. Lobato, Márcia Pinheiro","doi":"10.1145/3106426.3117760","DOIUrl":"https://doi.org/10.1145/3106426.3117760","url":null,"abstract":"The microblogging service Twitter is one of the world's most popular online social networks and assembles a huge amount of data produced by interactions between users. A careful analysis of this data allows identifying groups of users who share similar traits, opinions, and preferences. We call community detection the process of user group identification, which grants valuable insights not available upfront. In order to extract useful knowledge from Twitter data many methodologies have been proposed, which define the attributes to be used in community detection problems by manual and empirical criteria - oftentimes guided by the aimed type of community and what the researcher attaches importance to. However, such approach cannot be generalized because it is well known that the task of finding out an appropriate set of attributes leans on context, domain, and data set. Aiming to the advance of community detection domain, reduce computational cost and improve the quality of related researches, this paper proposes a standard methodology for community detection in Twitter using feature selection methods. Results of the present research directly affect the way community detection methodologies have been applied to Twitter and quality of outcomes produced.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"116 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80732607","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: 33

Incorporating context and trends in news recommender systems 在新闻推荐系统中结合上下文和趋势

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3109433

A. Lommatzsch, B. Kille, S. Albayrak

引用次数: 25

A hybrid evolutionary algorithm for community detection 社区检测的混合进化算法

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106477

Fanzhen Liu, Zhengpeng Chen, Yali Cui, Chen Liu, Xianghua Li, Chao Gao

{"title":"A hybrid evolutionary algorithm for community detection","authors":"Fanzhen Liu, Zhengpeng Chen, Yali Cui, Chen Liu, Xianghua Li, Chao Gao","doi":"10.1145/3106426.3106477","DOIUrl":"https://doi.org/10.1145/3106426.3106477","url":null,"abstract":"Evolutionary algorithm belongs to the behaviorism which is one of major approaches to artificial intelligence. Community detection is one of the important applications of the evolutionary algorithm. Detecting the community structure, an essential property for complex networks, can help us understand the inherent functions of real systems. It has been proved that genetic algorithm (GA) is feasible for community detection, and yet existing GA-based community detection algorithms still need improving in terms of their robustness and accuracy. A Physarum-based network model (PNM) with an intelligence of recognizing inter-community edges based on a kind of multi-headed slime mold, has been proposed in the phase of GA's initialization for optimization. In this paper, integrated with PNM after three operators of GA during the process of community detection, a novel genetic algorithm, called P-GACD, is proposed to improve the efficiency of GA for community detection. In addition, some experiments are implemented in five real-world networks to evaluate the performance of P-GACD. The results reveal that P-GACD shows an advantage in terms of the robustness and accuracy, contrasted with the existing algorithms.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"314 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88593857","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

A knowledge-driven approach for personalized literature recommendation based on deep semantic discrimination 基于深度语义辨析的个性化文献推荐知识驱动方法

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3109439

Hongzhi Kuai, Jianzhuo Yan, Jianhui Chen, Yongchuan Yu, Haiyuan Wang, Ning Zhong

引用次数: 2

Waves: a model of collective learning 波浪:一个集体学习的模型

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106544

Lise-Marie Veillon, Gauvain Bourgne, H. Soldano

引用次数: 2

Studying toxic behavior influence and player chat in an online video game 研究在线视频游戏中的有毒行为影响和玩家聊天

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106452

Joaquim A. M. Neto, Kazuki Yokoyama, Karin Becker

引用次数: 34

Factors impacting employee engagement on enterprise social media 影响企业社交媒体员工敬业度的因素

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3115865

Prema Sankaran, Sankaran Bheeman, K. Hari Priya, Xujuan Zhou, R. Gururajan

引用次数: 2

An ensemble method for the credibility assessment of user-generated content 用户生成内容可信度评估的集成方法

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106464

Julien Fontanarava, G. Pasi, Marco Viviani

{"title":"An ensemble method for the credibility assessment of user-generated content","authors":"Julien Fontanarava, G. Pasi, Marco Viviani","doi":"10.1145/3106426.3106464","DOIUrl":"https://doi.org/10.1145/3106426.3106464","url":null,"abstract":"The Social Web supports and fosters social interactions by means of different social media, which allow the spread of the so called User-Generated Content (UGC). In this context, characterized by the absence of trusted third parties that verify the reliability of the sources and the believability of the content generated, the issue of assessing the credibility of the information diffused by means of social media is receiving increasing attention. In the literature, this issue has been mainly tackled as a classification problem; information is categorized into genuine and fake, usually by implementing or applying classifiers that consider multiple kinds of features (mainly textual and non-textual) to be evaluated in terms of credibility. In this article, unlike prior research, textual features are considered separately with respect to other kinds of features during the classification process. In particular, an Ensemble Method that combines the results produced by two text classifiers and the ones returned by another classifier acting on non-textual features is proposed. This allows to have better results with respect to the use of a single classifier on multiple features together. The effectiveness of the Ensemble Method has been assessed in the context of review sites, by means of a labeled dataset gathered from the Yelp.com site, where on-line reviews are already classified as recommended and not recommended.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91044464","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: 11

New technique to deal with verbose queries in social book search 处理社交图书搜索中冗长查询的新技术

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106481

Messaoud Chaa, O. Nouali, P. Bellot

引用次数: 7

Handling conflicts in uncertain ontologies using deductive argumentation 用演绎论证处理不确定本体中的冲突

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106454

A. Bouzeghoub, Saïd Jabbour, Yue Ma, Badran Raddaoui

{"title":"Handling conflicts in uncertain ontologies using deductive argumentation","authors":"A. Bouzeghoub, Saïd Jabbour, Yue Ma, Badran Raddaoui","doi":"10.1145/3106426.3106454","DOIUrl":"https://doi.org/10.1145/3106426.3106454","url":null,"abstract":"Ontologies can represent knowledge in a structured and formally well-understood way, which is crucial for information sharing. However, in practice, it is often difficult to have an error-free ontology. Conflicts can occur due to modeling errors or ontology merging and evolution. Moreover, uncertainty can happen because of modeling choices or the lack of confidence for a constructed ontology. Argumentation frameworks for knowledge bases reasoning and management have received extensive interests in the field of Artificial Intelligence in recent years. In this paper, we propose a unified framework to handle conflicts in uncertain ontologies with the use of deductive argumentation. Different from existing approaches, we introduce a stronger notion of conflict that covers both inconsistency and incoherence, where the latter is a special contradiction that can occur in an ontology. The unified approach spreads uncertainty degrees throughout argumentation trees and the enriched argument structure leads us to two novel inference relations. We then present a method to compute (counter)-arguments as well as argumentation trees in the context of uncertain ontologies based on the developments of three notions called minimal conflicting subontologies, maximal nonconflicting subontologies, and prudent justifications.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90496218","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: 4