Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics最新文献_第6页

Paid review and paid writer detection 付费评论和付费作者检测

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106433

Man-Chun Ko, Hen-Hsen Huang, Hsin-Hsi Chen

引用次数: 4

Enhancing crowd wisdom using measures of diversity computed from social media data 使用从社交媒体数据中计算的多样性措施来增强人群智慧

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106491

Shreyansh P. Bhatt, B. Minnery, Srikanth Nadella, B. Bullemer, V. Shalin, A. Sheth

{"title":"Enhancing crowd wisdom using measures of diversity computed from social media data","authors":"Shreyansh P. Bhatt, B. Minnery, Srikanth Nadella, B. Bullemer, V. Shalin, A. Sheth","doi":"10.1145/3106426.3106491","DOIUrl":"https://doi.org/10.1145/3106426.3106491","url":null,"abstract":"\"Wisdom of Crowds\" (WoC) refers to a form of collective intelligence in which the aggregate judgment of a group of individuals is, in most instances, superior to that of any one group member. For a crowd to be wise, its members must possess diverse knowledge and viewpoints. Such diversity leads to uncorrelated judgment errors that cancel out in aggregate. Yet despite the fact that diversity is known to be an essential ingredient in WoC, little research aims to measure and exploit diversity in human social systems for the purpose of maximizing crowd intelligence. Here we quantify the diversity of a group of individuals through semantic analysis of their social media (Twitter) communications. Focusing on the domain of fantasy sports, we show that virtual crowds of fantasy team owners selected based on the diversity of their tweet content can outperform both non-diverse and randomly sampled crowds. Our results suggest a new approach for intelligent crowd assembly in which measures of diversity extracted from online social media communications can guide the selection of crowd members. These results have implications for numerous domains that utilize aggregated judgments - from consumer reviews, to econometrics, to geopolitical forecasting and intelligence analysis.","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":"88750037","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

Extracting attribute-value pairs from product specifications on the web 从web上的产品规格中提取属性值对

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106449

P. Petrovski, Christian Bizer

{"title":"Extracting attribute-value pairs from product specifications on the web","authors":"P. Petrovski, Christian Bizer","doi":"10.1145/3106426.3106449","DOIUrl":"https://doi.org/10.1145/3106426.3106449","url":null,"abstract":"Comparison shopping portals integrate product offers from large numbers of e-shops in order to support consumers in their buying decisions. Product offers often consist of a title and a free-text product description, both describing product attributes that are considered relevant by the specific vendor. In addition, product offers might contain structured or semi-structured product specifications in the form of HTML tables and HTML lists. As product specifications often cover more product attributes than free-text descriptions, being able to extract attribute-value pairs from these specifications is a critical prerequisite for achieving good results in tasks such as product matching, product categorisation, faceted product search, and product recommendation. In this paper, we present an approach for extracting attribute-value pairs from product specifications on the Web. We use supervised learning to classify the HTML tables and HTML lists within a web page as product specification or not. In order to extract attribute-value pairs from the HTML fragments identified by the specification detector, we again use supervised learning to classify columns as attribute column or value column. Compared to DEXTER, the current state-of-the-art approach for extracting attribute-value pairs from product specifications, we introduce several new features for specification detection and support the extraction of attribute-value pairs from specifications having more than two columns. This allows us to improve the F-score up to 10% for extracting attribute-value pairs from tables and up to 3% for lists. In addition, we report the results of using duplicate-based schema matching to align the product attribute schemata of 32 different e-shops. This experiment confirms the suitability of duplicate-based schema matching for product data integration.","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":"84868417","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: 22

Social analytics framework for intelligent information systems based on a complex adaptive systems approach 基于复杂自适应系统方法的智能信息系统社会分析框架

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3109430

Somayeh Koohborfardhaghighi, J. Altmann, K. Tserpes

引用次数: 1

Quantitative style analysis of Mo Yan and Zhang Wei's novels 莫言、张维小说的数量风格分析

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3109045

Yunxuan Li, Weiyun Ji, Dekuan Xu

引用次数: 1

Matcher composition for identification of subsumption relations in ontology matching 本体匹配中包含关系识别的匹配器组合

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106503

A. Vennesland

引用次数: 7

Analysing the behaviour of online investors in times of geopolitical distress: a case study on war stocks 分析地缘政治危机时期网上投资者的行为:以战争股票为例

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106510

Pierpaolo Dondio, J. Usher

{"title":"Analysing the behaviour of online investors in times of geopolitical distress: a case study on war stocks","authors":"Pierpaolo Dondio, J. Usher","doi":"10.1145/3106426.3106510","DOIUrl":"https://doi.org/10.1145/3106426.3106510","url":null,"abstract":"In this paper we analysed how the behavior of an online financial community changed in times of geopolitical crises. In particular, we studied the behaviour and communication patterns of online investors before and after a military geopolitical event. We selected a set of 23 key-events belonging to the 2003 US-led invasion of Iraq, the Arab Spring and the first period of the Ukraine crisis, and we restricted our study to a set of eight so called war stocks. We studied the resilience of the community to information shocks by comparing the community composition, its sentiment and users' communication networks before and after an event at different time intervals. We found how community reaction is governed by ordered patterns. Experimental evidence suggested how in the after-math of an event the community did not lose its information sharing functionality. Communication networks showed a higher in-degree Gini index, connectivity and a rich-club effect. Discussions developed around central users acting as hubs. These backbone users were present both before and after an event, their sentiment were less volatile than other users, and they were previously recognized as local experts of a specific stock. As a further evidence of community resilience, the equilibrium of all the indicators analysed were restored after two weeks.","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":"91432665","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: 1

Inferring your expertise from Twitter: combining multiple types of user activity 从Twitter推断你的专长:结合多种类型的用户活动

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106468

Yu Xu, Dong Zhou, S. Lawless

引用次数: 4

Robust spread of cooperation by expectation-of-cooperation strategy with simple labeling method 基于简单标记法的合作期望策略的鲁棒合作扩展

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3106458

Tomoaki Otsuka, T. Sugawara

引用次数: 2

Data mining in IoT: data analysis for a new paradigm on the internet 物联网中的数据挖掘:互联网新范式的数据分析

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2017-08-23 DOI: 10.1145/3106426.3115866

Peter Wlodarczak, Mustafa A. Ally, J. Soar

{"title":"Data mining in IoT: data analysis for a new paradigm on the internet","authors":"Peter Wlodarczak, Mustafa A. Ally, J. Soar","doi":"10.1145/3106426.3115866","DOIUrl":"https://doi.org/10.1145/3106426.3115866","url":null,"abstract":"This paper provides an overview on Data Mining (DM) technologies for the Internet of Things (IoT). IoT has become an active area of research, since IoT promises among other to improve quality of live and safety in Smart Cities, to make resource supply and waste management more efficient, and optimize traffic. DM is highly domain specific and depends on what is being mined for. For instance, if IoT is used to optimize traffic in a Smart City to reduce traffic jams and to find parking spaces quicker, different types of data needs to be collected and analysed from an eHealth solution, where IoT is used in a Smart Home to monitor the well being of patients or elderly people. IoT connects things that can collect numeric data from smart sensors, streaming data from cameras or route information on maps. Depending on the type of data, different techniques need to be adopted to analyse them. Also, many IoT applications analyse data from different devices and correlate them to make predictions about possible machine failures in production sites or looming emergency situations in Smart Buildings in a home security application. DM techniques need to handle the heterogeneity of IoT data, the large volumes of data and the speed at which they are produced. This paper explores the state of the art DM techniques for IoT.","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":"85164134","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: 14