Proceedings of the 21st ACM international conference on Information and knowledge management最新文献_第4页

DUBMMSM'12: international workshop on data-driven user behavioral modeling and mining from social media 社交媒体数据驱动的用户行为建模与挖掘国际研讨会[j]

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398751

J. Mahmud, James Caverlee, Jeffrey Nichols, J. O'Donovan, Michelle X. Zhou

{"title":"DUBMMSM'12: international workshop on data-driven user behavioral modeling and mining from social media","authors":"J. Mahmud, James Caverlee, Jeffrey Nichols, J. O'Donovan, Michelle X. Zhou","doi":"10.1145/2396761.2398751","DOIUrl":"https://doi.org/10.1145/2396761.2398751","url":null,"abstract":"Massive amounts of data are being generated on social media sites, such as Twitter and Facebook. This data can be used to better understand people, such as their personality traits, perceptions, and preferences, and predict their behavior. This deeper understanding of users and their behaviors can benefit a wide range of intelligent applications, such as advertising, social recommender systems, and personalized knowledge management. These applications will also benefit individual users themselves by optimizing their experiences across a wide variety of domains, such as retail, healthcare, and education. Since mining and understanding user behavior from social media often requires interdisciplinary effort, including machine learning, text mining, human-computer interaction, and social science, our workshop aims to bring together researchers and practitioners from multiple fields to discuss the creation of deeper models of individual users by mining the content that they publish and the social networking behavior that they exhibit.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114770250","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

Author-conference topic-connection model for academic network search 学术网络搜索的作者-会议-主题连接模型

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398597

Jianwen Wang, Xiaohua Hu, Xinhui Tu, Tingting He

{"title":"Author-conference topic-connection model for academic network search","authors":"Jianwen Wang, Xiaohua Hu, Xinhui Tu, Tingting He","doi":"10.1145/2396761.2398597","DOIUrl":"https://doi.org/10.1145/2396761.2398597","url":null,"abstract":"This paper proposes a novel topic model, Author-Conference Topic-Connection (ACTC) Model for academic network search. The ACTC Model extends the author-conference-topic (ACT) model by adding subject of the conference and the latent mapping information between subjects and topics. It simultaneously models topical aspects of papers, authors and conferences with two latent topic layers: a subject layer corresponding to conference topic, and a topic layer corresponding to the word topic. Each author would be associated with a multinomial distribution over subjects of conference (eg., KM, DB, IR for CIKM 2012), the conference(CIKM 2012), and the topics are respectively generated from a sampled subject. Then the words are generated from the sampled topics. We conduct experiments on a data set with 8,523 authors, 22,487 papers and 1,243 conferences from the well-known Arnetminer website, and train the model with different number of subjects and topics. For a qualitative evaluation, we compare ACTC with three others models LDA, Author-Topic (AT) and ACT in academic search services. Experiments show that ACTC can effectively capture the semantic connection between different types of information in academic network and perform well in expert searching and conference searching.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127770067","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: 18

Theme chronicle model: chronicle consists of timestamp and topical words over each theme 主题编年史模型:编年史由时间戳和每个主题的主题词组成

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398573

N. Kawamae

引用次数: 6

MAGIK: managing completeness of data MAGIK:管理数据的完整性

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398741

Ognjen Savkovic, Paramita Mirza, Sergey Paramonov, W. Nutt

引用次数: 9

CloST: a hadoop-based storage system for big spatio-temporal data analytics CloST:基于hadoop的大时空数据分析存储系统

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398589

Haoyu Tan, Wuman Luo, L. Ni

{"title":"CloST: a hadoop-based storage system for big spatio-temporal data analytics","authors":"Haoyu Tan, Wuman Luo, L. Ni","doi":"10.1145/2396761.2398589","DOIUrl":"https://doi.org/10.1145/2396761.2398589","url":null,"abstract":"During the past decade, various GPS-equipped devices have generated a tremendous amount of data with time and location information, which we refer to as big spatio-temporal data. In this paper, we present the design and implementation of CloST, a scalable big spatio-temporal data storage system to support data analytics using Hadoop. The main objective of CloST is to avoid scan the whole dataset when a spatio-temporal range is given. To this end, we propose a novel data model which has special treatments on three core attributes including an object id, a location and a time. Based on this data model, CloST hierarchically partitions data using all core attributes which enables efficient parallel processing of spatio-temporal range scans. According to the data characteristics, we devise a compact storage structure which reduces the storage size by an order of magnitude. In addition, we proposes scalable bulk loading algorithms capable of incrementally adding new data into the system. We conduct our experiments using a very large GPS log dataset and the results show that CloST has fast data loading speed, desirable scalability in query processing, as well as high data compression ratio.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121795093","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: 66

On compressing weighted time-evolving graphs 关于压缩加权时间演化图

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398630

Wei Liu, Andrey Kan, Jeffrey Chan, J. Bailey, C. Leckie, J. Pei, K. Ramamohanarao

{"title":"On compressing weighted time-evolving graphs","authors":"Wei Liu, Andrey Kan, Jeffrey Chan, J. Bailey, C. Leckie, J. Pei, K. Ramamohanarao","doi":"10.1145/2396761.2398630","DOIUrl":"https://doi.org/10.1145/2396761.2398630","url":null,"abstract":"Existing graph compression techniquesmostly focus on static graphs. However for many practical graphs such as social networks the edge weights frequently change over time. This phenomenon raises the question of how to compress dynamic graphs while maintaining most of their intrinsic structural patterns at each time snapshot. In this paper we show that the encoding cost of a dynamic graph is proportional to the heterogeneity of a three dimensional tensor that represents the dynamic graph. We propose an effective algorithm that compresses a dynamic graph by reducing the heterogeneity of its tensor representation, and at the same time also maintains a maximum lossy compression error at any time stamp of the dynamic graph. The bounded compression error benefits compressed graphs in that they retain good approximations of the original edge weights, and hence properties of the original graph (such as shortest paths) are well preserved. To the best of our knowledge, this is the first work that compresses weighted dynamic graphs with bounded lossy compression error at any time snapshot of the graph.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115861310","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: 28

Constructing test collections by inferring document relevance via extracted relevant information 通过提取相关信息推断文档的相关性来构建测试集合

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2396783

Shahzad Rajput, Matthew Ekstrand-Abueg, Virgil Pavlu, J. Aslam

引用次数: 15

Do ads compete or collaborate?: designing click models with full relationship incorporated 广告是竞争还是合作?:设计包含完整关系的点击模型

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398528

Xin Xin, Irwin King, Ritesh Agrawal, Michael R. Lyu, Heyan Huang

引用次数: 1

Exploiting enriched contextual information for mobile app classification 利用丰富的上下文信息进行移动应用程序分类

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398484

Hengshu Zhu, Huanhuan Cao, Enhong Chen, Hui Xiong, Jilei Tian

引用次数: 76

Cager: a framework for cross-page search 跨页面搜索的框架

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398733

Zhumin Chen, Byron J. Gao, Qi Kang

引用次数: 0