Proceedings of the 19th ACM international conference on Information and knowledge management最新文献_第10页

Third workshop on exploiting semantic annotations in information retrieval (ESAIR): CIKM 2010 workshop 第三届信息检索中语义注释的开发研讨会:CIKM 2010研讨会

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871793

Jaap Kamps, Jussi Karlgren, Ralf Schenkel

{"title":"Third workshop on exploiting semantic annotations in information retrieval (ESAIR): CIKM 2010 workshop","authors":"Jaap Kamps, Jussi Karlgren, Ralf Schenkel","doi":"10.1145/1871437.1871793","DOIUrl":"https://doi.org/10.1145/1871437.1871793","url":null,"abstract":"There is an increasing amount of structure on the Web as a result of modern Web languages, user tagging and annotation, and emerging robust NLP tools. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing the depth of analysis of today's systems. Currently, we have only started exploring the possibilities and only begin to understand how these valuable semantic cues can be put to fruitful use. Unleashing the potential of semantic annotations requires us to think outside the box, by combining the insights of natural language processing (NLP) to go beyond bags of words, the insights of databases (DB) to use structure efficiently even when aggregating over millions of records, the insights of information retrieval (IR) in effective goal-directed search and evaluation, and the insights of knowledge management (KM) to get grips on the greater whole. The Workshop aims to bring together researchers from these different disciplines and work together on one of the greatest challenges in the years to come. The desired result of the workshop will be concrete insight into the potential of semantic annotations, and in concrete steps to take this research forward; synchronize related research happening in NLP, DB, IR, and KM, in ways that combine the strengths of each discipline; and have a lively, interactive workshop were everyone contributes and that inspires attendees to think \"outside the box\".","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127632566","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: 0

Comparison of six aggregation strategies to compute users' trustworthiness 计算用户可信度的六种聚合策略的比较

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871726

Pierpaolo Dondio, Stephen Barrett

引用次数: 1

Selected new training documents to update user profile 选择新的培训文档来更新用户配置文件

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871540

Abdulmohsen Algarni, Yuefeng Li, Yue Xu

{"title":"Selected new training documents to update user profile","authors":"Abdulmohsen Algarni, Yuefeng Li, Yue Xu","doi":"10.1145/1871437.1871540","DOIUrl":"https://doi.org/10.1145/1871437.1871540","url":null,"abstract":"Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122056387","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

Visual cube and on-line analytical processing of images 可视化立方体和图像的在线分析处理

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871546

Xin Jin, Jiawei Han, Liangliang Cao, Jiebo Luo, Bolin Ding, C. Lin

引用次数: 33

A framework for evaluating database keyword search strategies 评估数据库关键字搜索策略的框架

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871531

Joel Coffman, A. Weaver

引用次数: 134

Decomposing background topics from keywords by principal component pursuit 采用主成分追踪法对关键词进行背景主题分解

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871475

Kerui Min, Zhengdong Zhang, John Wright, Yi Ma

{"title":"Decomposing background topics from keywords by principal component pursuit","authors":"Kerui Min, Zhengdong Zhang, John Wright, Yi Ma","doi":"10.1145/1871437.1871475","DOIUrl":"https://doi.org/10.1145/1871437.1871475","url":null,"abstract":"Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools such as Principal Component Analysis or Latent Semantic Indexing (LSI) have been widely adopted for document modeling, analysis, and retrieval. In this paper, we contend that a more pertinent model for a document corpus as the combination of an (approximately) low-dimensional topic model for the corpus and a sparse model for the keywords of individual documents. For such a joint topic-document model, LSI or PCA is no longer appropriate to analyze the corpus data. We hence introduce a powerful new tool called Principal Component Pursuit that can effectively decompose the low-dimensional and the sparse components of such corpus data. We give empirical results on data synthesized with a Latent Dirichlet Allocation (LDA) mode to validate the new model. We then show that for real document data analysis, the new tool significantly reduces the perplexity and improves retrieval performance compared to classical baselines.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126925552","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: 96

Path-hop: efficiently indexing large graphs for reachability queries Path-hop:为可达性查询有效地索引大型图

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871457

Jing Cai, C. Poon

引用次数: 43

Summary of the 4th workshop on analytics for noisy unstructured text data (AND) 噪声非结构化文本数据(AND)分析第四届研讨会总结

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871788

Roberto Basili, D. Lopresti, Christoph Ringlstetter, Shourya Roy, K. Schulz, L. V. Subramaniam

引用次数: 0

Relational feature engineering of natural language processing 自然语言处理中的关系特征工程

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871709

Hamidreza Kobdani, Hinrich Schütze, A. Burkovski, W. Kessler, G. Heidemann

引用次数: 14

Understanding retweeting behaviors in social networks 理解社交网络中的转发行为

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871691

Zi Yang, Jingyi Guo, Keke Cai, Jie Tang, Juan-Zi Li, Li Zhang, Zhong Su

引用次数: 265