Proceedings of the 19th ACM international conference on Information and knowledge management最新文献_第3页

Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting 行星图像中陨石坑的自动检测:一个使用特征选择和增强的嵌入式框架

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871534

W. Ding, T. Stepinski, L. Bandeira, R. Vilalta, Youxi Wu, Zhenyu Lu, Tianyu Cao

{"title":"Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting","authors":"W. Ding, T. Stepinski, L. Bandeira, R. Vilalta, Youxi Wu, Zhenyu Lu, Tianyu Cao","doi":"10.1145/1871437.1871534","DOIUrl":"https://doi.org/10.1145/1871437.1871534","url":null,"abstract":"Identifying impact craters on planetary surfaces is one fundamental task in planetary science. In this paper, we present an embedded framework on auto-detection of craters, using feature selection and boosting strategies. The paradigm aims at building a universal and practical crater detector. This methodology addresses three issues that such a tool must possess: (i) it utilizes mathematical morphology to efficiently identify the regions of an image that can potentially contain craters; only those regions, defined as crater candidates, are the subjects of further processing; (ii) it selects Haar-like image texture features in combination with boosting ensemble supervised learning algorithms to accurately classify candidates into craters and non-craters; (iii) it uses transfer learning, at a minimum additional cost, to enable maintaining an accurate auto-detection of craters on new images, having morphology different from what has been captured by the original training set. All three aforementioned components of the detection methodology are discussed, and the entire framework is evaluated on a large test image of 37,500 x 56,250$ m2 on Mars, showing heavily cratered Martian terrain characterized by nonuniform surface morphology. Our study demonstrates that this methodology provides a robust and practical tool for planetary science, in terms of both detection accuracy and efficiency.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"90 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":"121446244","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: 21

Accelerating probabilistic frequent itemset mining: a model-based approach 加速概率频繁项集挖掘:基于模型的方法

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871494

Liang Wang, Reynold Cheng, Sau-dan. Lee, D. Cheung

{"title":"Accelerating probabilistic frequent itemset mining: a model-based approach","authors":"Liang Wang, Reynold Cheng, Sau-dan. Lee, D. Cheung","doi":"10.1145/1871437.1871494","DOIUrl":"https://doi.org/10.1145/1871437.1871494","url":null,"abstract":"Data uncertainty is inherent in emerging applications such as location-based services, sensor monitoring systems, and data integration. To handle a large amount of imprecise information, uncertain databases have been recently developed. In this paper, we study how to efficiently discover frequent itemsets from large uncertain databases, interpreted under the Possible World Semantics. This is technically challenging, since an uncertain database induces an exponential number of possible worlds. To tackle this problem, we propose a novel method to capture the itemset mining process as a Poisson binomial distribution. This model-based approach extracts frequent itemsets with a high degree of accuracy, and supports large databases. We apply our techniques to improve the performance of the algorithms for: (1) finding itemsets whose frequentness probabilities are larger than some threshold; and (2) mining itemsets with the k highest frequentness probabilities. Our approaches support both tuple and attribute uncertainty models, which are commonly used to represent uncertain databases. Extensive evaluation on real and synthetic datasets shows that our methods are highly accurate. Moreover, they are orders of magnitudes faster than previous approaches.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"33 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113933722","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: 83

Support elements in graph structured schema reintegration 支持图结构模式整合中的元素

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871621

Xun Sun, R. Pottinger, Michael K. Lawrence

引用次数: 0

Detecting product review spammers using rating behaviors 使用评级行为检测产品评论垃圾邮件发送者

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871557

Ee-Peng Lim, Viet-An Nguyen, Nitin Jindal, B. Liu, Hady W. Lauw

引用次数: 802

Index structures for efficiently searching natural language text 用于有效搜索自然语言文本的索引结构

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871527

P. Chubak, Davood Rafiei

引用次数: 6

Online update of b-trees 在线更新b树

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871460

Marina Barsky, Alex Thomo, Zoltán Tóth, C. Zuzarte

{"title":"Online update of b-trees","authors":"Marina Barsky, Alex Thomo, Zoltán Tóth, C. Zuzarte","doi":"10.1145/1871437.1871460","DOIUrl":"https://doi.org/10.1145/1871437.1871460","url":null,"abstract":"Many scenarios impose a heavy update load on B-tree indexes in modern databases. A typical case is when B-trees are used for indexing all the keywords of a text field. For example upon the insertion of a new text record (e.g. a new document arrives), a barrage of new keywords has to be inserted into the index causing many random disk I/Os and interrupting the normal operation of the database. The common approach has been to collect the updates in a separate structure and then perform a batch update of the index. This update \"freezes\" the database. Many applications, however, require the immediate availability of the new updates without any interruption of the normal database operation. In this paper we present a novel online B-tree update method based on a new buffering data structure we introduce - Dynamic Bucket Tree (DBT). The DBT-buffer serves as a differential index for new updates. The grouping of keys in DBT-buffer is based on the longest common prefixes (LCP) of their binary representations. The LCP is used as a measure of the locality of keys to be transferred to the main B-tree. Our online update system does not slow down concurrent user transactions or lead to degradation of search performance. Experiments confirm that our DBT buffer can be efficiently used for online updates of text fields. As such it represents an effective solution to the notorious problem of handling updates to an Inverted Index.","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":"131064529","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

Using various term dependencies according to their utilities 根据它们的实用程序使用不同的术语依赖关系

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871655

Lixin Shi, Jian-Yun Nie

引用次数: 20

Exploring and visualizing academic social networks 探索和可视化学术社会网络

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871786

V. Ganev, Zhaochen Guo, Diego Serrano, Denilson Barbosa, Eleni Stroulia

引用次数: 2

Selecting keywords for content based recommendation 为内容推荐选择关键字

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871665

Christian Wartena, Wout Slakhorst, M. Wibbels

引用次数: 19

A topical link model for community discovery in textual interaction graph 文本交互图中社区发现的主题链接模型

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871686

Guoqing Zheng, Jinwen Guo, Lichun Yang, Shengliang Xu, Shenghua Bao, Zhong Su, Dingyi Han, Yong Yu

引用次数: 4