Proceedings of the 19th ACM international conference on Information and knowledge management最新文献_第6页

i-SEE: integrated stream execution environment over on-line data streams i-SEE:在线数据流的集成流执行环境

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871784

S. Shin, H. Park, Ho Jin Woo, W. Lee

引用次数: 0

Collaborative future event recommendation 协同未来事件推荐

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871542

Einat Minkov, B. Charrow, J. Ledlie, S. Teller, T. Jaakkola

{"title":"Collaborative future event recommendation","authors":"Einat Minkov, B. Charrow, J. Ledlie, S. Teller, T. Jaakkola","doi":"10.1145/1871437.1871542","DOIUrl":"https://doi.org/10.1145/1871437.1871542","url":null,"abstract":"We demonstrate a method for collaborative ranking of future events. Previous work on recommender systems typically relies on feedback on a particular item, such as a movie, and generalizes this to other items or other people. In contrast, we examine a setting where no feedback exists on the particular item. Because direct feedback does not exist for events that have not taken place, we recommend them based on individuals' preferences for past events, combined collaboratively with other peoples' likes and dislikes. We examine the topic of unseen item recommendation through a user study of academic (scientific) talk recommendation, where we aim to correctly estimate a ranking function for each user, predicting which talks would be of most interest to them. Then by decomposing user parameters into shared and individual dimensions, we induce a similarity metric between users based on the degree to which they share these dimensions. We show that the collaborative ranking predictions of future events are more effective than pure content-based recommendation. Finally, to further reduce the need for explicit user feedback, we suggest an active learning approach for eliciting feedback and a method for incorporating available implicit user cues.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"15 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":"125598584","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: 107

Yet another write-optimized DBMS layer for flash-based solid state storage 又一个写优化的DBMS层，用于基于闪存的固态存储

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871617

Hongchan Roh, D. Lee, Sanghyun Park

引用次数: 1

A new mathematics retrieval system 一种新的数学检索系统

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871635

Shahab Kamali, Frank Wm. Tompa

引用次数: 27

A comparison of user and system query performance predictions 用户和系统查询性能预测的比较

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871562

C. Hauff, D. Kelly, L. Azzopardi

{"title":"A comparison of user and system query performance predictions","authors":"C. Hauff, D. Kelly, L. Azzopardi","doi":"10.1145/1871437.1871562","DOIUrl":"https://doi.org/10.1145/1871437.1871562","url":null,"abstract":"Query performance prediction methods are usually applied to estimate the retrieval effectiveness of queries, where the evaluation is largely system sided. However, little work has been conducted to understand query performance prediction from the user's perspective. The question we consider is, whether the predictions of query performance that systems make are in line with the predictions that users make. To this aim, we compare the performance ratings users assign to queries with the performance scores estimated by a range of pre-retrieval and post-retrieval query performance predictors. Two studies are presented that explore the relationship between user ratings and system predictions on two levels: (i) the topic level, and, (ii) the query suggestions level. It is shown that when predicting the performance of query suggestions, user ratings were mostly uncorrelated with system predictions. At the topic level though, where a single query is judged for each information need, we observed moderate correlations between user ratings and a subset of system predictions. As query performance prediction methods are often based on intuitions of how users might rate queries, these findings suggest that such methods are not representative of how users actually rate query suggestions and topics. This motivates further research into understanding the rating process engaged by users, and developing models of query performance prediction in order to bridge the divide between systems and users.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"37 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":"121159060","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: 27

Digging for knowledge with information extraction: a case study on human gene-disease associations 用信息提取挖掘知识:人类基因与疾病关联的案例研究

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871744

Markus Bundschus, A. Bauer-Mehren, Volker Tresp, L. Furlong, H. Kriegel

引用次数: 8

Document allocation policies for selective searching of distributed indexes 选择性搜索分布式索引的文档分配策略

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871497

Anagha Kulkarni, Jamie Callan

{"title":"Document allocation policies for selective searching of distributed indexes","authors":"Anagha Kulkarni, Jamie Callan","doi":"10.1145/1871437.1871497","DOIUrl":"https://doi.org/10.1145/1871437.1871497","url":null,"abstract":"Indexes for large collections are often divided into shards that are distributed across multiple computers and searched in parallel to provide rapid interactive search. Typically, all index shards are searched for each query. For organizations with modest computational resources the high query processing cost incurred in this exhaustive search setup can be a deterrent to working with large collections. This paper investigates document allocation policies that permit searching only a few shards for each query (selective search) without sacrificing search accuracy. Random, source-based and topic-based document-to-shard allocation policies are studied in the context of selective search. A thorough study of the tradeoff between search cost and search accuracy in a sharded index environment is performed using three large TREC collections. The experimental results demonstrate that selective search using topic-based shards cuts the search cost to less than 1/5th of that of the exhaustive search without reducing search accuracy across all the three datasets. Stability analysis shows that 90% of the queries do as well or improve with selective search. An overlap-based evaluation with an additional 1000 queries for each dataset tests and confirms the conclusions drawn using the smaller TREC query sets.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"14 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":"122918958","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: 54

Community-based topic modeling for social tagging 基于社区的社会标签主题建模

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871673

Daifeng Li, Bing He, Ying Ding, Jie Tang, Cassidy R. Sugimoto, Zheng Qin, E. Yan, Juan-Zi Li, Tianxi Dong

引用次数: 56

Construction of a sentimental word dictionary 感伤词词典的构建

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871723

Eduard Constantin Dragut, Clement T. Yu, A. Sistla, W. Meng

引用次数: 84

Anonymizing data with quasi-sensitive attribute values 使用准敏感属性值对数据进行匿名化

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871628

Pu Shi, Li Xiong, B. Fung

引用次数: 27