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

Ranking under temporal constraints 时间约束下的排序

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871452

Lidan Wang, Donald Metzler, Jimmy J. Lin

引用次数: 39

Quantifying uncertainty in multi-dimensional cardinality estimations 多维基数估计中的不确定性量化

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871610

Andranik Khachatryan, Klemens Böhm

引用次数: 2

WikiPop: personalized event detection system based on Wikipedia page view statistics WikiPop:基于维基百科页面浏览量统计的个性化事件检测系统

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871769

M. Ciglan, K. Nørvåg

引用次数: 51

Concurrent atomic protocols for making and changing decisions in social networks 用于在社交网络中制定和更改决策的并发原子协议

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871615

Royi Ronen, O. Shmueli

引用次数: 1

TAER: time-aware entity retrieval-exploiting the past to find relevant entities in news articles TAER:时间感知实体检索-利用过去在新闻文章中找到相关实体

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871661

Gianluca Demartini, M. S. Missen, Roi Blanco, H. Zaragoza

引用次数: 22

Learning to rank relevant and novel documents through user feedback 学习通过用户反馈对相关和新颖的文档进行排序

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871499

A. Lad, Yiming Yang

{"title":"Learning to rank relevant and novel documents through user feedback","authors":"A. Lad, Yiming Yang","doi":"10.1145/1871437.1871499","DOIUrl":"https://doi.org/10.1145/1871437.1871499","url":null,"abstract":"We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several desirable properties: (i) It measures retrieval performance in terms of relevant as well as novel information, (ii) gives more importance to top ranks to reflect common browsing behavior of users, as opposed to existing objective functions based on set-coverage, (iii) accommodates different levels of tolerance towards redundancy, which is not taken into account by existing evaluation measures, and (iv) extends naturally to the evaluation of session-based retrieval comprising multiple ranked lists. Our ground truth is defined in terms of \"information nuggets\", which are obviously not known to the retrieval system when processing a new user query. Therefore, our approach uses observable query and document features (words and named entities) as surrogates for nuggets, whose weights are learned based on user feedback in an iterative search session. The ranked list is produced to maximize the weighted coverage of these surrogate nuggets. The optimization of such coverage-based metrics is known to be NP-hard. Therefore, we use a greedy algorithm and show that it guarantees good performance due to the submodularity of the objective function. Our experiments on Topic Detection and Tracking data show that the proposed approach represents an efficient and effective retrieval strategy for maximizing EGU, as compared to a purely-relevance based ranking approach that uses Indri, as well as a MMR-based approach for non-redundant ranking.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"52 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":"126620433","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: 3

Injecting domain knowledge into a granular database engine: a position paper 向细粒度数据库引擎注入领域知识:立场文件

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871762

D. Ślęzak, Graham Toppin

引用次数: 10

Multi-information fusion for uncertain semantic representations of videos 视频不确定语义表示的多信息融合

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871684

Bo Lu, Guoren Wang, Xiao-Yu Gong

引用次数: 1

Search as if you were in your home town: geographic search by regional context and dynamic feature-space selection 搜索就好像你在你的家乡:地理搜索区域背景和动态特征空间选择

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871667

Makoto P. Kato, H. Ohshima, S. Oyama, Katsumi Tanaka

{"title":"Search as if you were in your home town: geographic search by regional context and dynamic feature-space selection","authors":"Makoto P. Kato, H. Ohshima, S. Oyama, Katsumi Tanaka","doi":"10.1145/1871437.1871667","DOIUrl":"https://doi.org/10.1145/1871437.1871667","url":null,"abstract":"We propose a query-by-example geographic object search method for users that do not know well about the place they are in. Geographic objects, such as restaurants, are often retrieved using an attribute-based or keyword query. These queries, however, are difficult to use for users that have little knowledge on the place where they want to search. The proposed query-by-example method allows users to query by selecting examples in familiar places for retrieving objects in unfamiliar places. One of the challenges is to predict an effective distance metric, which varies for individuals. Another challenge is to calculate the distance between objects in heterogeneous domains considering the feature gap between them, for example, restaurants in Japan and China. Our proposed method is used to robustly estimate the distance metric by amplifying the difference between selected and non-selected examples. By using the distance metric, each object in a familiar domain is evenly assigned to one in an unfamiliar domain to eliminate the difference between those domains. We developed a restaurant search using data obtained from a Japanese restaurant Web guide to evaluate our method.","PeriodicalId":310611,"journal":{"name":"Proceedings of the 19th ACM international conference on Information and knowledge management","volume":"12 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":"122102585","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: 6

Use of semantics in real life applications 在实际应用程序中使用语义

Proceedings of the 19th ACM international conference on Information and knowledge management Pub Date : 2010-10-26 DOI: 10.1145/1871437.1871441

G. Grefenstette

引用次数: 2