Proceedings of the 21st ACM international conference on Information and knowledge management最新文献_第6页

Towards an effective and unbiased ranking of scientific literature through mutual reinforcement 通过相互加强，实现科学文献的有效和公正的排名

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2396853

Xiaorui Jiang, Xiaoping Sun, H. Zhuge

{"title":"Towards an effective and unbiased ranking of scientific literature through mutual reinforcement","authors":"Xiaorui Jiang, Xiaoping Sun, H. Zhuge","doi":"10.1145/2396761.2396853","DOIUrl":"https://doi.org/10.1145/2396761.2396853","url":null,"abstract":"It is important to help researchers find valuable scientific papers from a large literature collection containing information of authors, papers and venues. Graph-based algorithms have been proposed to rank papers based on networks formed by citation and co-author relationships. This paper proposes a new graph-based ranking framework MutualRank that integrates mutual reinforcement relationships among networks of papers, researchers and venues to achieve a more synthetic, accurate and fair ranking result than previous graph-based methods. MutualRank leverages the network structure information among papers, authors, and their venues available from a literature collection dataset and sets up a unified mutual reinforcement model that involves both intra- and inter-network information for ranking papers, authors and venues simultaneously. To evaluate, we collect a set of recommended papers from websites of graduate-level computational linguistics courses of 15 top universities as the benchmark and apply different methods to estimate paper importance. The results show that MutualRank greatly outperforms the competitors including Pag-eRank, HITS and CoRank in ranking papers as well as researchers. The experimental results also demonstrate that venues ranked by MutualRank are reasonable.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"1 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":"128898838","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: 39

gSCorr: modeling geo-social correlations for new check-ins on location-based social networks gSCorr:为基于位置的社交网络上的新签到建立地理社会关联模型

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398477

Huiji Gao, Jiliang Tang, Huan Liu

{"title":"gSCorr: modeling geo-social correlations for new check-ins on location-based social networks","authors":"Huiji Gao, Jiliang Tang, Huan Liu","doi":"10.1145/2396761.2398477","DOIUrl":"https://doi.org/10.1145/2396761.2398477","url":null,"abstract":"Location-based social networks (LBSNs) have attracted an increasing number of users in recent years. The availability of geographical and social information of online LBSNs provides an unprecedented opportunity to study the human movement from their socio-spatial behavior, enabling a variety of location-based services. Previous work on LBSNs reported limited improvements from using the social network information for location prediction; as users can check-in at new places, traditional work on location prediction that relies on mining a user's historical trajectories is not designed for this \"cold start\" problem of predicting new check-ins. In this paper, we propose to utilize the social network information for solving the \"cold start\" location prediction problem, with a geo-social correlation model to capture social correlations on LBSNs considering social networks and geographical distance. The experimental results on a real-world LBSN demonstrate that our approach properly models the social correlations of a user's new check-ins by considering various correlation strengths and correlation measures.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"151 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":"134475644","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: 231

Reconciling ontologies and the web of data 协调本体和数据网络

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398467

Ziawasch Abedjan, Johannes Lorey, Felix Naumann

引用次数: 25

Monochromatic and bichromatic reverse nearest neighbor queries on land surfaces 单色和双色逆最近邻查询在陆地表面

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2396880

D. Yan, Zhou Zhao, Wilfred Ng

{"title":"Monochromatic and bichromatic reverse nearest neighbor queries on land surfaces","authors":"D. Yan, Zhou Zhao, Wilfred Ng","doi":"10.1145/2396761.2396880","DOIUrl":"https://doi.org/10.1145/2396761.2396880","url":null,"abstract":"Finding reverse nearest neighbors (RNNs) is an important operation in spatial databases. The problem of evaluating RNN queries has already received considerable attention due to its importance in many real-world applications, such as resource allocation and disaster response. While RNN query processing has been extensively studied in Euclidean space, no work ever studies this problem on land surfaces. However, practical applications of RNN queries involve terrain surfaces that constrain object movements, which rendering the existing algorithms inapplicable. In this paper, we investigate the evaluation of two types of RNN queries on land surfaces: monochromatic RNN (MRNN) queries and bichromatic RNN (BRNN) queries. On a land surface, the distance between two points is calculated as the length of the shortest path along the surface. However, the computational cost of the state-of-the-art shortest path algorithm on a land surface is quadratic to the size of the surface model, which is usually quite huge. As a result, surface RNN query processing is a challenging problem. Leveraging some newly-discovered properties of Voronoi cell approximation structures, we make use of standard index structures such as an R-tree to design efficient algorithms that accelerate the evaluation of MRNN and BRNN queries on land surfaces. Our proposed algorithms are able to localize query evaluation by accessing just a small fraction of the surface data near the query point, which helps avoid shortest path evaluation on a large surface. Extensive experiments are conducted on large real-world datasets to demonstrate the efficiency of our algorithms.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"24 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":"115422426","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: 17

Efficient influence-based processing of market research queries 有效的基于影响的市场调查查询处理

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398420

Anastasios Arvanitis, Antonios Deligiannakis, Y. Vassiliou

{"title":"Efficient influence-based processing of market research queries","authors":"Anastasios Arvanitis, Antonios Deligiannakis, Y. Vassiliou","doi":"10.1145/2396761.2398420","DOIUrl":"https://doi.org/10.1145/2396761.2398420","url":null,"abstract":"The rapid growth of social web has contributed vast amounts of user preference data. Analyzing this data and its relationships with products could have several practical applications, such as personalized advertising, market segmentation, product feature promotion etc. In this work we develop novel algorithms for efficiently processing two important classes of queries involving user preferences, i.e. potential customers identification and product positioning. With regards to the first problem, we formulate product attractiveness based on the notion of reverse skyline queries. We then present a new algorithm, termed as RSA, that significantly reduces the I/O cost, as well as the computation cost, when compared to the state-of-the-art reverse skyline algorithm, while at the same time being able to quickly report the first results. Several real-world applications require processing of a large number of queries, in order to identify the product characteristics that maximize the number of potential customers. Motivated by this problem, we also develop a batched extension of our RSA algorithm that significantly improves upon processing multiple queries individually, by grouping contiguous candidates, exploiting I/O commonalities and enabling shared processing. Our experimental study using both real and synthetic data sets demonstrates the superiority of our proposed algorithms for the studied classes of queries.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"44 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":"115550944","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: 24

PARMA: a parallel randomized algorithm for approximate association rules mining in MapReduce PARMA: MapReduce中近似关联规则挖掘的并行随机化算法

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2396776

Matteo Riondato, Justin A. DeBrabant, Rodrigo Fonseca, E. Upfal

{"title":"PARMA: a parallel randomized algorithm for approximate association rules mining in MapReduce","authors":"Matteo Riondato, Justin A. DeBrabant, Rodrigo Fonseca, E. Upfal","doi":"10.1145/2396761.2396776","DOIUrl":"https://doi.org/10.1145/2396761.2396776","url":null,"abstract":"Frequent Itemsets and Association Rules Mining (FIM) is a key task in knowledge discovery from data. As the dataset grows, the cost of solving this task is dominated by the component that depends on the number of transactions in the dataset. We address this issue by proposing PARMA, a parallel algorithm for the MapReduce framework, which scales well with the size of the dataset (as number of transactions) while minimizing data replication and communication cost. PARMA cuts down the dataset-size-dependent part of the cost by using a random sampling approach to FIM. Each machine mines a small random sample of the dataset, of size independent from the dataset size. The results from each machine are then filtered and aggregated to produce a single output collection. The output will be a very close approximation of the collection of Frequent Itemsets (FI's) or Association Rules (AR's) with their frequencies and confidence levels. The quality of the output is probabilistically guaranteed by our analysis to be within the user-specified accuracy and error probability parameters. The sizes of the random samples are independent from the size of the dataset, as is the number of samples. They depend on the user-chosen accuracy and error probability parameters and on the parallel computational model. We implemented PARMA in Hadoop MapReduce and show experimentally that it runs faster than previously introduced FIM algorithms for the same platform, while 1) scaling almost linearly, and 2) offering even higher accuracy and confidence than what is guaranteed by the analysis.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"23 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":"115625673","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: 144

Supporting temporal analytics for health-related events in microblogs 支持对微博中与健康相关的事件进行时间分析

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398726

Nattiya Kanhabua, Sara Romano, Avare Stewart, W. Nejdl

引用次数: 24

Detecting offensive tweets via topical feature discovery over a large scale twitter corpus 通过大规模推特语料库上的主题特征发现来检测攻击性推文

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398556

Guang Xiang, Bin Fan, Ling Wang, Jason I. Hong, C. Rosé

引用次数: 254

Trust prediction via aggregating heterogeneous social networks 基于聚合异质社会网络的信任预测

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398515

Jin Huang, F. Nie, Heng Huang, Yi-Cheng Tu

{"title":"Trust prediction via aggregating heterogeneous social networks","authors":"Jin Huang, F. Nie, Heng Huang, Yi-Cheng Tu","doi":"10.1145/2396761.2398515","DOIUrl":"https://doi.org/10.1145/2396761.2398515","url":null,"abstract":"Along with the increasing popularity of social web sites, users rely more on the trustworthiness information for many online activities among users. However, such social network data often suffers from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches explore the topology of trust graph. Previous research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behavior and tastes. Such ancillary information, is often accessible and therefore could potentially help the trust prediction. In this paper, we address the link prediction problem by aggregating heterogeneous social networks and propose a novel joint manifold factorization (JMF) method. Our new joint learning model explores the user group level similarity between correlated graphs and simultaneously learns the individual graph structure, therefore the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph, but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the objective function, we break down the proposed objective function into several manageable sub-problems, then further establish the theoretical convergence with the aid of auxiliary function. Extensive experiments were conducted on real world data sets and all empirical results demonstrated the effectiveness of our method.","PeriodicalId":313414,"journal":{"name":"Proceedings of the 21st ACM international conference on Information and knowledge management","volume":"40 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":"116978839","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: 33

An evaluation and enhancement of densitometric fragmentation for content slicing reuse 面向内容切片重用的密度碎片评价与改进

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI: 10.1145/2396761.2398652

Killian Levacher, S. Lawless, V. Wade

引用次数: 3