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检索条件"机构=Key Labs. of Data Engineering and Knowledge Engineering"

共 41 条记录，以下是1-10 订阅

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A Timeline-Based Algorithm for Personalized Tag Recommendation

A Timeline-Based Algorithm for Personalized Tag Recommendati...

引用

11th International Conference on Web Information Systems engineering

作者： Yu, Zhaohui Wang, Puwei Du, Xiaoyong Cui, Jianwei Xu, Tianren Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642243950

Recently, tagging has been a flexible and important way to share and categorize web resources, these user-generated tags are effective to represent user interests because these tags reflect human being's judgments while more concise and closer to human understanding, and the user interests are changing over time. Thus, modeling user interests to meet individual user needs is an important challenge for personalization and information filtering applications, such as recommender systems. In this paper, we apply a distance decay model for modeling user interests in terms of tags based on timeline. We then propose a novel algorithm to measure users' similarities in terms of their tagging activity over a specific time period and provide personalized tag recommendation according to similar users' interests in their next time intervals. Experimental results demonstrate the higher precision and recall with our personalized tag recommendation algorithm than other existing methods.

关键词： timeline user interests distance decay model personalized tag recommendation

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SeCCX: Semantics-based fine granular concurrency control for XML data

SeCCX: Semantics-based fine granular concurrency control for...

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1st International Workshop on Graph database, IWGD 2010, 1st International Workshop on Advanced Techniques on XML data Management, XMLDM 2010, 2nd International Workshop on WCMT 2010, Held in Conj. with WAIM 2010

作者： Rong, Chuitian Lu, Wei Zhang, Xiao Liu, Zhen Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China

ISBN: (纸本)3642167195

This paper proposes a new locking protocol, SeCCX, for isolation of concurrent transactions on XML data. This protocol adopts the semantics of operations issued by users. Comparing with previous XML locking protocols, SeCCX has some new features, like richer lock modes, finer granular, lower lock confliction and dynamic lock escalation. The importance is that it locks the objects according to the semantics of user's operation and sets different restrictions on different objects. It provides finer granular concurrency control such that the overall system performance can be improved. We prove that the SeCCX protocol is conflict serializability. We also compare it with other protocols to demonstrate the advantages of SeCCX. © 2010 Springer-Verlag.

关键词： Locks (fasteners)

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Predicting New User's Behavior in Online Dating Systems

Predicting New User's Behavior in Online Dating Systems

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7th International Conference on Advanced data Mining and Applications

作者： Wang, Tingting Liu, Hongyan He, Jun Jiang, Xuan Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642258558

Predicting new user's reaction behavior to its recommended candidate partner correctly is critical to improve recommendation accuracy in online dating systems. However, new user (cold start) problem and data sparseness problem in the online dating system make this task very challenging. In this paper, we propose a hybrid method called crowd wisdom based behavior prediction to solve the two problems and achieve good prediction accuracy. By this method, old users who have been recommended partners before are first separated into groups. Users in each group have similar preference for partners. Then, we propose a novel measure to combine a group user's collective behavior to predict one user's behavior, which can solve the data sparseness problem. By calculating the probability a new user belongs to each group and utilizing the group's behavior we can solve the new user problem. Based on these strategies. we develop a behavior prediction algorithm for new users. Experimental results conducted on a real online dating dataset show that our proposed method performs better than other traditional methods.

关键词： online dating recommendation clustering classification

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Efficient Duplicate Detection on Cloud Using a New Signature Scheme

Efficient Duplicate Detection on Cloud Using a New Signature...

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12th International Conference on Web-Age Information Management

作者： Rong, Chuitian Lu, Wei Du, Xiaoyong Zhang, Xiao Key Labs. of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China China Shanghai Key Laboratory of Intelligent Information Processing China

ISBN: (纸本)9783642235344;9783642235351

Duplicate detection has been well recognized as a crucial task to improve the quality of data. Related work on this problem mainly aims to propose efficient approaches over a single machine. However, with increasing volume of the data, the performance to identify duplicates is still far from satisfactory. Hence, we try to handle the problem of duplicate detection over MapReduce, a share-nothing paradigm. We argue the performance of utilizing MapReduce to detect duplicates mainly depends on the number of candidate record pairs. In this paper, we proposed a new signature scheme with new pruning strategy over MapReduce to minimize the number of candidate record pairs. Our experimental results over both real and synthetic datasets demonstrate that our proposed signature based method is efficient and scalable.

关键词： duplicate detection MapReduce Cloud

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Co-spatial searcher: Efficient tag-based collaborative spatial search on geo-social network

Co-spatial searcher: Efficient tag-based collaborative spati...

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17th International Conference on database Systems for Advanced Applications, DASFAA 2012

作者： Zhang, Jinzeng Meng, Xiaofeng Zhou, Xuan Liu, Dongqi School of Information Renmin University of China Beijing China Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9783642290374

The proliferation of geo-social network, such as Foursquare and Facebook Places, enables users to generate location information and its corresponding descriptive tags. Using geo-social networks, users with similar interests can plan for social activities collaboratively. This paper proposes a novel type of query, called Tag-based top-k Collaborative Spatial (TkCoS) query, for users to make outdoor plans collaboratively. This type of queries aim to retrieve groups of geographic objects that can satisfy a group of users' requirements expressed in tags, while ensuring that the objects be within the minimum spatial distance from the users. To answer TkCoS queries efficiently, we introduce a hybrid index structure called Spatial-Tag R-tree (STR-tree), which is an extension of the R-tree. Based on STR-tree, we propose a query processing algorithm that utilizes both spatial and tag similarity constraints to prune search space and identify desired objects quickly. Moreover, a differential impact factor is adopted to fine-tune the returned results in order to maximize the users' overall satisfaction. Extensive experiments on synthetic and real datatsets validate the efficiency and the scalability of the proposed algorithm. © 2012 Springer-Verlag.

关键词： Forestry

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FlexTable: Using a Dynamic Relation Model to Store RDF data

FlexTable: Using a Dynamic Relation Model to Store RDF Data

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15th International Conference on database Systems for Advanced Applications

作者： Wang, Yan Du, Xiaoyong Lu, Jiaheng Wang, Xiaofang Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China Information School Renmin University of China China

ISBN: (纸本)9783642120251

Efficient management of RDF data is an important factor in realizing the Semantic Web vision. The existing approaches store RDF data based on triples instead of a relation model. In this paper, we propose a system called FlexTable, where all triples of an instance are coalesced into one tuple and all tuples are stored in relation schemas. The main technical challenge is how to partition all the triples into several tables, i.e. it is needed to design an effective and dynamic schema structure to store RDF triples. To deal with this challenge, we firstly propose a schema evolution method called LBA, which is based on a lattice structure to automatically evolve schemas while new triples are inserted. Secondly, we propose a novel page layout with an interpreted storage format to reduce the physical adjustment cost during schema evolution. Finally we perform comprehensive experiments on two practical RDF data sets to demonstrate that FlexTable is superior to the state-of-the-art approaches.

关键词： FlexTable RDF data dynamic relational model Lattice

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Efficient parallel skyline processing using hyperplane projections 11

Efficient parallel skyline processing using hyperplane proje...

引用

2011 ACM SIGMOD and 30th PODS 2011 Conference

作者： Köhler, Henning Yang, Jing Zhou, Xiaofang School of Information Technology and Electrical Engineering University of Queensland Australia School of Information Renmin University of China Key Labs. of Data Engineering and Knowledge Engineering BeiJing China

ISBN: (纸本)9781450306614

The skyline of a set of multi-dimensional points (tuples) consists of those points for which no clearly better point exists in the given set, using component-wise comparison on domains of interest. Skyline queries, i.e., queries that involve computation of a skyline, can be computationally expensive, so it is natural to consider parallelized approaches which make good use of multiple processors. We approach this problem by using hyperplane projections to obtain useful partitions of the data set for parallel processing. These partitions not only ensure small local skyline sets, but enable efficient merging of results as well. Our experiments show that our method consistently outperforms similar approaches for parallel skyline computation, regardless of data distribution, and provides insights on the impacts of different optimization strategies. © 2011 ACM.

关键词： Geometry

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Mining user interests from information sharing behaviors in social media

引用

17th Pacific-Asia Conference on knowledge Discovery and data Mining, PAKDD 2013

作者： Wang, Tingting Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374555

Mining user interests and preference plays an important role for many applications such as information retrieval and recommender systems. This paper intends to study how to infer interests for new users and inactive users from social media. Although some recently proposed methods can mine user interests efficiently, these works cannot make full use of relationship between users in their social network. In this paper, we propose a novel approach to infer interests of new users or inactive users based on social connections between users. A random-walk based mutual reinforcement model combining both text and link information is developed in the approach. More importantly, we compare the contribution of different social connections such as "follow", "retweet", "mention", and "comment" to interest sharing. Experiments conducted on real dataset show that our method is effective and outperforms existing algorithms, and different social connections have different impacts on mining user interests. © Springer-Verlag 2013.

关键词： Recommender systems

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Combining spatial cloaking and dummy generation for location privacy preserving

Combining spatial cloaking and dummy generation for location...

引用

8th International Conference on Advanced data Mining and Applications, ADMA 2012

作者： Xu, Nana Zhu, Dan Liu, Hongyan He, Jun Du, Xiaoyong Liu, Tao Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China Department of Management Science and Engineering Tsinghua University China

ISBN: (纸本)9783642355264

Location privacy preserving is attracting more and more attentions with the wide use of accurate positioning devices. Two kinds of methods based on k-anonymity have been proposed for location privacy preserving. One is spatial cloaking and the other is dummy generation. However, simple cloaking may result in large cloaking region, especially when user distribution is sparse. Large cloaking region means low efficiency and high time cost. Dummy generation will also arouse great extra system cost. In this paper, we propose an approach that combines the two techniques to achieve an ideal complement. On one hand, cloaking algorithm is used to blur precise location into a region so that location privacy can be well protected. On the other hand, to those users whose cloaking region is large, generating limited number of dummies can help decrease the size of region. The effectiveness of our methods has been demonstrated by comprehensive experiments. © Springer-Verlag 2012.

关键词： Location

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Detecting event rumors on Sina Weibo automatically

Detecting event rumors on Sina Weibo automatically

引用

15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Sun, Shengyun Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374005

Sina Weibo has become one of the most popular social networks in China. In the meantime, it also becomes a good place to spread various spams. Unlike previous studies on detecting spams such as ads, pornographic messages and phishing, we focus on identifying event rumors (rumors about social events), which are more harmful than other kinds of spams especially in China. To detect event rumors from enormous posts, we studied the characteristics of event rumors and extracted features which can distinguish rumors from ordinary posts. The experiments conducted on real dataset show that the new features are effective to improve the rumor classifier. Further analysis of the event rumors reveals that they can be classified into 4 different types. We propose an approach for detecting one major type, text-picture unmatched event rumors. The experiment demonstrates that this approach is well-performed. © 2013 Springer-Verlag.

关键词： Social networking (online)

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