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检索条件"机构=APEX Data and Knowledge Management Lab"

共 73 条记录，以下是61-70 订阅

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A statistical study of today's Gnutella

A statistical study of today's Gnutella

引用

8th Asia-Pacific Web Conference and Workshops (APWeb 2006)

作者： Meng, SC Shi, C Han, DY Zhu, X Yu, Y Shanghai Jiao Tong Univ Dept Comp Sci & Engn APEX Data & Knowledge Management Lab Shanghai 200030 Peoples R China

ISBN: (纸本)3540311424

As a developing P2P system, Gnutella has upgraded its protocol to 0.6, which significantly changed the characteristics of its hosts. However, few previous work has given a wide-scale study to the new version of Gnutella. In addition, various kinds of P2P models are used to evaluate P2P systems or mechanisms, but the reliability of some hypotheses used in the models are not carefully studied or proved. In this paper, we try to remedy this situation by performing a large scaled measurement study on Gnutella with the help of some new crawling approaches. In particular, we characterize Gnutella by its queries, shared files and peer roles. Our measurements show that the assumption that query arrival follows Poisson distribution may not be true in Gnutella and most peers incline to share files of very limited types, even when MP3 files are excluded. We also find that many ultrapeers in Gnutella are not well selected. Statistical data provided in this paper can also be useful for P2P modeling and simulation.

关键词： Computer networks

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Reinforcement learning for query-oriented routing indices in unstructured peer-to-peer networks 6

Reinforcement learning for query-oriented routing indices in...

引用

6th International Conference on Peer-to-Peer Computing (P2P 2006)

作者： Shi, Cong Meng, Shicong Liu, Yuanjie Han, Dingyi Yu, Yong Shanghai Jiao Tong Univ Apex Data & Knowledge Management Lab Dept Comp Sci & Engn Shanghai 200240 Peoples R China

ISBN: (纸本)0769526799

The idea of building query-oriented routing indices has changed the way of improving routing efficiency from the basis as it can learn the content distribution during the query routing process. It gradually improves routing efficiency with no excessive network overhead of the routing index construction and maintenance. However the previously proposed mechanism is not practically effective due to the slow improvement of routing efficiency. In this paper we propose a novel mechanism for query-oriented routing indices which quickly achieves high routing efficiency at low cost. The maintenance method employs reinforcement learning to utilize mass peer behaviors to construct and maintain routing indices. It explicitly uses the expected value of returned content number to depict the content distribution, which helps quickly approximate the real distribution. Meanwhile, the routing method is to retrieve as many contents as possible. It also helps speed up the learning process further The experimental evaluation shows that the mechanism has high routing efficiency, quick learning ability and satisfactory performance under chum.

关键词： Reinforcement learning

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LSM: Language sense model for information retrieval

引用

7th International Conference on Web-Age Information management

作者： Bao, Shenghua Zhang, Lei Chen, Erdong Long, Min Li, Rui Yu, Yong Shanghai Jiao Tong Univ Dept Comp Sci & Engn APEX Data & Knowledge Management Lab Shanghai 200230 Peoples R China

ISBN: (纸本)3540352252

A lot of work has been done on drawing word senses into retrieval to deal with the word sense ambiguity problem, but most of them achieved negative results. In this paper, we first implement a WSD system for nouns and verbs, then the language sense model (LSM) for information retrieval is proposed. The LSM combines the terms and senses of a document seamlessly through an EM algorithm. Retrieval on TREC collections shows that the LSM outperforms both the vector space model (BM25) and the traditional language model significantly for both medium and long queries (7.53%-16.90%). Based on the experiments, we can also empirically draw the conclusion that the fine-grained senses will improve the retrieval performance when they are properly used.

关键词： Information retrieval

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Image description mining and hierarchical clustering on data records using HR-tree

Image description mining and hierarchical clustering on data...

引用

8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development

作者： Zhang, Cong-Le Huang, Sheng Xue, Gui-Rong Yu, Yong Apex Data and Knowledge Management Lab. Department of Computer Science and Engineering Shanghai JiaoTong University Shanghai 200030 China

ISBN: (纸本)3540311424

Since we can hardly get semantics from the low-level features of the image, it is much more difficult to analyze the image than textual information on the Web. Traditionally, textual information around the image is used to represent the high-level features of the image. We argue that such "flat" representation can not describe images well. In this paper, Hierarchical Representation (HR) and HR-Tree are proposed for image description. Salient phrases in HR-Tree are further to distinguish this image with others sharing the same ancestor concepts. First, we design a method to extract the salient phrases for the images in data records. Then HR-Trees are built using these phrases. Finally, new hierarchical clustering algorithm based on HR-Tree is proposed for users' browsing conveniently. We demonstrate some HR-Trees and clustering results in experimental section. These results illustrate the advantages of our methods. © Springer-Verlag Berlin Heidelberg 2006.

关键词： data mining

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Emergent semantics from folksonomies: A quantitative study

引用

Journal on data Semantics VI - Special Issue on Emergent Semantics

作者： Zhang, Lei Wu, Xian Yu, Yong APEX Data and Knowledge Management Lab. Department of Computer Science and Engineering Shanghai JiaoTong University Shanghai 200030 China

ISBN: (纸本)3540367128

Defining and using ontology to annotate web resources with semantic markups is generally perceived as the primary way to implement the vision of the Semantic Web. The ontology provides a shared and machine understandable semantics for web resources that agents and applications can utilize. This top-down approach (in the sense that an ontology is defined first on top of existing web resources and then used later to markup them), however, has a high barrier to entry and is difficult to scale up. In this paper, we investigate using a bottom-up approach for semantically annotating web resources as supported by the now widely popular social bookmarks services on the web where users can annotate and categorize web resources using "tags" freely choosen by the user without any pre-existing global semantic model. This kind of informal social categories is coined as "folksonomies". We show how global semantics can be statistically inferred from the folksonomies to semantically annotate the web resources. The global semantic model also disambiguate the tags and group synonymous tags together. Finally, we show that there indeed are hierarchical relations among the emerged concepts in the folksonomy and it is plausible to further identify them if we use more advanced probabilistic models. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Semantics

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Mining and predicting duplication over peer-to-peer query streams

Mining and predicting duplication over peer-to-peer query st...

引用

作者： Meng, Shicong Shao, Yifeng Shi, Cong Han, Dingyi Yu, Yong APEX Data and Knowledge Management Lab. Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200030 China

ISBN: (纸本)0769527027

Many previous works of data mining user queries in Peer-to-Peer systems focused their attention on the distribution of query contents. However, few has been done towards a better understanding of the time series distribution of these queries, which is vital for system performance. To remedy this situation, this paper mines query steams by using automatic time series analysis to evaluate different linear models(Box-Jenkins models and some simple windowed-mean models) for predicting the number of duplicated queries from 10 minutes to 2 hours into the future. Both the predictive power and the computational costs of these models are evaluated over 318,942,450 real world Gnutella queries collected over 3 months. We find the number of duplicated queries is consistently predictable. Simple, practical models like AR perform well on prediction. © 2006 IEEE.

关键词： Time series analysis

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Minerva: A scalable OWL ontology storage and inference system

引用

1st Asian Semantic Web Conference

作者： Zhou, Jian Ma, Li Liu, Qiaoling Zhang, Lei Yu, Yong Pan, Yue Shanghai Jiao Tong Univ Dept Comp Sci & Engn APEX Data & Knowledge Management Lab Shanghai 200240 Peoples R China IBM Corp China Res Lab Beijing 100094 Peoples R China

ISBN: (纸本)3540383298

With the increasing use of ontologies in Semantic Web and enterprise knowledge management, it is critical to develop scalable and efficient ontology management systems. In this paper, we present Minerva, a storage and inference system for large-scale OWL ontologies on top of relational databases. It aims to meet scalability requirements of real applications and provide practical reasoning capability as well as high query performance. The method combines Description Logic reasoners for the TBox inference with logic rules for the ABox inference. Furthermore, it customizes the database schema based on inference requirements. User queries are answered by directly retrieving materialized results from the back-end database. The effective integration of ontology inference and storage is expected to improve reasoning efficiency, while querying without runtime inference guarantees satisfactory response time. Extensive experiments on University Ontology Benchmark show the high efficiency and scalability of Minerva system.

关键词： World Wide Web

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Providing an uncertainty reasoning service for semantic Web application

Providing an uncertainty reasoning service for semantic Web ...

引用

8th Asia-Pacific Web Conference and Workshops (APWeb 2006)

作者： Li, L Liu, QL Tao, YF Zhang, L Zhou, J Yu, Y Shanghai Jiao Tong Univ APEX Data & Knowledge Management Lab Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Basic Lab Dept Comp Sci & Engn Shanghai 200240 Peoples R China

ISBN: (纸本)3540311424

In the semantic web context,the formal representation of knowledge is not resourceful while the informal one with uncertainty prevails. In order to provide an uncertainty reasoning service for semantic web applications, we propose a probabilistic extension of Description Logic, namely Probabilistic Description Logic Program (PDLP). In this paper, we introduce the syntax and intensional semantics of PDLP, and present a fast reasoning algorithm making use of Logic Programming techniques. This extension is expressive, lightweight, and intuitive. Based on this extension, we implement a PDLP reasoner, and apply it into practical use: Tourism Ontology Uncertainty Reasoning system (TOUR). The TOUR system uses PDLP reasoner to make favorite travel plans on top of an integrated tourism ontology, which describes travel cites and services with their evaluation.

关键词： Semantics

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Research on expert search at enterprise track of TREC 2006

Research on expert search at enterprise track of TREC 2006

引用

15th Text REtrieval Conference, TREC 2006

作者： Bao, Shenghua Duan, Huizhong Zhou, Qi Xiong, Miao Cao, Yunbo Yu, Yong APEX Data and Knowledge Management Lab Shanghai Jiao Tong University Minhang District Shanghai 200240 China Microsoft Research Asia 5F Sigma Center No.49 Zhichun Road Haidian Beijing 100080 China

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An approach to RDF(S) query, manipulation and inference on databases

引用

6th International Conference on Web -Age Informational management

作者： Lu, J Yu, Y Tu, KW Lin, CX Zhang, L Shanghai Jiao Tong Univ APEX Data & Knowledge Management Lab Dept Comp Sci & Engn Shanghai 200240 Peoples R China

ISBN: (纸本)3540292276

In order to lay a solid foundation for the emerging semantic web, effective and efficient management of large RDF(S) data is in high demand. In this paper we propose an approach to the storage, query, manipulation and inference of large RDF(S) data on top of relational databases. Specifically, RDF(S) inference is done on the database in advance instead of on the fly, so that the query efficiency is maximized. To reduce the cost of inference, two inference modes, the batch mode and the incremental mode, are provided for different scenarios. In both modes, optimized strategies axe applied for efficiency purpose. In order to support efficient query and inference on the database, the storage schema is also specially designed. In addition, a powerful RDF(S) query and manipulation language RQML is provided for easy and uniform data access in a declarative way. Finally, we evaluate and report the performance on both query and inference of our approach. Experiments show that our approach achieves encouraging performance in million-scale real data.

关键词： Query languages

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