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Combining parametric and nonparametric topic model to discover microblog event

Combining parametric and nonparametric topic model to discov...

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International Conference on Information Science, Electronics and Electrical Engineering (ISEEE)

作者： Shengbing Liu Li Liu Ruzhong Cheng Peking University Beijing Beijing CN Dept. of Electronic and Computer Engineering South University of Science and Technology of China Shenzhen P.R. China Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) Peking University Shenzhen P.R. China

Compared with traditional news media, microblog holds overwhelming superiority in fast-diffusion and comprehensive coverage of topics. Microblog becomes an effective, particular and important carrier of affair information and many other text analysis tasks, e.g., event discovering based on microblog have special significance. Common tools of content analysis, such as topic model, however, experience severe data sparsity problems due to short length of microblog. Following previous researchers' idea, such as separating personal interest post from global event post, we further differentiate general topics from event topics and adopt nonparametric method to model the birth and death of event. We conduct experiments on Twitter data set, and the experimental results demonstrate that our method can not only discover event effectively, but also mine higher quality general topics.

关键词： Computational modeling Educational institutions Coherence Media Data models Twitter Computational linguistics

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TopicDSDR: Combining topic decomposition and data reconstruction for summarization

TopicDSDR: Combining topic decomposition and data reconstruc...

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14th International Conference on Web-Age Information Management, WAIM 2013

作者： Zhang, Zhiming Li, Hongjie Huang, Lian'En Shenzhen Key Lab for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Shenzhen Guangdong China

ISBN: (纸本)9783642385612

Multi-document summarization attempts to select the most important information to generate a compressed summary from a collection of documents. From the perspective of data reconstruction, a good summary may also well reconstruct the original documents. A document generally contains a variety of information centered around a main topic and covers different aspects of the main topic. In this paper we propose a novel model that combines data reconstruction and topic decomposition to summarize the documents, named TopicDSDR, which can not only best reconstruct the original documents but also capture the semantic similarity and main topics. We discuss two kinds of reconstructions: linear reconstruction and nonnegative reconstruction. We use the generalized Kullback-Leibler(KL) divergence as the loss function to evaluate the quality of summary for linear and nonnegative reconstruction and develop two new algorithms respectively. We conduct experiments on DUC2006 and DUC2007 summarization data sets, the experimental results demonstrate the effectiveness of our proposed methods. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Semantics

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Comments-oriented document summarization based on multi-aspect co-feedback ranking

Comments-oriented document summarization based on multi-aspe...

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14th International Conference on Web-Age Information Management, WAIM 2013

作者： Huang, Lifu Li, Hongjie Huang, Lian'En Shenzhen Key Lab for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Shenzhen Guangdong 518055 China

ISBN: (纸本)9783642385612

With the popularity of Web 2.0, comments left by readers on web documents have drawn much attention. In this paper, we study the problem of comments-oriented document summarization, which aims to summarize a web document by considering not only its content but also the comments. Generally, most of the comments usually convey one or a few aspects of the document. Given a sentence set from both the web document and its corresponding comments to summarize, we can divide different sentences into different clusters (named "aspects") according to the content. It is challenging and interesting to summarize the web document based on these clusters. Motivated by this, we propose a novel model: MultiAspectCoRank, for comments-oriented document summarization. Firstly we rank all the sentences based on the multiple aspects obtained from the whole document, and then provide each ranking list as feedback to others until the top-N results of each ranking list are unchanged. We get the final result by integrating these different ranking lists together. Experimental results on a set of real-world blog data with manually labeled sentences show the promising performance of our approach. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Computers

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Optimized event storyline generation based on mixture-event-aspect model

Optimized event storyline generation based on mixture-event-...

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2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013

作者： Huang, Lifu Huang, Lian'en Shenzhen Key Lab for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Shenzhen Guangdong518055 China

ISBN: (纸本)9781937284978

Recently, much research focuses on event storyline generation, which aims to produce a concise, global and temporal event summary from a collection of articles. Generally, each event contains multiple sub-events and the storyline should be composed by the component summaries of all the sub-events. However, different sub-events have different part-whole relationship with the major event, which is important to correspond to users' interests but seldom considered in previous work. To distinguish different types of sub-events, we propose a mixture-event-aspect model which models different sub-events into local and global aspects. Combining these local/global aspects with summarization requirements together, we utilize an optimization method to generate the component summaries along the timeline. We develop experimental systems on 6 distinctively different datasets. Evaluation and comparison results indicate the effectiveness of our proposed method. © 2013 Association for Computational Linguistics.

关键词： Mixtures

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WordTopic-MultiRank: A New Method for Automatic keyphrase Extraction 6

WordTopic-MultiRank: A New Method for Automatic Keyphrase Ex...

引用

6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Zhang, Fan Huang, Lian'en Peng, Bo Shenzhen Key Lab for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Shenzhen518055 China Institute of Network Computing and Information Systems Peking University Beijing100871 China

ISBN: (纸本)9784990734800

Automatic keyphrase extraction aims to pick out a set of terms as a representation of a document without manual assignment efforts. Supervised and unsupervised graph-based ranking methods have been studied for this task. However, previous methods usually computed importance scores of words under the assumption of single relation between words. In this work, we propose WordTopic-MultiRank as a new method for keyphrase extraction, based on the idea that words relate with each other via multiple relations. First we treat various latent topics in documents as heterogeneous relations between words and construct a multi-relational word network. Then, a novel ranking algorithm, named Biased-MultiRank, is applied to score the importance of words and topics simultaneously, as words and topics are considered to have mutual influence on each other. Experimental results on two different data sets show the outstanding performance and robustness of our proposed approach in automatic keyphrase extraction task. © IJCNLP *** right reserved.

关键词： Extraction

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A novel biased diversity ranking model for Query-oriented multidocument summarization

A novel biased diversity ranking model for Query-oriented mu...

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2013 International Conference on Vehicle and Mechanical Engineering and Information technology, VMEIT 2013

作者： Lei, Kai Zeng, Yi Fan The Shenzhen Key Lab for Cloud Computing Technology and Application Peking University Shenzhen Graduate School Shenzhen Guangdong 518055 China

ISBN: (纸本)9783037858202

Query-oriented multi-document summarization (QMDS) attempts to generate a concise piece of text byextracting sentences from a target document collection, withthe aim of not only conveying the key content of that corpus,also, satisfying the information needs expressed by that *** to its great applicable value, QMDS has been intensively studied in recent decades. Three properties are supposed crucial for a good summary, i.e., relevance, prestige and low redundancy (orso-called diversity). Unfortunately, most existing work either disregarded the concern of diversity, or handled it with non-optimized heuristics, usually based on greedy sentences election. Inspired by the manifold-ranking process, which deals with query-biased prestige, and DivRank algorithm which captures query-independent diversity ranking, in this paper, we propose a novel biased diversity ranking model, namedManifoldDivRank, for query-sensitive summarization tasks. The top-ranked sentences discovered by our algorithm not only enjoy query-oriented high prestige, more importantly, they are dissimilar with each other. Experimental results on DUC2005and DUC2006 benchmark data sets demonstrate the effectivenessof our proposal. © (2013) Trans Tech Publications, Switzerland.

关键词： Conveying

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Large-scale wire-speed multicast switching structure based on multipath self-routing switching structure and implemented on FPGA

Large-scale wire-speed multicast switching structure based o...

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3rd International Conference on Materials Science and Information technology, MSIT 2013

作者： Cui, Kai Li, Hui Zhu, Zhi Pu Chen, Fu Xing Shenzhen Eng. Lab of Converged Networks Technology Shenzhen Key Lab of Cloud Computing Tech. and App Shenzhen Graduate School Peking University Shenzhen China

ISBN: (纸本)9783037857700

Ensuring high quality of service (QoS) of multicast video stream over next generation network is a challenging issue, and how to implement the wire-speed multicast with hardware logical support in the network nodes of every hierarchy is a key solution to achieve high QoS multicast. Currently, the multicast packets are processed in this way, in which they are copied and then scheduled by ports, lastly, sent respectively. But this approach cannot ensure high QoS in realtime applications. Moreover, the traditional hardware solutions do not possess excellent large-scale scalability owning to their own bottlenecks. In this project, we have constructed a wire-speed multicast switching structure based on Multipath Self-routing Switching Structure, and implemented it on a Stratix IV FPGA chip. Additionally, we have designed the signaling system and control mechanism to support the process of self-routing and wire-speed fan-out copy of multicast packets. © (2013) Trans Tech Publications, Switzerland.

关键词： Wire

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Optimizing interactive performance for desktop-virtualization environment

Optimizing interactive performance for desktop-virtualizatio...

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Joint International Conference on Pervasive computing and the Networked World, ICPCA/SWS 2012

作者： Wang, Xiaolin Zhang, Binbin Luo, Yingwei Dept. of Computer Science and Technology Peking University Beijing 100871 China Dept. of Computer Science and Engineering Yunnan University Yunnan 650091 China Shenzhen Key Lab. for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Guangdong 518055 China

ISBN: (纸本)9783642370144

Full virtualization is vastly applied in desktop virtualization. Although hardware-assisted virtualization greatly improves the performance, the interactive performance is still a bottleneck for full virtualization. Interactive performance is mainly influenced by I/O devices. In one hand, I/O devices are slow device. In another hand, they are often shared by multiple virtual machines through simulation. Our study focuses on the interactive performance optimization, and can mainly be classified into three categories: (1) Targeting multi-core system, we investigate virtual machine deployment to ensure stable performance of the whole system and individual virtual machine. (2) Dynamically adjust the resource among virtual machines based on the individual machine's interactive behavior. (3) Optimize the I/O request scheduler in term of the virtualization implementation. © 2013 Springer-Verlag.

关键词： Virtual machine

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International Conference on Networking and Distributed computing (ICNDC)

作者： Kai Lei Qian Yu Rui Ning Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) Peking University Shenzhen P.R. China

Smart Mobile device are becoming popular platforms for information accessing, especially when coupled with recommendation system technologies. They are also treated as key tools for mobile users both for leisure and business applications. Recommendation techniques can increase the usability of mobile systems by providing more personalized and interested content. In this paper, a novel personalized recommender system is proposed, focusing on Mobile Terminal (MT) similarities, such as brands, versions and types of Operating Systems. These similarities play a key role in filtering original recommendation data sets at the preprocessing stage. By calculating and comparing the Mean Absolute Error (MAE) values through 5-fold cross validation of the Slope One algorithm with/without optimizing data sets by device-similarity, the overall effectiveness and accuracy of the recommendation results are at least 20% improved in our experiment.

关键词： Mobile communication Context Mobile handsets Filtering Operating systems Educational institutions Collaboration

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Understanding Sina Weibo online social network: A community approach

Understanding Sina Weibo online social network: A community ...

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2013 IEEE Global Communications Conference (GLOBECOM)

作者： Kai Lei Kai Zhang Kuai Xu Shenzhen Key Lab for Cloud Computing Technology & Applications (SPCCTA) Peking University Shenzhen P.R. China School of Mathematical and Natural Sciences Arizona State University

ISBN: (纸本)9781479913510

Sina Weibo, one of the most popular online social networks in China, has recently become a critical medium for Internet users to disseminate and discuss breaking news, social events and other information. Although online social networks and social media have received significant attention from the research community, few studies have focused on Sina Weibo due to the lack of data collection. Given the sheer size of Sina Weibo online social network and vast amount of tweets, retweets and comments, this paper introduces a novel community approach for understanding Sina Weibo online social network. Specifically, we collect all Weibo users registered with shenzhen as primary geographic location, and build a shenzhen Weibo community graph based on their following or follower relationships. Our experimental results describe interesting graphical characteristics such as clustering coefficients of this community graph, and reveal the impact of user popularity on tweet influence. Through modeling interactions of shenzhen Weibo users and their tweeted messages with bipartite graphs and one-mode projections, we analyze the similarity of retweeting and commenting activities among these users, and discuss the implications of the findings on understanding different types of user accounts and the motivations of their following and retweeting behaviors. To the best of our knowledge, this study is the first effort to introduce a community approach for understanding the community characteristics of Sina Weibo and characterizing the similarity of retweeting behaviors and following relationships.

关键词： Communities Educational institutions Correlation Data collection Bipartite graph Twitter

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