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检索条件"机构=Key Lab of Streaming Data Computing Technologies and Applications"

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Topic Representation:A Novel Method of Tag Recommendation for Text 2

Topic Representation:A Novel Method of Tag Recommendation fo...

引用

2017 IEEE 2nd International Conference on Big data Analysis（ICBDA 2017）

作者： Shangru Zhong Kai Lei Xiaohui Huang Jincheng Wu Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology & Applications School of Electronic and Computer Engineering Peking University

ISBN: (纸本)9781509036202

With tags widely used in organizing and searching contents in massive data era,how to automatically generate appropriate tags of resource for users became a hot issue on social networks *** recommendation for text resource can be modeled as a keyword extraction problem,hence topic modeling such as LDA which extracts latent semantic topics from text is suitable for tag ***,latent topics are too coarse-grained to describe ***,LDA trains corpus globally without considering context ***,topics generated are difficult to be quantifiably *** problems lead to the poor quality of tag recommendation in topic model based *** this paper,we propose topic representation method,which introduces embedding semantic representation into topic *** results of evaluation on real social networks show that the proposed method improves the quality of tag recommendation for Chinese text resource,when comparing with traditional LDA-based method,which demonstrates the effectiveness of modifying topic modeling.

关键词： Tag recommendation topic model LDA word embedding

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Syndromes Diagnostic Model for Coronary Artery Disease(CAD):An Improved Na?ve Bayesian Classification Model Based on Attribute Relevancy 2

Syndromes Diagnostic Model for Coronary Artery Disease(CAD):...

引用

2017 IEEE 2nd International Conference on Big data Analysis（ICBDA 2017）

作者： Kai Lei Lizhu Zhang Ying Shen Xiaohui Huang Jincheng Wu Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering Peking University

ISBN: (纸本)9781509036202

Clinical decision support is a probabilistic and quantitative method learning used for problem modeling in situations of ***,mathematical methods such as probability learning and statistical analysis is increasingly used in the medical field to assure the accuracy of the diagnoses and optimize the *** study describes the design and implementation of an improved weighted Na?ve Bayes classifier based on the idea that there is a certain level of dependency between *** the coronary artery disease,clinical data and patients' medical records were used to train the improved Na?ve Bayes classifier to compute the possible disease manifestations,the priori probability and the posterior probability and to carry out the disease ***,we were able to improve the precision of the improved weighted Na?ve Bayes classifier to 79%(increase of 12% compared to Na?ve Bayes).The suitability of the improved Na?ve Bayes classifiers for carrying out diagnosis allows them to be utilized to distinguish syndromes and signs based on unobserved evidence.

关键词： Na?ve Bayes decision support diagnostic classification attribute relevancy negative symptoms coronary artery disease

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BCStore: Bandwidth-Efficient in-memory kv-store with batch coding 33

BCStore: Bandwidth-Efficient in-memory kv-store with batch c...

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33rd International Conference on Massive Storage Systems and Technology, MSST 2017

作者： Li, Shenglong Zhang, Quanlu Yang, Zhi Dai, Yafei Peking University China Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications China

In-memory key-value store KV-store is a crucial building block for many systems including large-scale web services and databases. Recent research works pay close attention to data availability of in-memory KV-store. Replication is a common solution to achieve data availability, but the significant memory consumption makes it not applicable for memoryintensive applications. Integrating erasure coding into inmemory KV-store is an emerging approach to achieve memory efficiency. However, traditional in-place update mechanism of erasure coding incurs significant bandwidth cost for writeintensive workload due to frequent broadcast of data update. In this paper, we build BCStore, a bandwidth-efficient inmemory KV-store with erasure coding. We propose a novel batch coding mechanism to optimize the bandwidth cost, and verify its feasibility and efficiency through theoretical analysis. To recycle the memory space due to delete and update operations, we design an efficient move-based garbage collection (GC) mechanism with a novel data layout called virtual coding stripe. Besides, BCStore guarantees consistent data read and write under these new designs, and supports fast online data recovery. We evaluate the performance of BCStore under various workloads. Experimental results show that BCStore can save up to 41% memory compared with replication, and achieve up to 2.4x throughput improvement and 51% bandwidth saving compared to erasure coding with in-place update. © 33rd International Conference on Massive Storage Systems and Technology, MSST 2017. All rights reserved.

关键词： Bandwidth

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An Enhanced Computational Feature Selection Method for Medical Synonym Identification via Bilingualism and Multi-corpus Training 2

An Enhanced Computational Feature Selection Method for Medic...

引用

2017 IEEE 2nd International Conference on Big data Analysis（ICBDA 2017）

作者： Kai Lei Shangchun Si Desi Wen Ying Shen Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering(SECE) Peking University

ISBN: (纸本)9781509036202

Medical synonym identification has been an important part of medical natural language processing(NLP).However,in the field of Chinese medical synonym identification,there are problems like low precision and low recall *** solve the problem,in this paper,we propose a method for identifying Chinese medical *** first selected 13 features including Chinese and English *** we studied the synonym identification results of each feature alone and different combinations of the *** the comparison among identification results,we present an optimal combination of features for Chinese medical synonym *** show that our selected features have achieved 97.37% precision rate,96.00% recall rate and 97.33% F1 score.

关键词： medical synonym feature selection bilingual multi-corpus

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Open domain question answering with character-level deep learning models

Open domain question answering with character-level deep lea...

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作者： Lei, Kai Deng, Yang Zhang, Bing Shen, Ying Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering Peking University Shenzhen518055 China

ISBN: (纸本)9781538636749

Single-relation factoid question answering (QA) is strongly supported by rich sources of facts from knowledge bases (KB). However, there are many irrelevant information in questions and overwhelming number of facts in knowledge bases, making it difficult to capture goal entity and relation involved in a question. In order to settle these issues, firstly, a state-of-the-art sequence tagging model (BiLSTM-CRF) is adopted to detect the entity mention in a question. Then, we propose a n-gram match (NGM) algorithm with Chinese-specific rules and an attention-based siamese bidirectional long-short term memory (ASBLSTM) model to measure the lexical and semantic similarity between questions and candidate facts. Our whole method requires no hand-crafted template or feature engineering. In addition, character-level models are proved to be effective in solving the out of vocabulary (OOV) issue and improving the accuracy in Chinese KBQA task. Experiment results show that our system outperforms the best system with deep learning models in the KBQA share task of the Conference on Natural Language Processing and Chinese computing (NLPCC) 2016 and our system achieves an AverageF1 measure of 80.97% and 37.18% on test dataset in NLPCC 2016 and 2017 respectively. © 2017 IEEE.

关键词： Entity extraction Entity linking Knowledge base question answering Relation recognition

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On Star Coloring of Mycielski's Graphs for Special Graphs

On Star Coloring of Mycielski's Graphs for Special Graphs

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Cai Jin Shuangliang Tian Zhuomo An School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781728186696

Let G be a simple graph with vertex set V (G) and edge set E (G). A vertex coloring of G is called a star coloring of G if any path of 4 order is bicolored. The minimum number of colors required for a star coloring of G is denoted by χ s (G). Let G is a simple graph with vertex set V (G) = V and edge set E (G) = E, if the vertex set is V ∪ V' ∪ {w} where V' = {X' : x ∈ V} and the edge set is EU{xy' : xy∈V} U {y'w : y'∈V'}, then G is a Mycielski's graph. This paper mainly studies star coloring of Mycielski's graph for some special graphs, the specific results are as follows: if n = 2,3 , then χ s (M (P n )) = 4, otherwise, χ s (M (P n )) = 6 ; if n = 5, then χ s (M(C n )) = 8, otherwise, χ s (M(C n )) = 6 ; χ s (M(S n )) = 4 ; χ s (M (K n )) = n + 2.

关键词： Computer science Color

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The acyclic coloring of the Corona product and Edge corona product of special graphs

The acyclic coloring of the Corona product and Edge corona p...

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Qiqi Lu Shuangliang Tian Lizhen Peng School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

An acyclic coloring of a graph is a proper vertex coloring such that there are no bichromatic cycles. The acyclic chromatic number of G, denoted a(G), is the minimum number of colors required for acyclic coloring of a graph G. We study the acyclic coloring of the corona product, edge corona product of paths or circles and any simple graph, and the corresponding acyclic chromatic number are determined.

关键词： Computer science Color Corona

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Adjacent vertex distinguishing incidence coloring of semi-strong product of paths

Adjacent vertex distinguishing incidence coloring of semi-st...

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Lizhen Peng Shuangliang Tian Qiqi Lu School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781728186696

Adjacent vertex distinguishing incidence coloring of graph G is an incidence coloring that satisfies that adjacent vertices have different color sets, and the minimum color number is called the adjacent vertex distinguishing incidence coloring number of graph G, which is denoted as χ ai (G). In this paper, we study the adjacent vertex distinguishing incidence coloring of semi-strong products and strong products of paths of different orders, and obtain the exact values of the corresponding coloring numbers.

关键词： Computer science Color

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An Entropy-based Probabilistic Forwarding Strategy in Named data Networking

An Entropy-based Probabilistic Forwarding Strategy in Named ...

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IEEE International Conference on Communications

作者： Kai Lei Jiawei Wang Jie Yuan Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology & Applications School of Electronics and Computer Engineering (SECE) Peking University

ISBN: (纸本)9781467364300

The forwarding strategy is the key to the resiliency and efficiency of Named data Networking (NDN), which is a new and fundamental research area. For forwarding strategy, dynamically selecting an optimal interface from multiple alternative interfaces to forward an Interest packet is indeed a multiple attribute decision making (MADM) problem. In this paper, an entropy-based probabilistic forwarding (EPF) strategy is proposed to make a stochastic interface selection based on the combination of interfaces' dynamic availabilities and static routing information, which achieves better load balance in comparison with deterministic interface selection. By objectively assigning weights to attributes and considering multiple real-time network condition metrics, EPF can obtain the availabilities of interfaces more accurately and comprehensively. Since additional network metrics can be easily added and integrated into interfaces' assessment model, EPF provides good extensibility. In addition, we innovatively define two parameters (γ, δ) which can be used to trade off the effect factors between static routing information and dynamic running status of interfaces to customize EPF strategy for different network and application scenarios. Experiments show that EPF can realize preferable load balance and achieve higher throughput compared to the representative BestRoute forwarding strategy.

关键词： Entropy Throughput Routing Probabilistic logic Load modeling Packet loss

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Internet Traffic Analysis Using Community Detection and Apache Spark

Internet Traffic Analysis Using Community Detection and Apac...

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第九届网络分布式计算与知识发现国际会议( 2017 International Conference on Cyber-enabled distributed computing and knowledge discovery)

作者： Jiake Ni Weitao Weng Jiayu Chen Kai Lei Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology & Applications School of Electronic and Computer Engineering(SECE)Peking University SHENZHEN 518055P.R.CHINA

With the rapid development of Internet,Internet traffic and end hosts continue to grow in *** behavior analysis for a large-scale network is becoming more and more *** address these challenges,this paper proposes an Internet traffic analysis approach based on community detection to discover community consisted of end hosts with similar traffic behavior in a large campus ***,we use only the IP-to-IP information without packet payloads to model the similarity of end hosts in campus *** the similarity graph which represent the social behavior similarity of all end hosts is ***,we leverage label Propagation algorithm to discover end hosts community on the similarity *** satisfy demands for the scalable analysis of evergrowing Internet traffic data,a Spark-based Internet traffic analysis system is developed,including implementing the above *** experimental results based on real campus network traffic show the benefits of the proposed approach in analyzing traffic behavior of a large-scale network on host community level and detecting potential anomalous traffic *** proposed approach reduces the complexity of analyzing the traffic behavior of a large network compare with analyzing individual *** addition,the experimental results also demonstrate the Spark-based Internet traffic analysis system can analyze Internet traffic efficiently.

关键词： Internet traffic analysis community detection Apache Spark data mining

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