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26th International Conference on Computational Linguistics, COLING 2016

作者： Li, Bofang Zhao, Zhe Liu, Tao Wang, Puwei Du, Xiaoyong School of Information Renmin University of China Key laboratory of Data Engineering and Knowledge Engineering MOE China

ISBN: (纸本)9784879747020

NBSVM is one of the most popular methods for text classification and has been widely used as baselines for various text representation approaches. It uses Naive Bayes (NB) feature to weight sparse bag-of-n-grams representation. N-gram captures word order in short context and NB feature assigns more weights to those important words. However, NBSVM suffers from sparsity problem and is reported to be exceeded by newly proposed distributed (dense) text representations learned by neural networks. In this paper, we transfer the n-grams and NB weighting to neural models. We train n-gram embeddings and use NB weighting to guide the neural models to focus on important words. In fact, our methods can be viewed as distributed (dense) counterparts of sparse bag-of-n-grams in NBSVM. We discover that n-grams and NB weighting are also effective in distributed representations. As a result, our models achieve new strong baselines on 9 text classification datasets, e.g. on IMDB dataset, we reach performance of 93.5% accuracy, which exceeds previous state-of-the-art results obtained by deep neural models. All source codes are publicly available at https://***/zhezhaoa/neural-BOW-toolkit. © 1963-2018 ACL.

关键词： Classification (of information)

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Approximation algorithm for constructing data aggregation trees for wireless sensor networks

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中国高等学校学术文摘·计算机科学 2009年第4期3卷 524-534页

作者： Deying LI Jiannong CAO Qinghua ZHU Key Laboratory of Data Engineering and Knowledge Engineering School of InformationRenmin University of ChinaBeijing 100872China Internet and Mobile Computing Lab Department of ComputingHong Kong Polytechnic UniversityHong KongChina

This paper considers the problem of constructing data aggregation trees in wireless sensor networks (WSNs)for a group of sensor nodes to send collected information to a single sink *** data aggregation tree contains the sink node,all the source nodes,and some other non-source *** goal of constructing such a data aggregation tree is to minimize the number of non-source nodes to be included in the tree so as to save *** prove that the data aggregation tree problem is NP-hard and then propose an approximation algorithm with a performance ratio of four and a greedy *** also give a distributed version of the approximation *** simulations are performed to study the performance of the proposed *** results show that the proposed algorithms can find a tree of a good approximation to the optimal tree and has a high degree of scalability.

关键词： WSNs data aggregation tree approximation algorithm distributed algorithm

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Efficient SPARQL query evaluation via automatic data partitioning

Efficient SPARQL query evaluation via automatic data partiti...

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18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Yang, Tao Chen, Jinchuan Wang, Xiaoyan Chen, Yueguo Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China

ISBN: (纸本)9783642374494

The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like Hadoop is a good choice for processing queries over large data sets. Previous works on evaluating SPARQL queries with Hadoop mainly focus on reducing the number of joins through careful split of HDFS files and algorithms for generating Map/Reduce jobs. However, the way of partitioning RDF data could also affect the performance. Specifically, a good partitioning will greatly reduce or even totally avoid cross-node joins and significantly reduce the cost of query evaluation. Based on HadoopDB, this work processes SPARQL queries in a hybrid architecture where Map/Reduce takes charge of the computing tasks and an RDF query engine, RDF-3X, stores the data and evaluates join operations over local data. Based on analysis of query work-loads, we propose a novel algorithm for automatically partitioning RDF data. We also present an approximate solution to physically place the partitions in order to reduce data redundancy. All the proposed approaches are evaluated by extensive experiments over large RDF data sets. © Springer-Verlag 2013.

关键词： Resource Description Framework (RDF)

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Cutting Learned Index into Pieces: An In-depth Inquiry into Updatable Learned Indexes 39

Cutting Learned Index into Pieces: An In-depth Inquiry into ...

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Ge, Jiake Shi, Boyu Chai, Yanfeng Luo, Yuanhui Guo, Yunda He, Yinxuan Chai, Yunpeng Moe Key Laboratory of Data Engineering and Knowledge Engineering China Renmin University of China School of Information China

ISBN: (纸本)9798350322279

Numerous high-performance updatable learned indexes have recently been designed to support the writing requirements in practical systems. Researchers have proposed various strategies to improve the availability of updatable learned indexes. However, it is unclear which strategy is more profitable. Therefore, we deconstruct the design of learned indexes into multiple dimensions and in-depth evaluate their impacts on the overall performance, respectively. Through the in-depth exploration of learned indexes, we reckon that the approximation algorithm is the most crucial design dimension for improving the performance of the learned indexes rather than the popular works that focus on the learned index structure. Moreover, this paper makes a comprehensive end-to-end evaluation based on a high-performance key-value store to answer people's concerns about which learned index is better and whether learned indexes can outperform traditional ones. Finally, according to end-to-end and in-depth evaluation results, we give some constructive suggestions on designing a better learned index in these dimensions, especially how to design an excellent approximate algorithm to improve the lookup and insertion performance of learned indexes. © 2023 IEEE.

关键词： Approximation algorithms

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Optimization framework for distributed clustering scheme in wireless sensor networks

Optimization framework for distributed clustering scheme in ...

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SNPD 2007: 8th ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing

作者： Yongxuan, Lai Xiaobo, Fan Hong, Chen Tingting, Xie School of Information Renmin University of China Beijing Key Laboratory of Data Engineering and Knowledge Engineering MOE

ISBN: (纸本)0769529097

Recently there have been growing interests in the applications of wireless sensor networks. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach and data gathering protocol in wireless sensor networks. In this paper, we propose a novel optimization framework called MICA (MICa Adjustments) for clustering scheme in wireless sensor networks. MICA takes the cluster as a whole, and dynamically adjusts the clusters according to the real-lime workload of the local clusters to balance energy consumption among clusters. The adjustments can also deal with link failures. Simulation results show that MICA can be easily embedded into existing clustering schemes to balance the energy consumptions among the clusters, and to prolong the lifetime of wireless sensor networks. © 2007 IEEE.

关键词： Wireless sensor networks

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A sampling-based algorithm for approximating maximum average value region in wireless sensor network

A sampling-based algorithm for approximating maximum average...

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International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems

作者： Zhang, Hao Wu, Zhongbo Li, Deying Chen, Hong School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China

ISBN: (纸本)9780769541570

in wireless sensor network, sensory readings are often noisy due to the imprecision of measuring hardware and the disturbance of deployment environment, so it is often inaccurate if we use individual sensor readings to answer queries. In this paper, we consider a useful application of sensor network: maximum average value region query. This query returns the region with the maximum average value among all possible regions in the network, where the region is a fix-sized circle pre-defined by users. Using the average value of a region to answer the query, noises between sensors will be neutralized with each other, which will make the results more reliable. However, because of the huge amount of possible regions in the network, it is costly to process the query exactly. Therefore, w e propose a sampling-based algorithm AMAVR to deal with the problem approximately. AMAVR uses a background value to prun e the useless regions which cannot be the result. A further optimization strategy is also given to handle the situation that, background value based filter does not work when some individual sensor nodes have higher values than their neighbors. By using both of the two techniques, the scale of the sampling population can be effectively reduced, that is, we cost less energy to get a satisfying result. At last, the conducted simulations demonstrate the energy efficiency of the proposed methods in our paper. © 2010 IEEE.

关键词： Sensor nodes

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Fault-tolerant routing: κ-inconnected many-to-one routing in wireless networks

Fault-tolerant routing: κ-inconnected many-to-one routing i...

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3rd International Conference on Combinatorial Optimization and Applications, COCOA 2009

作者： Li, Deying Zhu, Qinghua Yang, Huiqiang School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China

ISBN: (纸本)3642020259

This paper addresses the problem of fault-tolerant many-to-one routing in static wireless networks with asymmetric links, which is important in both theoretical and practical aspects. The problem is to find a minimum energy subgraph for a given subset and a destination node such that there are κ node-disjoint paths from each node in the subset to the destination node in the subgraph. We prove that the problem is NP-hard, and propose two efficient heuristic approaches, namely, the minimum weight κ node-disjoint paths based (MWkNDPB) approach and the minimum energy κ node-disjoint paths based (MEkNDPB) approach. Extensive simulations have been conducted to show that proposed algorithms are efficient. © 2009 Springer Berlin Heidelberg.

关键词： Wireless networks

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RUC @ INEX 2011 data-centric track

RUC @ INEX 2011 data-centric track

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Lecture Notes in Computer Science

作者： Wang, Qiuyue Gan, Yantao Sun, Yu School of Information Renmin University of China China Key Lab. of Data Engineering and Knowledge Engineering MOE Beijing 100872 China

ISBN: (纸本)9783642357336

We report our experiment results on the INEX 2011 data-Centric Track. We participated in both the ad hoc and faceted search tasks. On the ad hoc search task, we employ language modeling approaches to do structured object retrieval, trying to capture both the structure in data and structure in query and unify the structured and unstructured information retrieval in a general framework. However, our initial experimental results using INEX test bed show that the unstructured retrieval model performs better than structured retrieval models. On the faceted search task, we propose a simple user-simulation model to evaluate the effectiveness of a faceted search system's recommending facet-values. We implemented the evaluation system and conducted the evaluations for the track. We also tested basic redundancy and relevance based approaches for recommending facet-values. The results show that our basic approaches of recommending facet-values perform quite well. © Springer-Verlag 2012.

关键词： XML

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An Adaptive Method for the Efficient Similarity Calculation

An Adaptive Method for the Efficient Similarity Calculation

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14th International Conference on database Systems for Advanced Applications

作者： Cai, Yuanzhe Liu, Hongyan He, Jun Du, Xiaoyong Jia, Xu Key Labs of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China China Department of Management Science and Engineering Tsinghua University China

ISBN: (纸本)9783642008863

SimRank is a well-known algorithm for similarity calculation based on object-to-object relationship. However, it suffers from high computation cost. Inthis paper, we find that the convergence behavior of different object pairs is different when we use SimRank to compute the similarity of objects. Many similarity scores converge fast, while others need more time before convergence. Based on this observation, we propose an adaptive method called Adaptive-SimRank to speed up similarity calculation. Using this method, we don't need to recalculate those converged pairs' similarity. The experiments conducted on web datasets and synthetic dataset show that our new method can reduce the running time by nearly 35%.

关键词： Similarity Calculation Linkage Mining

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Integrated retrieval over structured and unstructured data

Integrated retrieval over structured and unstructured data

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2012 Cross Language Evaluation Forum Conference, CLEF 2012

作者： Wang, Qiuyue Kang, Jinglin School of Information Renmin University of China Beijing100872 China Key Lab of Data Engineering and Knowledge Engineering MOE Beijing100872 China

We report our experiment results on the INEX 2012 Linked data Track. We participated in the ad hoc and jeopardy tasks. As the new data collection on INEX 2012 Linked data Track features a combination of unstructured and structured data, our first attempt is to investigate different strategies of combining the retrievals over structured and unstructured data, and compare the combined approaches with the traditional unstructured ones. In this paper, we discussed three types of combination strategies and we experimented two of them on the track. The experiment results show that.

关键词： Linked data

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