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Positional translation language model for ad-hoc information retrieval

Positional translation language model for ad-hoc information...

引用

18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014

作者： Tu, Xinhui Luo, Jing Li, Bo He, Tingting Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Department of Computer Science Central China Normal University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

ISBN: (纸本)9783319066042

Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features that capture the degree to which search terms appear close to each other in a document. Another one considers the use of semantic relationships between words. Previous studies have proven that these two types of information, including term proximity features and semantic relationships between words, are both useful to improve retrieval performance. Intuitionally, we can use them in combination to further improve retrieval performance. Based on this idea, this paper propose a positional translation language model to explicitly incorporate both of these two types of information under language modeling framework in a unified way. In the first step, we present a proximity-based method to estimate word-word translation probabilities. Then, we define a translation document model for each position of a document and use these document models to score the document. Experimental results on standard TREC collections show that the proposed model achieves significant improvements over the state-of-the-art models, including positional language model, and translation language models. © 2014 Springer International Publishing.

关键词： information retrieval

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Efficient latent structural perceptron with hybrid trees for semantic parsing

Efficient latent structural perceptron with hybrid trees for...

引用

23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Zhou, Junsheng Xu, Juhong Qu, Weiguang School of Computer Science and Technology Nanjing Normal University China Jiangsu Research Center of Information Security and Privacy Technology China State Key Lab. for Novel Software Technology Nanjing University China

ISBN: (纸本)9781577356332

Discriminative structured prediction models have been widely used in many natural language processing tasks, but it is challenging to apply the method to semantic parsing. In this paper, by introducing hybrid tree as a latent structure variable to close the gap between the input sentences and output representations, we formulate semantic parsing as a structured prediction problem, based on the latent variable perceptron model incorporated with a tree edit-distance loss as optimization criterion. The proposed approach maintains the advantage of a discriminative model in accommodating flexible combination of features and naturally incorporates an efficient decoding algorithm in learning and inference. Furthermore, in order to enhance the efficiency and accuracy of inference, we design an effective approach based on vector space model to extract a smaller subset of relevant MR productions for test examples. Experimental results on publicly availab.e corpus show that our approach significantly outperforms previous systems.

关键词： Inference engines

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Dynamic weighted discrimination power analysis in DCT domain for face and palmprint recognition

Dynamic weighted discrimination power analysis in DCT domain...

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2010 International Conference on information and Communication technology Convergence, ICTC 2010

作者： Leng, Lu Zhang, Jiashu Xu, Jing Khan, Muhammad Khurram Alghathbar, Khaled Sichuan Province Key Lab. of Signal and Information Processing Southwest Jiaotong University Chengdu China Center of Excellence in Information Assurance King Saud University Riyadh Saudi Arabia Information Systems Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

ISBN: (纸本)9781424498062

Discrimination power analysis (DPA) is a statistical analysis combining discrimination concept with discrete cosine transform coefficients (DCTCs) properties. Unfortunately there is not a uniform and effective criterion to optimize the shape and size of premasking window on which the effect of DPA excessively relies. Proper premasking is an auxiliary process to select the feature coefficients that have more discrimination power (DP). Dynamic weighted DPA (DWDPA) is proposed in this paper to enhance the DP of the selected DCTCs without premasking window, in other words, it does not need to optimize the shape and size of premasking window. The DCTCs are adaptively selected according to their discrimination power values (DPVs). More DCTCs with higher DP are preserved. The selected coefficients are normalized and dynamic weighted according to their DPVs. Normalization assures that the DCTCs with large absolute value don't destroy the DP of the other DCTCs that have less absolute value but high DPVs. Dynamic weighting gives larger weights to the DCTCs with larger DPVs which optimizes and enhances the recognition performance. The experimental results on ORL, Yale and PolyU databases show that DWDPA outperforms DPA obviously. © 2010 IEEE.

关键词： Discrete cosine transforms

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A Sentiment Classification Model Based on Syntactic Graph Attention Networks 24

A Sentiment Classification Model Based on Syntactic Graph At...

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2024 International Conference on Intelligent Education and computer technology, IECT 2024

作者： Cheng, Yan Zhou, Ziwei School of Computer Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Prov. Key Lab. of Intelligent Information Processing and Affective Computing of Jiangxi Province 330022 China School of Software Jiangxi Normal University 330022 China

ISBN: (纸本)9798400709920

Text Sentiment Classification, a significant task in Natural Language processing, aims to comprehend user needs and expectations by categorizing the sentiments of texts posted on platforms. Despite their utility, existing models for this task do not fully account for the influence of contextual and syntactic text features on sentiment classification. To address these issues, a text sentiment classification model based on syntactic graph attention network is proposed in this study. The model begins by extracting the contextual features of a sentence using BiGRU. It then generates a syntactic graph through a syntactic analyzer, using the contextual features as the node features of the syntactic graph. A syntactic graph attention network is constructed to extract the syntactic features of the syntactic graph. These feature vectors are then input into a softmax function to achieve text sentiment classification. Experimental results indicate that the proposed model outperforms similar models on two public datasets in terms of classification accuracy, thus demonstrating its effectiveness. © 2024 ACM.

关键词： Syntactics

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Adversarial Recovery Network for Low-Light Person Re-Identification 23

Adversarial Recovery Network for Low-Light Person Re-Identif...

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6th International Conference on Image and Graphics processing, ICIGP 2023

作者： Xu, Liu Wang, Xiao Yuan, Xin Mao, Zhu Xu, Xin School of Computer Science and Technology Wuhan University of Science and Technology China School of Computer Science and Technology Wuhan University of Science and Technology ChinaHubei Prov. Key Lab. of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology China

ISBN: (纸本)9781450398572

Person re-identification (re-ID), which is to connect pedestrians with the same identity in different scenarios, has been more widely used in case detection of security. The re-ID datasets and technology have contributed greatly to advancing community research. There are currently no availab.e low-light datasets due to the difficulty of collecting and lab.ling images of people in low-light scenes. As a result, the vast majority of current re-ID methods do not have the recognition capability in low-light scenes. However, the recognition of persons in the low-light surveillance video has become an important issue to be solved for urban security, which plays an important role in improving the crime-solving rate of public safety departments and protecting people's lives and property. In this paper, we propose an Adversarial Recovery Network (ARN) that, unlike other approaches, enables a re-ID model with low-light recognition capability without the need for low-light data. Specifically, we first degrade the original images to generate multi-level low-light images;then obtain recovered images through the adversarial recovery module, and finally input the recovered images into the CNN network to extract pedestrian recognition knowledge. In addition, to validate the effectiveness of the proposed method, we also propose a low-light re-ID dataset (LOLR). Extensive experiments on LOLR have shown that our method outperforms other competitors by a wide margin. The dataset and code are availab.e online at https://***/xl02111/ARN. © 2023 ACM.

关键词： Recovery

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EFFICIENT ONLINE lab.L CONSISTENT HASHING FOR LARGE-SCALE CROSS-MODAL RETRIEVAL

EFFICIENT ONLINE LABEL CONSISTENT HASHING FOR LARGE-SCALE CR...

引用

2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Yi, Jinhan Liu, Xin Cheung, Yiu-Ming Xu, Xing Fan, Wentao He, Yi Department of Computer Science and Technology Huaqiao University Xiamen361021 China Xiamen Key Lab. of Computer Vision and Pattern Recognition Fujian Key Lab. of Big Data Intelligence and Security China Department of Computer Science Hong Kong Baptist University Kowloon Hong Kong School of Computer Science and Engineering University of Electronic Science and Technology of China China Provincial Key Laboratory for Computer Information Processing Technology Soochow University China

ISBN: (纸本)9781665438643

Existing cross-modal hashing still faces three challenges: (1) Most batch-based methods are unsuitable for processing large-scale and streaming data. (2) Current online methods often suffer from insufficient semantic association, while lacking flexibility to learn the hash functions for varying streaming data. (3) Existing supervised methods always require much computation time or accumulate large quantization loss to learn hash codes. To address above challenges, we present an efficient Online lab.l Consistent Hashing (OLCH) for cross-modal retrieval, which aims to incrementally learn hash codes for the current arriving data, while updating the hash functions at a streaming manner. To be specific, an online semantic representation learning framework is designed to adaptively preserve the semantic similarity across different modalities, and a mini-batch online gradient descent approach associated with forward-backward splitting is developed to optimize the hash functions. Accordingly, the hash codes are adaptively learned online with the high discriminative capability, while avoiding high computation complexity to process the streaming data. Experimental results show its outstanding performance in comparison with the-state-of-arts. © 2021 IEEE computer Society. All rights reserved.

关键词： Hash functions

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引用

2nd World Congress on computer Science and information Engineering, CSIE 2011

作者： Wang, Haiyan Wang, Ying Yue, Xiwen College of Computer Science Nanjing University of Posts and Telecommunications Nanjing 210003 Jiangsu China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing 210003 Jiangsu China Key Lab. of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province Nanjing 210003 Jiangsu China

ISBN: (纸本)9783642257650

A novel trust transmission method which is based on the similarities of nodes in trust models is proposed in this paper. Trust transmission is evaluated by calculating the similarity between recommenders when trustor does not have direct interaction with trustee. However, when there does not have direct recommenders, trust transmission is realized by guaranteed trust chains. Simulation results show that the proposed method improves the trustworthiness of node behavior to some extent and is practical especially in case when nodes do not know each other. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Network security

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A trusted network remediation scheme based on the stability of access terminals

引用

2nd World Congress on computer Science and information Engineering, CSIE 2011

作者： Wang, Haiyan Xu, Mingming College of Computer Nanjing University of Posts and Telecommunications 210003 Nanjing Jiangsu China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks 210003 Nanjing Jiangsu China Key Lab. of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province 210003 Nanjing Jiangsu China

ISBN: (纸本)9783642257650

To improve the effectiveness of control and remediation of failure access terminals in trusted network, a novel remediation scheme is proposed in this paper. Based on the introduction of a definition of stability of access terminals and the employment of the architecture of trusted network connect(TNC), the proposed remediation scheme can not only realize a dynamic control on terminal's behaviors but also support a trustworthy remediation. Simulation results demonstrate that the proposed scheme is more effective compared with static and integrity-based remediation scheme and significantly improve the speed of remediation. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Remediation

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A dynamic multi-strategies scheduling algorithm for heterogeneous computing systems 21

A dynamic multi-strategies scheduling algorithm for heteroge...

引用

21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Lv, Xiangyu Hu, Wei Wang, Yonghao College of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System China Digital Media Lab Birmingham City University United Kingdom

ISBN: (纸本)9781728120584

Efficient scheduling algorithms play an essential part in heterogeneous computing systems (HeCS) to achieve high performance. So we proposed a new efficient dynamic multi-strategies scheduling algorithm (DMS). The basic idea of this algorithm is to reduce communication in the priority calculation phase and task mapping phase. In the priority calculation phase, the algorithm increases the weight of the task. During the task mapping phase, three approaches for mapping tasks are proposed, and the method which reduces the most communication time among the three approaches is chosen as the task mapping standard. The results of the algorithm presented in this paper demonstrate improved performance in terms of speedup, and schedule length ratio. © 2019 IEEE.

关键词： Scheduling algorithms

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Research on remote heterogeneous disaster recovery technology in grid computing security

Research on remote heterogeneous disaster recovery technolog...

引用

2006 2nd International Conference on Semantics Knowledge and Grid, SKG

作者： Wu, Ronghui Li, Renfa Yu, Fei Yue, Guangxue Wen, Jigang School of Computer and Communication Hunan University Changsha 410082 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Provincial Key Laboratory of Computer Information Processing Technology Jiangsu Province Suzhou University Suzhou 150063 China College of Informationg Engineering JiaXing University JiaXing 314000 China

ISBN: (纸本)0769532055

The tradition standby mechanism can't carry out the dynamic Disaster Recovery of database between distributed isomeric storage systems, accordingly, research the method of allopatric isomeric backup based on grid calculation is an important research subject. In this paper, some technique and strategy of allopatric isomeric backup in grid calculation environment are researched by comparing and analyzing the existing technique of database allopatric backup, a remote-data copy method is presented, a remote-data disaster dump system and a allopatric isomeric data Disaster Recovery tool are designed and implemented based on interlaver. © 2006 IEEE.

关键词： Middleware

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