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检索条件"机构=Language Information Processing and Cloud Computing Application"

共 172 条记录，以下是31-40 订阅

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An Efficient and Secure RFID Batch Authentication Protocol with Group Tags Ownership Transfer

An Efficient and Secure RFID Batch Authentication Protocol w...

引用

International Conference on Collaborative computing: Networking, applications and Worksharing (CollaborateCom)

作者： Rong Zhang Liehuang Zhu Chang Xu Yi Yi Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application Beijing Institute of Technology Beijing China

Tag Authentication is an essential issue in RFID system which is wildly applied in many areas. Compared to the per-tag-based authentication, the batch-mode authentication has better performance for complex applications. However, many existing batch authentication protocols suffer from security and privacy threats, low efficiency problem or high communication and computation cost. In order to solve these problems better, we propose a new RFID batch authentication protocol. In this protocol, tags are grouped and each key in one group shares the same group key. The connection between the group key and the tag's own key is fully utilized to construct our batch authentication protocol. Meanwhile, based on the proposed batch authentication protocol, we propose a group tags ownership transfer protocol which also supports the tag authorisation recovery. Compared with previous schemes, our scheme achieves stronger security and higher efficiency. In the side of security and privacy, our scheme meets most requirements, such as tag information privacy, forward/backward security, resistance against reply, tracking, and Dos attacks. Then we carry on the theoretical analysis and implement the simulation experiment. Both of them indicate that the performance of our scheme is much efficient than other authentication schemes. Particularly, the simulation results show that the run time of the whole authentication process in our scheme is decreased 20% at least compared with the other existing schemes.

关键词： Protocols Authentication Radiofrequency identification Privacy Servers Computer crime

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cloud Storage-oriented Secure information Gateway

Cloud Storage-oriented Secure Information Gateway

引用

International Conference on cloud and Service computing (CSC)

作者： Qiongyu Zhang Liehuang Zhu Huishan Bian Xiaoyao Peng Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application Beijing Institute of Technology Beijing China

The Secure Channel Free Public Key Encryption with Keyword Search (SCF-PEKS) scheme, which enables one to search for the encrypted keywords without leaking the privacy. In this paper, we point out the inefficiency of SCF-PEKS scheme and construct a new Located Secure Channel Free Public Key Encryption with Keyword Search (LSCF-PEKS) scheme to improve the efficiency. Furthermore, the LSCF-PEKS scheme is applied to implement cloud storage-oriented secure information gateway. At last, a bidding system is implemented as a case of this scenario.

关键词： Logic gates cloud computing Keyword search Public key Encryption Databases

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Exploiting Knowledge Embedding to Improve the Description for Image Captioning 5th

Exploiting Knowledge Embedding to Improve the Description fo...

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5th China Conference on Knowledge Graph, and Semantic computing, CCKS 2020

作者： Song, Dandan Peng, Cuimei Yang, Huan Liao, Lejian Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Key Laboratory of Intelligent Information Technology School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9789811619632

Most existing methods for image captioning are based on the encoder-decoder framework which directly translates visual features into sentences, without exploiting commonsense knowledge available in the form of knowledge graph. Inspired by the success of information retrieval and question answering systems that leverage prior knowledge, we explore a knowledge embedding approach for image captioning. In this paper, we propose a Knowledge Embedding with Attention on Attention (KE-AoA) method for image captioning, which judges whether or how well the objects are related and augments semantic correlations and constraints between them. The KE-AoA method combines knowledge base method (TransE) and text method (Skip-gram), adding external knowledge graph information (triplets) into the language model to guide the learning of word vectors as the regularization term. Then it employs the AoA module to model the relations among different objects. As more inherent relations and commonsense knowledge are learned, the model can generate better image descriptions. The experiments on MSCOCO data sets achieve a significant improvement on the existing methods and validate the effectiveness of our prior knowledge-based approach. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Knowledge graph

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Deep Hashing with Attribute Guidance for Image Retrieval 4

Deep Hashing with Attribute Guidance for Image Retrieval

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4th International Conference on Artificial Intelligence, Automation and Control Technologies, AIACT 2020

作者： Lu, Yao Huang, Heyan Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications Department of Computer Science and Technology Beijing Institute of Technology China

Similarity-preserving hashing is an important method to solve approximate nearest neighbour search problem for image retrieval. Lots of works have been proposed for supervised hashing and image category labels are utilized as supervised information. However, current works ignore a fact that images can be described by a set of attributes. Intuitively, images of different categories with close visual features can be separated by their attribute features because attributes keep more detailed information. In this paper, we propose a novel supervised deep hashing method with image attribute guidance. Specifically, hash codes are learnt through image visual features and guided by image attributes by maintaining pair wise similarities between images as well as the corresponding attribute descriptions. Extensive experimental results on two benchmark datasets show that our proposed method achieves better performance compared with the state of the art hashing methods. © Published under licence by IOP Publishing Ltd.

关键词： Image retrieval

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Identifying suspected cybermob on Tieba 15th

Identifying suspected cybermob on Tieba

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15th China National Conference on Chinese Computational Linguistics, CCL 2016 and 4th International Symposium on Natural language processing Based on Naturally Annotated Big Data, NLP-NABD 2016

作者： Shi, Shumin Zhou, Xinyu Zhao, Meng Huang, Heyan School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

ISBN: (纸本)9783319476735

This paper describes an approach to identify suspected cybermob on social media. Many researches involve making predictions of group emotion on Internet (such as quantifying sentiment polarity), but this paper instead focuses on the origin of information diffusion, namely back to its makers and contributors. According our previous findings that have shown, at the level of Tieba’s contents, the negative information or emotions spread faster than positive ones, we centre on the maker of negative message in this paper, so-called cybermobs who post aggressive, provocative or insulting remarks on social websites. We explore the different characteristics between suspected cybermobs and general netizens and then extract relative unique features of suspected cybermobs. We construct real system to identify suspected cybermob automatically using machine learning method with above features, including other common features like user/content-based ones. Empirical results show that our approach can detect suspected cybermob correctly and efficiently as we evaluate it with benchmark models, and apply it to actual cases. © Springer International Publishing AG 2016.

关键词： Artificial intelligence

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Reducing Length Bias in Scoring Neural Machine Translation via a Causal Inference Method 20

Reducing Length Bias in Scoring Neural Machine Translation v...

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20th China National Conference on Computational Linguistics, CCL 2021

作者： Shi, Xuewen Huang, Heyan Jian, Ping Tang, Yi-Kun School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing100081 China

ISBN: (纸本)9783030841850

Neural machine translation (NMT) usually employs beam search to expand the searching space and obtain more translation candidates. However, the increase of the beam size often suffers from plenty of short translations, resulting in dramatical decrease in translation quality. In this paper, we handle the length bias problem through a perspective of causal inference. Specifically, we regard the model generated translation score S as a degraded true translation quality affected by some noise, and one of the confounders is the translation length. We apply a Half-Sibling Regression method to remove the length effect on S, and then we can obtain a debiased translation score without length information. The proposed method is model agnostic and unsupervised, which is adaptive to any NMT model and test dataset. We conduct the experiments on three translation tasks with different scales of datasets. Experimental results and further analyses show that our approaches gain comparable performance with the empirical baseline methods. © 2021, Springer Nature Switzerland AG.

关键词： Neural machine translation

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Chinese parsing model based on constraint dependency grammar

Chinese parsing model based on constraint dependency grammar

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2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012

作者： Li, Peng Liao, Lejian Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9781457714153

Constraint Dependency Grammar (CDG) is a formalism representing grammatical rules as constraints on dependency relations. It reduces the structural ambiguity via constraint-propagation without generating individual parse trees. In this paper, we propose a high quality parsing model for Chinese, which defines the phrase molecule lexicalizing the CDG at the word-level. Ternary constraints are used to improve the accuracy and efficiency of parsing. © 2012 IEEE.

关键词： Formal languages

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A hierarchy-based constraint dependency grammar parsing for Chinese

A hierarchy-based constraint dependency grammar parsing for ...

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2012 3rd IEEE/IET International Conference on Audio, language and Image processing, ICALIP 2012

作者： Li, Peng Liao, Lejian Li, Xin Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9781467301718

Constraint Dependency Grammar (CDG) is a well known formalism which represents the grammatical rules as constraints on dependency relations. It reduces the structural ambiguities via constraint-propagation instead of generating individual parse trees as the conventional works. In our previous work, we have successfully adopted CDG in Chinese [5]. In this paper, we tend to further explore the nature of the constraints for Chinese CDG. We propose to develop a schema of three hierarchies for the constraints, namely in-the-phrase, between-the-phrase and between-the-simple-sentence, which is based on a study of constraints in corpus with a prior knowledge. With this proposed schema, we could further diminish the ambiguities caused by the originally defined constraints which is lack of hierarchical grammar information considered, The experiments are conducted and the results support our claims. © 2012 IEEE.

关键词： Formal languages

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ET5: A Novel End-to-end Framework for Conversational Machine Reading Comprehension 29

ET5: A Novel End-to-end Framework for Conversational Machine...

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29th International Conference on Computational Linguistics, COLING 2022

作者： Zhang, Xiao Huang, Heyan Chi, Zewen Mao, Xian-Ling School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Southeast Academy of Information Technology Beijing Institute of Technology China

Conversational machine reading comprehension (CMRC) aims to assist computers to understand an natural language text and thereafter engage in a multi-turn conversation to answer questions related to the text. Existing methods typically require three steps: (1) decision making based on entailment reasoning;(2) span extraction if required by the above decision;(3) question rephrasing based on the extracted span. However, for nearly all these methods, the span extraction and question rephrasing steps cannot fully exploit the fine-grained entailment reasoning information in decision making step because of their relative independence, which will further enlarge the information gap between decision making and question phrasing. Thus, to tackle this problem, we propose a novel end-to-end framework for conversational machine reading comprehension based on shared parameter mechanism, called entailment reasoning T5 (ET5). Despite the lightweight of our proposed framework, experimental results show that the proposed ET5 achieves new state-of-the-art results on the ShARC leaderboard with the BLEU-4 score of 55.2. Our model and code are publicly available © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Decision making

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Contracting of web services with constraint handling rules

Contracting of web services with constraint handling rules

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2012 IEEE 8th World Congress on Services, SERVICES 2012

作者： Chen, Ruoyu Liao, Lejian Fang, Zhi Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications Multi-living-agent Information System Key Laboratory Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9780769547565

In e-service environment, service contract is important for assurance of business interoperability and quality of services. Combining service contract and process model will facilitate analyzing service process and monitoring service execution. This paper proposes a service modeling approach consists of service contract and process model. Service contracts are used as service advertisement and service request in this approach. The operational semantics of service contract and process model are translated into Constraint Handling Rules(CHR) program by a compiler. Based on this approach, a concept named service contracting is defined as a phase between service discovery and execution, which checks the consistency of service advertisement and process model as well as the the applicability of services w.r.t. the consumer's capabilities. Further, constraint solver centered implementation is designed, the modeling and contracting of web services under this architecture is illustrated. © 2012 IEEE.

关键词： Web services

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