检索结果-南通市图书馆

Patent expanded retrieval via word embedding under composite-domain perspectives

Frontiers of Computer Science 2019年第5期13卷 1048-1061页

作者： Fei WANG Tieyun QIAN Bin LIU zhiyong peng School of Computer Science Wuhan University Wuhan 430072 China State Key Lab of Software Engineering Wuhan University Wuhan 430072 China

Patent prior art search uses dispersed information to retrieve all the relevant documents with strong ambiguity from the massive patent database. This challenging task con-sists in patent reduction and patent expansion. Existing stud-ies on patent reduction ignore the relevance between techni-cal characteristics and technical domains, and result in am-biguous queries. Works on patent expansion expand terms from external resource by selecting words with similar dis-tribution or similar semantics. However, this splits the rele-vance between the distribution and semantics of the terms. Besides, common repository hardly meets the requirement of patent expansion for uncommon semantics and unusual terms. In order to solve these problems, we first present a novel composite-domain perspective model which converts the technical characteristic of a query patent to a specific composite classified domain and generates aspect queries. We then implement patent expansion with double consistency by combining distribution and semantics simultaneously. We also propose to train semantic vector spaces via word em-bedding under the specific classified domains, so as to pro-vide domain-aware expanded resource. Finally, multiple re-trieval results of the same topic are merged based on perspec-tive weight and rank in the results. Our experimental results on CLEP-IP 2010 demonstrate that our method is very effec-tive. It reaches about 5.43% improvement in recall and nearly 12.38% improvement in PRES over the state-of-the-art. Our work also achieves the best performance balance in terms of recall, MAP and PRES.

关键词： patent retrieval composite-domain perspective double-consistency expansion word embedding

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Graphene-based ambipolar electronics for radio frequency applications

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Chinese Science Bulletin 2012年第23期57卷 2956-2970页

作者： WANG ZhenXing ZHANG zhiyong peng LianMao Key Laboratory for the Physics and Chemistry of Nanodevices and Department of Electronics Peking University Beijing 100871 China

Graphene is considered as a promising material to construct field-effect transistors (FETs) for high frequency electronic applications due to its unique structure and properties,mainly including extremely high carrier mobility and saturation velocity,the ultimate thinnest body and *** continuously scaling down the gate length and optimizing the structure,the cut-off frequency of graphene FET (GFET) was rapidly increased and up to about 300 GHz,and further improvements are also *** of the lack of an intrinsic band gap,the GFETs present typical ambipolar transfer characteristic without off state,which means GFETs are suitable for analog electronics rather than digital *** advantage of the ambipolar characteristic,GFET is demonstrated as an excellent building block for ambipolar electronic circuits,and has been used in applications such as highperformance frequency doublers,radio frequency mixers,digital modulators,and phase detectors.

关键词： graphene radio frequency field-effect transistor ambipolar electronics high-κ dielectrics

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Implicit policy constraint for offline reinforcement learning

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 973-981页

作者： zhiyong peng Yadong Liu Changlin Han Zongtan Zhou National University of Defense Technology ChangshaChina

Offline reinforcement learning(RL)aims to learn policies entirely from passively collected datasets,making it a data‐driven decision *** of the main challenges in offline RL is the distribution shift problem,which causes the algorithm to visit out‐of‐distribution(OOD)*** distribution shift can be mitigated by constraining the divergence between the target policy and the behaviour ***,this method can overly constrain the target policy and impair the algorithm's performance,as it does not directly distinguish between in‐distribution and OOD *** addition,it is difficult to learn and represent multi‐modal behaviour policy when the datasets are collected by several different behaviour *** overcome these drawbacks,the au-thors address the distribution shift problem by implicit policy constraints with energy‐based models(EBMs)rather than explicitly modelling the behaviour *** EBM is powerful for representing complex multi‐modal distributions as well as the ability to distinguish in‐distribution samples and *** results show that their method significantly outperforms the explicit policy constraint method and other *** addition,the learnt energy model can be used to indicate OOD visits and alert the possible failure.

关键词： artificial intelligence artificial neural network learning(artificial intelligence) planning(artificial intelligence)

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Wuhan University Journal of Natural Sciences 2018年第4期23卷 347-354页

作者： WU Xia ZHU Yuanyuan peng Yuwei peng zhiyong School of Computer Wuhan University

In recent years, a few researches focus on the similarity measure of semantic trajectories in road networks, since semantic trajectories in road networks have smaller volumes, higher qualities and can better reflect user behaviors. However, these works do not further discuss how to efficiently search similar trajectories. Thus, to implement an efficient similarity search, we design an index called SIET based on the structures of road networks. Then, we propose a novel algorithm called SSN-BF to search similar trajectories efficiently by using best-first strategy. At last, we take the experimental evaluations on real dataset and prove the efficiency of our algorithm.

关键词： semantic trajectory road network trajectory search similarity search

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Attribute Level Lineage in Uncertain Data with Dependencies

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Wuhan University Journal of Natural Sciences 2016年第5期21卷 376-386页

作者： WANG Liang WANG Liwei peng zhiyong State Key Laboratory of Software Engineering Wuhan University School of Computer Wuhan University International School of Software Wuhan University

In uncertain data management, lineages are often used for probability computation of result tuples. However, most of existing works focus on tuple level lineage, which results in imprecise data derivation. Besides, correlations among attributes cannot be captured. In this paper, for base tuples with multiple uncertain attributes, we define attribute level annotation to annotate each attribute. Utilizing these annotations to generate lineages of result tuples can realize more precise derivation. Simultaneously,they can be used for dependency graph construction. Utilizing dependency graph, we can represent not only constraints on schemas but also correlations among attributes. Combining the dependency graph and attribute level lineage, we can correctly compute probabilities of result tuples and precisely derivate data. In experiments, comparing lineage on tuple level and attribute level, it shows that our method has advantages on derivation precision and storage cost.

关键词： uncertain data attribute level lineage dependency

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A Patent Hotspot Discovery Method

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Wuhan University Journal of Natural Sciences 2016年第5期21卷 369-375页

作者： FENG Ling LIU Bin peng zhiyong School of Computer Wuhan University

Due to the importance of patent, many studies have been done in patent analysis. However, the problem of finding the hotspots of competitors is seldom considered. Although there exist some hotspot discovery methods in Micro-blog and online public opinion, it is difficult to be directly applied because of the particularity of the patent text. In this paper, we proposed a text-clustering-based patent hotspot discovery method to find the hotspots of competitors. We first measure the similarity between patents by both semantic association and IPC association. After that, we use a hierarchical clustering algorithm to find the research topics and name for them. Then, we calculate the hotness of the technical phrases in order to find the hotspots. Finally, we use a case study of Huawei company to show the effectiveness of the proposed method.

关键词： hotspot discovery patent clustering

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An Improved Daugman Method for Iris Recognition

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Wuhan University Journal of Natural Sciences 2015年第3期20卷 229-234页

作者： peng zhiyong WANG Hongchen WU Jun LI Jun School of Electrical Engineering and Automation Guilin University of Electronic Technology Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology Editorial Board of Geomatics and Information Science of Wuhan University

An improved Daugman iris recognition algorithm is provided in this paper, which embodies in two aspects： 1 Improvement for iris localization and 2 The improvement for both iris encoding and matching algorithms. In Step 1, the localization and shape of the pupil are roughly determined in iris image, which is used as prior knowledge to quickly locate the inner and outer boundary of iris from rough to fine scale. Eyelids, eyelashes areas and the spot in the pupil are automatically detected and removed to improve the localization accuracy. In Step 2, the possible noise from residual eyelashes is further filtered by selecting a ＂pure＂ iris area as a reference and making a validation judgment pixel-wise. Furthermore, the validation flag for each pixel is introduced into the iris encoding and matching computation, as a result, the rejection rate of iris recognition is reduced. Compared with Daugman algorithm, iris recognition test on collected human eye images shows that our proposed algorithm has an obvious improvement both on boosting the speed and reducing the rejection rate.

关键词： iris recognition iris localization iris encoding

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Public integrity verification for data sharing in cloud with asynchronous revocation

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Digital Communications and Networks 2022年第1期8卷 33-43页

作者： Wei Song Yu Wu Yihui Cui Qilie Liu Yuan Shen Zicheng Qiu Jianjun Yao zhiyong peng School of Computer Science Wuhan UniversityWuhan430074China b School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400054China College of Information Engineering Tarim UniversityAlar CityXinjiang843300China

Cloud data sharing service,which allows a group of people to access and modify the shared data,is one of the most popular and efficient working styles in ***,there is an uprising trend that enterprises tend to move their IT service from local to cloud to ease the management and reduce the *** the new cloud environment,the cloud users require the data integrity verification to inspect the data service at the cloud *** recent studies have focused on this application *** these studies,each user within a group is required to sign a data block created or modified by *** a user is revoked,all the data previously signed by him should be *** the existing research,the resigning process is dependent on the revoked ***,cloud users are *** may exit the system at any time without notifying the system admin and even are revoked due to *** the developers in the cloud-based software development platform,they are voluntary and not strictly controlled by the *** to this feature,cloud users may not always follow the cloud service *** may not participate in generating the resigning key and may even expose their secret keys after being *** the signature is not resigned in time,the subsequent verification will be *** if the secret key is exposed,the shared data will be maliciously modified by the attacker who grasps the ***,forcing a revoked user to participate in the revocation process will lead to efficiency and security *** a result,designing a practical and efficient integrity verification scheme that supports this scenario is highly *** this paper,we identify this challenging problem as the asynchronous revocation,in which the revocation operations(i.e.,re-signing key generation and resigning process)and the user's revocation are *** the revocation operations must be able to be performed without the participation of the revo

关键词： Cloud storage Integrity verification Asynchronous revocation

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A Novel Cross-Media Layered Semantic Mining Model

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Wuhan University Journal of Natural Sciences 2008年第1期13卷 21-26页

作者： ZENG Cheng CAO Jiaheng peng zhiyong WANG Ke WANG Hui State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 Hubei China School of Computer Wuhan University Wuhan 430072 Hubei China

This paper presents a cross-media semantic mining model （CSMM） based on object semantic. This model obtains object-level semantic information in terms of maximum probability principle. Then semantic templates are trained and constructed with STTS （Semantic Template Training System）, which are taken as the bridge to realize the transition from various low-level media feature to object semantic. Furthermore, we put forward a kind of double layers metadata structure to efficaciously store and manage mined low-level feature and high-level semantic. This model has broad application in lots of domains such as intelligent retrieval engine, medical diagnoses, multimedia design and so on.

关键词： cross-media semantic mining model object semantic semantic template semantic template training system metadata

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Supporting Various Top-k Queries over Uncertain Datasets

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Wuhan University Journal of Natural Sciences 2014年第1期19卷 84-92页

作者： LI Wenfeng FU Zufa WANG Liwei LI Deyi peng zhiyong State Key Laboratory of Software Engineering Wuhan University School of Computer Wuhan University International School of Software Wuhan University Institute of Electronic System Engineering of China

There have been many researches and semantics in answering top-k queries on uncertain data in various applications. However, most of these semantics must consume much of their time in computing position probability. Our approach to support various top-k queries is based on position probability distribution （PPD） sharing. In this paper, a PPD-tree structure and several basic operations on it are proposed to support various top-k queries. In addition, we proposed an approximation method to improve the efficiency of PPD generation. We also verify the effectiveness and efficiency of our approach by both theoretical analysis and experiments.

关键词： top-k queries uncertain data position probability distribution

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