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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

A Novel Mathematical Model for similarity search in Pattern Matching Algorithms

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Journal of Computer and Communications 2020年第9期8卷 94-99页

作者： P. Vinod-Prasad Department of Technology Ministry of Higher Education Sur Oman

Modern applications require large databases to be searched for regions that are similar to a given pattern. The DNA sequence analysis, speech and text recognition, artificial intelligence, Internet of Things, and many other applications highly depend on pattern matching or similarity searches. In this paper, we discuss some of the string matching solutions developed in the past. Then, we present a novel mathematical model to search for a given pattern and it’s near approximates in the text.

关键词： String Matching Pattern Matching similarity search Substring search

LLE Based Pivot Selection for similarity search of Biological Data

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LLE Based Pivot Selection for Similarity Search of Biologica...

Malware Variant Detection Using similarity search over Content Fingerprint

2012 National Conference on Information Technology and Computer Science

作者： Kewei Ma,Honglong Xu,Pang Yue,Fuli Lei,Sheng Liu,Rui Mao Guangdong Key Laboratory of Popular High Performance Computers Shenzhen Key Laboratory of Service Computing and Applications.Shenzhen University Shenzhen,China Jiaxin Han Oracle Corporation Redwood City,CA,USA

Distance-based indexing is a widely used technique for general purpose *** selection is the most crucial step of bulkloading a metric-space indexing *** pivot selection methods are mainly based on linear methods.A non-linear method based on Locally Linear Embedding is *** results demonstrate that the performance of new method is superior to existing methods.

关键词： similarity search metric-space indexing pivot selection locally linear embedding dimensional reduction

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Malware Variant Detection Using Similarity Search over Conte...

Self-selective memristor-enabled in-memory search for highly efficient data mining

第26届中国控制与决策会议

作者： Ban Xiaofang Chen Li Hu Weihua Wu Qu China Information Technology Security Evaluation Center Tsinghua University

Detection of polymorphic malware variants plays an important role to improve information system security. Traditional static/dynamic analysis technologies have shown to be an effective characteristic that represents polymorphic malware instances. While these approaches demonstrate promise, they are themselves subject to a growing array of countermeasures that increase the cost of capturing these malware code features. Further, feature extraction requires a time investment per malware that does not scale well to the daily volume of malwares being reported by those who diligently collect malware. In this paper, we propose a similarity search of malware using novel distance（similarity） metrics of malware content fingerprint based on the locality-sensitive hashing（LSH） schemes. We describe a malware by the binary content of the malware contains;the next step is to compute an feature fingerprint for the malware binary image sample by using the SURF algorithm, and then do fast fingerprint matching with the LSH from malware code corpus to return the top most visually（structurally） similar variants. The LSH algorithm that captures malware similarity is based on image similarity. We implement B2M（Binary mapping to image） algorithm, the SURF algorithm and the LSH algorithm in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of response time and malware variant detection.

关键词： Malware Variant Detection Content Fingerprint Locality-sensitive Hashing similarity search

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InfoMat 2023年第5期5卷 121-133页

作者： Ling Yang Xiaodi Huang Yi Li Houji Zhou Yingjie Yu Han Bao Jiancong Li Shengguang Ren Feng Wang Lei Ye Yuhui He Jia Chen Guiyou Pu Xiang Li Xiangshui Miao School of Integrated Circuits Hubei Key Laboratory for Advanced MemoriesHuazhong University of Science and TechnologyWuhanthe People's Republic of China Hubei Yangtze Memory Laboratories Wuhanthe People's Republic of China InnoHK Centers AI Chip Center for Emerging Smart SystemsHong Kongthe People's Republic of China Huawei Technologies Co. Ltd.Shenzhenthe People's Republic of China

similarity search,that is,finding similar items in massive data,is a fundamental computing problem in many fields such as data mining and information ***,for large-scale and high-dimension data,it suffers from high computational complexity,requiring tremendous computation ***,based on the low-power self-selective memristors,for the first time,we propose an in-memory search(IMS)system with two innovative ***,by exploiting the natural distribution law of the devices resistance,a hardware locality sensitive hashing encoder has been designed to transform the realvalued vectors into more efficient binary ***,a compact memristive ternary content addressable memory is developed to calculate the Hamming distances between the binary codes in *** IMS system demonstrated a 168energy efficiency improvement over all-transistors counterparts in clustering and classification tasks,while achieving a software-comparable accuracy,thus providing a low-complexity and low-power solution for in-memory data mining applications.

关键词： in-memory search self-selective memristor similarity search ternary content addressable memory

CORE:Common Region Extension Based Multiple Protein Structure Alignment for Producing Multiple Solution

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Journal of Computer Science & Technology 2013年第4期28卷 647-656页

作者： Woo-Cheol Kim Sanghyun Park Jung-Im Won College of Information Sciences and Technology The Pennsylvania State University University Park Department of Computer Science Yonsei University Research Center of Information and Electronic Engineering Hallym University Chuncheon

Over the past several decades, biologists have conducted numerous studies examining both general and specific functions of proteins. Generally, if similarities in either the structure or sequence of amino acids exist for two proteins, then a common biological function is expected. Protein function is determined primarily based on the structure rather than the sequence of amino acids. The algorithm for protein structure alignment is an essential tool for the research. The quality of the algorithm depends on the quality of the similarity measure that is used, and the similarity measure is an objective function used to determine the best alignment because of their individual strength and weakness However, none of existing similarity measures became golden standard They require excessive filtering to find a single alignment. In this paper, we introduce a new strategy that finds not a single alignment, but multiple alignments with different lengths. This method has obvious benefits of high quality alignment. However, this novel method leads to a new problem that the running time for this method is considerably longer than that for methods that find only a single alignment. To address this problem~ we propose algorithms that can locate a common region （CORE） of multiple alignment candidates, and can then extend the CORE into multiple alignments. Because the CORE can be defined from a final alignment, we introduce CORE＊ that is similar to CORE and propose an algorithm to identify the CORE＊. By adopting CORE＊ and dynamic programming, our proposed method produces multiple alignments of various lengths with higher accuracy than previous methods. In the experiments, the alignments identified by our algorithm are longer than those obtained by TM-align by 17% and 15.48%, on average, when the comparison is conducted at the level of super-family and fold, respectively.

关键词： structure alignment similarity search protein structure

A Multi-dimensional Index Structure Based on Improved VA-file and CAN in the Cloud

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International Journal of Automation and computing 2014年第1期11卷 109-117页

作者： Chun-Ling Cheng Chun-Ju Sun Xiao-Long Xu Deng-Yin Zhang College of Computer Nanjing University of Posts and Telecommunications Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsMinistry of Education Jiangsu Province

Currently,the cloud computing systems use simple key-value data processing,which cannot support similarity search efectively due to lack of efcient index structures,and with the increase of dimensionality,the existing tree-like index structures could lead to the problem of"the curse of dimensionality".In this paper,a novel VF-CAN indexing scheme is ***-CAN integrates content addressable network(CAN)based routing protocol and the improved vector approximation fle(VA-fle) *** are two index levels in this scheme:global index and local *** local index VAK-fle is built for the data in each storage ***-fle is thek-means clustering result of VA-fle approximation vectors according to their degree of *** cluster forms a separate local index fle and each fle stores the approximate vectors that are contained in the *** vector of each cluster center is stored in the cluster center information fle of corresponding storage *** the global index,storage nodes are organized into an overlay network CAN,and in order to reduce the cost of calculation,only clustering information of local index is issued to the entire overlay network through the CAN *** experimental results show that VF-CAN reduces the index storage space and improves query performance efectively.

关键词： Cloud computing index similarity search clustering vector approximation fle(VA-fle) content addressable network(CAN)

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Chinese Journal of Electronics 2017年第1期26卷 22-26页

作者： GONG Xudong WANG Caimei XIONG Yan HUANG Wenchao School of Computer Science University of Science and Technology of China Department of Computer Science Hefei University

Similar time series searching plays an important role in applications such as time series classification and outlier detection. We observe that different segment of a time series may have different significance, thus propose to assign different weight to each segment, and extract those segments with highest weights for distance computation. Since these segments are more representative, we can achieve high accuracy of similarity search with much lower computation overhead. The result of experiments on both real world and synthetic data sets demonstrates that we can achieve comparable or even higher accuracy while largely reduce the computation overhead, if we use only those important segments rather than the whole time series while performing similarity search.

关键词： similarity search Time series Algorithm

Exploring the Pathways and Targets of Shexiang Baoxin Pill for Coronary Heart Disease through a Network Pharmacology Approach

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World Journal of Traditional Chinese Medicine 2018年第4期4卷 137-181页

作者： Shou-De Zhang Zhan-Hai Su Rui-Hui Liu Yan-Yan Diao Shi-Liang Li Ya-Ping-Hua Hong-Lin Li Wei-Dong Zhang State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXiningQinghai Department of Phytochemistry School of PharmacySecond Military Medical University Shanghai Key Laboratory of New Drug Design School of PharmacyEast China University of Science and TechnologyShanghaiChina Department of Clinical Science 2 Faculty of Medicine and DentistryUniversity of Bergen5009Norway

Objective: To investigate the network pharmacology of Shexiang Baoxin pill(SBP) and systematically analyze the mechanisms of ***: In this study, we excavated all the targets of 26 constituents of SBP which were identified in rat plasma though literature mining and target calculation(reverse docking and similarity search) and analyzed the multiple pharmacology actions of SBP comprehensively through a network pharmacology ***: In the end, a total of 330 Homo sapiens targets were identified for 26 blood constituents of ***, the pathway enrichment analysis found that these targets mapped into 171 KEGG pathways and 31 of which were more *** these identified pathways, 3 pathways were selected for analyzing the mechanisms of SBP for treating coronary heart ***: This study systematically illustrated the mechanisms of the SBP by analyzing the corresponding "drug-target-pathway-disease" interaction network.

关键词： Coronary heart disease network pharmacology reverse docking Shexiang Baoxin pill similarity search