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2018 2nd International Conference on Artificial Intelligence: Technologies and Applications（ICAITA2018）

作者： Shaozhi Dai Yanchun Liang Shuyan Liu Ying Wang Wenle Shao Xixun Lin Xiaoyue Feng Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University

With the growth of existing knowledge graph, the completion of knowledge graph has become a crucial problem. In this paper, we propose a novel model based on descriptionembodied knowledge representation learning framework, which is able to take advantages of both fact triples and entity description. Specifically, the relation projection is combined with description-embodied representation learning to learn entity and relation embeddings. Convolutional neural network and Trans R are adopted to get the description-based and structure-based representation of entity and relation, respectively. We employ FB15 K dataset generated from a large knowledge graph freebase, to evaluate the performances of the proposed model. Experimental results show that our proposed model greatly outperforms other existing baseline models.

关键词： knowledge graph completion entity description natural language processing

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A Task Allocation Method for Stream Processing with Recovery Latency Constraint

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Journal of Computer Science & Technology 2018年第6期33卷 1125-1139页

作者： Hong-Liang Li Jie Wu Zhen Jiang Xiang Li Xiao-Hui Wei College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer and Information Sciences Temple University Philadelphia PA 19122 U.S.A. Department of Computer Science West Chester University of Pennsylvania West Chester PA 19383 U.S.A.

Stream processing applications continuously process large amounts of online streaming data in real time or nearreal time. They have strict latency constraints. However, the continuous processing makes them vulnerable to any failures,and the recoveries may slow down the entire processing pipeline and break latency constraints. The upstream backupscheme is one of the most widely applied fault-tolerant schemes for stream processing systems. It introduces complexbackup dependencies to tasks, which increases the difficulty of controlling recovery latencies. Moreover, when dependenttasks are located on the same processor, they fail at the same time in processor-level failures, bringing extra recovery latencies that increase the impacts of failures. This paper studies the relationship between the task allocation and therecovery latency of a stream processing application. We present a correlated failure effect model to describe the recoverylatency of a stream topology in processor-level failures under a task allocation plan. We introduce a recovery-latency awaretask allocation problem （RTAP） that seeks task allocation plans for stream topologies that will achieve guaranteed recoverylatencies. We discuss the difference between RTAP and classic task allocation problems and present a heuristic algorithmwith a computational complexity of O（n log2 n） to solve the problem. Extensive experiments were conducted to verify thecorrectness and effectiveness of our approach. It improves the resource usage by 15%-20% on average.

关键词： stream processing task allocation fault-tolerance upstream backup, recovery latency

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Efficient zonal diagnosis with maximum satisfiability

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Science China(Information Sciences) 2018年第11期61卷 17-30页

作者： Meng LIU Dantong OUYANG Shaowei CAI Liming ZHANG College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of EducationJilin University State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences

Model-based diagnosis(MBD) has been widely acknowledged as an effective diagnosis ***, for large scale circuits, it is difficult to find all cardinality-minimal diagnoses within a reasonable time. This paper proposes a novel method that takes a significant step in this direction. The idea is to divide a circuit into zones and compute the cardinality-minimal diagnoses by finding subset-minimal diagnoses with cardinality-minimal via a maximum satisfiability(MaxSAT) solver on an abstracted circuit that is composed of these zones instead of all components. We also propose a new propagate-extend method for extending the seed-TLDs to obtain all cardinality-minimal diagnoses efficiently. We implement our method with a state-of-the-art core-guided MaxSAT solver, and present evidence that it significantly improves the diagnosis efficiency on ISCAS-85 circuits. Our method outperforms SATbD, which was recently shown to outperform most complete MBD approaches using satisfiability(SAT).

关键词： model-based diagnosis MaxS AT subset-minimal diagnoses cardinality-minimal diagnoses zone propagate-extend

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Explanation Chains Model Based on the Fine-Grained Data 8th

Explanation Chains Model Based on the Fine-Grained Data

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8th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2019

作者： Ma, Fu-Yuan Chen, Wen-Qi Xiao, Min-Hao Wang, Xin Wang, Ying College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun130012 China Changchun Institute of Technology Changchun130012 China College of Software Jilin University Changchun130012 China

ISBN: (纸本)9783030322359

With the development of information society, Recommendation System has been an import tool to help users filter information and create more economic value for enterprises. However, it is difficult for traditional recommendation systems to interpret recommendation results. In order to improve users’ trust in recommendation results, interpretable recommendation models have attracted more and more attention. In this paper, we present the Explanation Chains Model based on the Fine-grained Data (F-ECM) to enhance the effectiveness of recommendation while achieving the interpretability of recommendation. First, we generate parsing trees from user comments and extract three key sentence structure information (i.e., aspects, features and sentiment tendency) from those generated parsing tree. The fine-grained similarity is computed based on the aspects and features of the products to be recommended, and users’ product satisfaction is predicted by combining sentiment tendency. Then the recommendation chain will be constructed according to the satisfaction degree in the recommendation list. Finally, we calculate recommendation chain scores of all the items to be recommended to the target user, generate the recommendation results and personal explanation for the user by the recommendation chains. Experiments in the Amazon data set show that the Explanation Chains Model based on the Fine-grained Data achieve better interpretability and performance of product recommendation systems. © 2019, Springer Nature Switzerland AG.

关键词： Recommender systems

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Ordered proposition fusion based on consistency and uncertainty measurements

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Science China(Information Sciences) 2017年第8期60卷 117-135页

作者： Dayou LIU Yungang ZHU Ni NI Jie LIU College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Beijing Entry-Exit Inspection and Quarantine Bureau

The fusion of ordered propositions is an important and widespread problem in artificial intelligence,but existing fusion methods have difficulty handling the fusion of ordered propositions. In this paper, we propose a solution based on consistency and uncertainty measurements. The main contributions of this paper are as follows. First, we propose the concept of convexity degree, mean, and center of basic support function to comprehensively describe the basic support function of ordered propositions. Second, we introduce entropy as a measure of uncertainty in the basic support function of ordered propositions. Third, we generalize the indeterminacy of the basic support function and propose a novel method to measure the consistency between two basic support functions. Finally, based on the above researches, we propose a novel algorithm for fusing ordered propositions. Theoretical analysis and experimental results demonstrate that the proposed method outperforms state-of-the-art methods.

关键词： uncertainty processing ordered proposition evidence theory dempster rule of combination information fusion

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Web-based Teamwork: Distributed Software Development Course under Covid-19

Web-based Teamwork: Distributed Software Development Course ...

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International Conference on Computer Science & Education (ICCSE)

作者： Rui ZHANG Pedro Mestre Carlos Serodio Marília Prada Wenjuan GAO College of Computer Science and Technology Jilin University Key Lab of Symbolic Computation and Knowledge Engineering Chinese Ministry of Education Changchun China Centro Algoritmi University of Minho Guimaraes Portugal CITAB University of Tras-os-Montes and Alto Douro Vila Real Portugal Department of Social and Organizational Psychology Instituto Universitário de Lisboa (ISCTE-IUL) Lisboa Portugal Library of Changchun University Changchun China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

In a increasingly globalized world, it is very important to help students to acquire the hard and soft skills needed to cope with the challenges they will face when working in such environments. However, even though students find this subject interesting and volunteer for it, it is hard, even impossible to teach college students such a distributed fashion of teamwork. In this paper, a case study is provided to illustrate the methodology and experiences of a joint course, distributed software development, of multiple universities from Asia, Europe, North and South Americas. The results show that student can get the spirit, effective communication for such web-based teamwork environment and achieve software project development. The recent developments because of the Covid-19 pandemic are the facts that now students have to cooperate remotely with each other not only across continents but also inside their own city or country. It has increased the awareness of the need for this kind of training and effectively improved the interactions between team elements in different countries and improved the students' feeling of belonging to their team.

关键词： Software Software engineering Games Faces Teamwork Electronic mail Tools

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Automatic localization of macular area based on structure label transfer

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International Journal of Ophthalmology(English edition) 2018年第3期11卷 422-428页

作者： Xiao-Xin Guo Qun Li Chao Sun Yi-Nan LU Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun130012 Jilin Province China College of Computer Science and Technology Jilin University Changchun 130012 Jilin Province China

AIM： To explore feasibility and practicability of macula localization independent of macular morphological features. METHODS： A novel method was proposed to identify macula in fundus images by using structure label transfer. Its main idea was to match a processed image with the candidate images with known structures, and then transfer the structure label representing the macular to the processed image as a result of macula localization. In this way, macula localization couldn＇t be influenced by lesion or other interference any more. RESULTS： The average success rate in four datasets was 98.18%. For accuracy, the average error distance in four datasets was 0.151 optic disc diameter （ODD）. Even for severe lesion images, the proposed method can still maintain high success rate and high accuracy, e.g., 95.65% and 0.124 ODD in the case of STARE dataset, respectively, which indicated that the proposed method was highly robust and stable in the complicated situations. CONCLUSION： The proposed method can avoid the interference of lesion to macular morphological features in macula localization, and can locate macula with high accuracy and robustness, verifying its feasibility.

关键词： fundus image optic disc macula structurelabel transfer

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An improved fruit fly optimization algorithm for solving traveling salesman problem

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Frontiers of Information Technology & Electronic engineering 2017年第10期18卷 1525-1533页

作者： Lan HUANG Gui-chao WANG Tian BAI Zhe WANG College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering (Jilin University) Ministry of Education Changchun 130012 China

The traveling salesman problem(TSP), a typical non-deterministic polynomial(NP) hard problem, has been used in many engineering applications. As a new swarm-intelligence optimization algorithm, the fruit fly optimization algorithm(FOA) is used to solve TSP, since it has the advantages of being easy to understand and having a simple implementation. However, it has problems, including a slow convergence rate for the algorithm, easily falling into the local optimum, and an insufficient optimization precision. To address TSP effectively, three improvements are proposed in this paper to improve FOA. First, the vision search process is reinforced in the foraging behavior of fruit flies to improve the convergence rate of FOA. Second, an elimination mechanism is added to FOA to increase the diversity. Third, a reverse operator and a multiplication operator are proposed. They are performed on the solution sequence in the fruit fly's smell search and vision search processes, respectively. In the experiment, 10 benchmarks selected from TSPLIB are tested. The results show that the improved FOA outperforms other alternatives in terms of the convergence rate and precision.

关键词： Traveling salesman problem Fruit fly optimization algorithm Elimination mechanism Vision search Operator

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Topology-Aware Task Allocation for Distributed Stream Processing with Latency Guarantee

Topology-Aware Task Allocation for Distributed Stream Proces...

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作者： Xiaohui Wei Xun Wei Hongliang Li Yuan Zhuang Hengshan Yue College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education

Nowadays it becomes more and more critical to process the increasingly large amounts of data in timely *** order to meet this requirement and ensure the reliable processing of streaming data,a variety of distributed stream processing architectures and platforms have been developed,which handles the fundamental task of allocating processing tasks to the currently available physical resources and routing streaming data between these ***,many stream processing systems lack an intelligent scheduling mechanism,in which their default schedulers allocate tasks without taking resource demands and availability,or the transfer latency between resources into *** stream processing has a strict request for *** it's important to give latency guarantee for distributed stream *** this paper,we propose a new algorithm for stream processing with latency guarantee,the algorithm both consider transfer latency and resource demand in the process of task *** experiments verify the correctness and effectiveness of our *** the condition of satisfying the latency constraints,the heuristic algorithm AHA on average,reduce more than 21.3% and 58.9% resources compared with the greedy and the round-robin algorithms.

关键词： Distributed stream processing Task allocation Transfer latency

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RiWalk: Fast Structural Node Embedding via Role Identification

RiWalk: Fast Structural Node Embedding via Role Identificati...

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IEEE International Conference on Data Mining (ICDM)

作者： Xuewei Ma Geng Qin Zhiyang Qiu Mingxin Zheng Zhe Wang College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

Nodes performing different functions in a network have different roles, and these roles can be gleaned from the structure of the network. Learning latent representations for the roles of nodes helps to understand the network and to transfer knowledge across networks. However, most existing structural embedding approaches suffer from high computation and space cost or rely on heuristic feature engineering. Here we propose RiWalk, a flexible paradigm for learning structural node representations as it decouples the structural embedding problem into a role identification procedure and a network embedding procedure. Through role identification, rooted kernels with structural dependencies kept are built to better integrate network embedding methods. To demonstrate the effectiveness of RiWalk, we develop two different role identification methods named RiWalk-SP and RiWalk-WL respectively and employ random walk based network embedding methods. Experiments on within-network classification tasks show that our proposed algorithms achieve comparable performance with other baselines while being an order of magnitude more efficient. Besides, we also conduct across-network role classification tasks. The results show potential of structural embeddings in transfer learning. RiWalk is also scalable, making it capable of capturing structural roles in massive networks.

关键词： Kernel Task analysis knowledge engineering Machine learning Bridges Proteins Network topology

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