To discover process models from event logs has recently aroused many researchers’ interest in the area of process mining. Notwithstanding the interest and related efforts, existing algorithms are far from being satisfactory. For example, some researchers have proved that α-algorithm is capable of discovering the processes of the so-called SWF-nets without short loops; however, α-algorithm has been found to contain some severe limitations. This paper is therefore to introduce the notation of S-Coverable workflow nets, to reach theorems about the characteristics of Sound S-Coverable Workflow Nets, and to develop a new process mining algorithm, namely, algorithm S. On such basis, suggested in the paper is a new approach to dealing with the problem of hidden transition discovering, an approach that, by means of the pretreatment of such hidden tasks, allows algorithm S to discover process models that will help preserve better structures. Theorems thus reached are applicable not only to process mining, but also to process modeling and process model checking.
{"title":"Process Mining: Algorithm for S-Coverable Workflow Nets","authors":"Jianchun She, Dongqing Yang","doi":"10.1109/WKDD.2009.158","DOIUrl":"https://doi.org/10.1109/WKDD.2009.158","url":null,"abstract":"To discover process models from event logs has recently aroused many researchers’ interest in the area of process mining. Notwithstanding the interest and related efforts, existing algorithms are far from being satisfactory. For example, some researchers have proved that α-algorithm is capable of discovering the processes of the so-called SWF-nets without short loops; however, α-algorithm has been found to contain some severe limitations. This paper is therefore to introduce the notation of S-Coverable workflow nets, to reach theorems about the characteristics of Sound S-Coverable Workflow Nets, and to develop a new process mining algorithm, namely, algorithm S. On such basis, suggested in the paper is a new approach to dealing with the problem of hidden transition discovering, an approach that, by means of the pretreatment of such hidden tasks, allows algorithm S to discover process models that will help preserve better structures. Theorems thus reached are applicable not only to process mining, but also to process modeling and process model checking.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121914248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the design of Viterbi Decoder of punctured convolutional codes, the SST method is used to reduce power consumption in this paper. Moreover, the punctured vector table is optimized by hard wire logic, thus reducing the area required by the system. Effective operation of adjustment is used to reduce the word length of path metric memory. At the same time, this algorithm can also help reduce operation load by controlling the highest order of path metric memory, thereby reducing the scale of hardware.
{"title":"An Efficient Viterbi Decoder for Digital Mobile Multimedia Broadcasting Receiver","authors":"Hongli Zhu, G. Gao, Gang Bi","doi":"10.1109/WKDD.2009.196","DOIUrl":"https://doi.org/10.1109/WKDD.2009.196","url":null,"abstract":"In the design of Viterbi Decoder of punctured convolutional codes, the SST method is used to reduce power consumption in this paper. Moreover, the punctured vector table is optimized by hard wire logic, thus reducing the area required by the system. Effective operation of adjustment is used to reduce the word length of path metric memory. At the same time, this algorithm can also help reduce operation load by controlling the highest order of path metric memory, thereby reducing the scale of hardware.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"31 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120900023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ontology mapping is a core task to achieve interoperability among the distributed and heterogeneous ontologies. The quality of ontology mapping is still not good due to the inconsideration of semantic information of the ontology. This paper proposes an ontology mapping method based on tree segmentation. It first divides the ontology into a set of sub-trees with different granularities according to the structure of the ontologies, then use Sub-tree Mapping Algorithm to map them. Preliminary experiments demonstrate that the proposed mapping method performs well in both precision and recall compared with the current mapping methods.
{"title":"Research on Tree Segmentation-based Ontology Mapping","authors":"Liansheng Li, Lihui Huang, Qinghua Guan, Dezhi Xu","doi":"10.1109/WKDD.2009.135","DOIUrl":"https://doi.org/10.1109/WKDD.2009.135","url":null,"abstract":"Ontology mapping is a core task to achieve interoperability among the distributed and heterogeneous ontologies. The quality of ontology mapping is still not good due to the inconsideration of semantic information of the ontology. This paper proposes an ontology mapping method based on tree segmentation. It first divides the ontology into a set of sub-trees with different granularities according to the structure of the ontologies, then use Sub-tree Mapping Algorithm to map them. Preliminary experiments demonstrate that the proposed mapping method performs well in both precision and recall compared with the current mapping methods.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122357817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we formulate image annotation as a semi-supervised learning problem under multi-instance learning framework. A novel graph based semi-supervised learning approach to image annotation using multiple instances is presented, which extends the conventional semi-supervised learning to multi-instance setting by introducing the adaptive geometric relationship between two bags of instances. The experiments over Corel images have shown that this approach outperforms other methods and is effective for image annotation.
{"title":"A Novel Region-based Image Annotation Using Multi-instance Learning","authors":"Xiaohong Hu, Xu Qian, Xinming Ma, Ziqiang Wang","doi":"10.1109/WKDD.2009.89","DOIUrl":"https://doi.org/10.1109/WKDD.2009.89","url":null,"abstract":"In this paper, we formulate image annotation as a semi-supervised learning problem under multi-instance learning framework. A novel graph based semi-supervised learning approach to image annotation using multiple instances is presented, which extends the conventional semi-supervised learning to multi-instance setting by introducing the adaptive geometric relationship between two bags of instances. The experiments over Corel images have shown that this approach outperforms other methods and is effective for image annotation.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129869892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Density-based clustering and density-based outlier detection have been extensively studied in the data mining. However, Existing works address density-based clustering or density-based outlier detection solely. But for many scenarios, it is more meaningful to unify density-based clustering and outlier detection when both the clustering and outlier detection results are needed simultaneously. In this paper, a novel algorithm named DBCOD that unifies density-based clustering and outlier detection is proposed. In order to discover density-based clusters and assign to each outlier a degree of being an outlier, a novel concept called neighborhood-based local density factor (NLDF) is employed. The experimental results on different shape, large-scale, and high-dimensional databases demonstrate the effectiveness and efficiency of our method.
{"title":"Unifying Density-Based Clustering and Outlier Detection","authors":"Yunxin Tao, D. Pi","doi":"10.1109/WKDD.2009.127","DOIUrl":"https://doi.org/10.1109/WKDD.2009.127","url":null,"abstract":"Density-based clustering and density-based outlier detection have been extensively studied in the data mining. However, Existing works address density-based clustering or density-based outlier detection solely. But for many scenarios, it is more meaningful to unify density-based clustering and outlier detection when both the clustering and outlier detection results are needed simultaneously. In this paper, a novel algorithm named DBCOD that unifies density-based clustering and outlier detection is proposed. In order to discover density-based clusters and assign to each outlier a degree of being an outlier, a novel concept called neighborhood-based local density factor (NLDF) is employed. The experimental results on different shape, large-scale, and high-dimensional databases demonstrate the effectiveness and efficiency of our method.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130249442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Privacy-preserving Data Mining aims at securely extracting knowledge from two or more parties' private data. Secure Multi-party Computation is the paramount approach to it. In this paper, we study Privacy-preserving Add and Multiply Exchanging Technology and present three new different approaches to Privacy-preserving Add to Multiply Protocol. After that, we analyze and compare the three different approaches about the communication overheads, the computation efforts and the security. In addition, we extend Privacy-preserving Add to Multiply Protocol to Privacy-preserving Adding to Scalar Product Protocol, which is more secure and more useful in the high security situations of Privacy-preserving Data Mining. Meantime, we present a solution for the new protocol.
{"title":"Three New Approaches to Privacy-preserving Add to Multiply Protocol and its Application","authors":"Youwen Zhu, Liusheng Huang, Wei Yang, Dong Li, Yonglong Luo, Fan Dong","doi":"10.1109/WKDD.2009.34","DOIUrl":"https://doi.org/10.1109/WKDD.2009.34","url":null,"abstract":"Privacy-preserving Data Mining aims at securely extracting knowledge from two or more parties' private data. Secure Multi-party Computation is the paramount approach to it. In this paper, we study Privacy-preserving Add and Multiply Exchanging Technology and present three new different approaches to Privacy-preserving Add to Multiply Protocol. After that, we analyze and compare the three different approaches about the communication overheads, the computation efforts and the security. In addition, we extend Privacy-preserving Add to Multiply Protocol to Privacy-preserving Adding to Scalar Product Protocol, which is more secure and more useful in the high security situations of Privacy-preserving Data Mining. Meantime, we present a solution for the new protocol.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128709781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Associative classification has high classification accuracy and strong flexibility. However, it still suffers from overfitting since the classification rules satisfied both minimum support and minimum confidence are returned as strong association rules back to the classifier. In this paper, we propose a new association classification method based on compactness of rules, it extends Apriori Algorithm¿which considers the interestingness, importance, overlapping relationships among rules. At last, experimental results shows that the algorithm has better classification accuracy in comparison with CBA and CMAR are highly comprehensible and scalable.
{"title":"Association Classification Based on Compactness of Rules","authors":"Q. Niu, Shixiong Xia, Lei Zhang","doi":"10.1109/WKDD.2009.160","DOIUrl":"https://doi.org/10.1109/WKDD.2009.160","url":null,"abstract":"Associative classification has high classification accuracy and strong flexibility. However, it still suffers from overfitting since the classification rules satisfied both minimum support and minimum confidence are returned as strong association rules back to the classifier. In this paper, we propose a new association classification method based on compactness of rules, it extends Apriori Algorithm¿which considers the interestingness, importance, overlapping relationships among rules. At last, experimental results shows that the algorithm has better classification accuracy in comparison with CBA and CMAR are highly comprehensible and scalable.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127224600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
According to the different branches of city’s intersections and the traffic flow at different times, the program of intelligent traffic light controller based on VHDL is given and simulated by Quartus¿ by using hierarchical design thought. The simulation results show that the intelligent traffic light controller can realize the transition of 2-phase, 3-phase and 4-phase based on actual situations. The adaptability and applicability of the system can be strengthened by changing the phase.
{"title":"Design of Intelligent Traffic Light Controller Based on VHDL","authors":"Shuo Shi, H. Tian, Yandong Zhai","doi":"10.1109/WKDD.2009.19","DOIUrl":"https://doi.org/10.1109/WKDD.2009.19","url":null,"abstract":"According to the different branches of city’s intersections and the traffic flow at different times, the program of intelligent traffic light controller based on VHDL is given and simulated by Quartus¿ by using hierarchical design thought. The simulation results show that the intelligent traffic light controller can realize the transition of 2-phase, 3-phase and 4-phase based on actual situations. The adaptability and applicability of the system can be strengthened by changing the phase.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper discusses the concepts of data warehouse technology and its importance for decision support system (DSS). The DSS as one kind smart software system of the important application value, provides, each kind of decision information as well as the commercial question solution for the enterprise. Thus Data warehouse can meet the requirements of the database management subsystems of DSS, and is fitted to form its technology frame. Then we put forth the structure of data warehouse and its main functional components. Along with widespread application of the data warehouse, DSS based on data warehouse arises at the historic moment. Begin with actual demand of the DSS, characteristic and the structure of the data warehouse have been analyzed. DSS based on the data warehouse technology is elaborated, and finally give the application example.
{"title":"Research of Decision Support System Based on Data Warehouse Techniques","authors":"Q. Han, Xiaoyan Gao","doi":"10.1109/WKDD.2009.96","DOIUrl":"https://doi.org/10.1109/WKDD.2009.96","url":null,"abstract":"This paper discusses the concepts of data warehouse technology and its importance for decision support system (DSS). The DSS as one kind smart software system of the important application value, provides, each kind of decision information as well as the commercial question solution for the enterprise. Thus Data warehouse can meet the requirements of the database management subsystems of DSS, and is fitted to form its technology frame. Then we put forth the structure of data warehouse and its main functional components. Along with widespread application of the data warehouse, DSS based on data warehouse arises at the historic moment. Begin with actual demand of the DSS, characteristic and the structure of the data warehouse have been analyzed. DSS based on the data warehouse technology is elaborated, and finally give the application example.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126033679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.
{"title":"Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application","authors":"Y. Wan, Yangu Zhang","doi":"10.1109/WKDD.2009.169","DOIUrl":"https://doi.org/10.1109/WKDD.2009.169","url":null,"abstract":"The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126215982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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