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An algorithm on generating lattice based on layered concept lattice

Telkomnika - Indonesian Journal of Electrical engineering 2013年第8期11卷 4477-4483页

作者： Chang-Sheng, Zhang Jing, Ruan Hai-Long, Huang long-Chang, Li Bing-Ru, Yang School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083 China College of Physics and Electronic Information Engineering Wenzhou University Zhejiang 325035 China Wenzhou Vocational and Technical College Zhejiang 325035 China

Concept lattice is an effective tool for data analysis and rule extraction, a bottleneck factor on impacting the applications of concept lattice is how to generate lattice efficiently. In this paper, an algorithm LCLG on generating lattice in batch processing based on layered concept lattice is developed, this algorithm is based on layered concept lattice, the lattice is generated downward layer by layer through concept nodes and provisional nodes in current layer;the concept nodes are found parent-child relationships upward layer by layer, then the Hasse diagram of inter-layer connection is generated;in the generated process of the lattice nodes in each layer, we do the pruning operations dynamically according to relevant properties, and delete some unnecessary nodes, such that the generating speed is improved greatly;the experimental results demonstrate that the proposed algorithm has good performance. © 2013 Universitas Ahmad Dahlan.

关键词： information analysis

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Frequent itemsets mining based on concept lattice and sliding window

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Telkomnika - Indonesian Journal of Electrical engineering 2013年第8期11卷 4780-4787页

In this paper, a frequent itemsets mining algorithm of data stream based on concept lattice and sliding window is presented. This algorithm mines frequent concepts for new inflowing basic window in batches in a sliding window and generates concept lattice Hasse diagram. With introduction into small support degree? and error factor? to do the pruning operations for non-frequent concept node, each connection point in the Hasse diagram contains the information of frequent itemsets and support degree. As the generation of Hasse diagram in the new basic windows, we integrate concept lattice vertically with the generated Hasse diagram and sliding window, and ultimately output all frequent itemsets through scanning all the graph nodes of Hasse diagram graph. The experimental results show that the proposed algorithm has a good performance. © 2013 Universitas Ahmad Dahlan.

关键词： Graphic methods

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An approach for personalized tag recommendation based on interest transfer model

An approach for personalized tag recommendation based on int...

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9th Web information Systems and Applications Conference, WISA 2012

作者： Liu, Yue Yang, Nan Yang, Gang School of Information Renmin University of China Bejing China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Bejing China

ISBN: (纸本)9781467330541

Recently, social tagging systems become more and more popular in many Web 2.0 applications. In such systems, Users are allowed to annotate a particular resource with a freely chosen a set of tags. These user-generated tags can represent users' interests more concise and closer to human understanding. Interests will change over time. Thus, how to describe users' interests and interests transfer path become a big challenge for personalized recommendation systems. In this approach, we propose a variable-length time interval division algorithm and user interest model based on time interval. Then, in order to draw users' interests transfer path over a specific time period, we suggest interest transfer model. After that, we apply a classical community partition algorithm in our approach to separate users into communities. Finally, we raise a novel method to measure users' similarities based on interest transfer model and provide personalized tag recommendation according to similar users' interests in their next time intervals. Experimental results demonstrate the higher precision and recall with our approach than classical user-based collaborative filtering methods. © 2012 IEEE.

关键词： Collaborative filtering

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Thermal Stability, Microstructure and Photocatalytic Activity of the Bismuth Oxybromide Photocatalyst

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Chinese Journal of Chemistry 2012年第3期30卷 721-726页

作者：余长林周晚琴余济美操芳芳李鑫 School of Metallurgy and Chemical Engineering Jiangxi University of Science and TechnologyGanzhouJiangxi 341000China School of Information Engineering Jiangxi University of Science and TechnologyGanzhouJiangxi 341000China Department of Chemistry The Center of Novel Functional Molecules and Environmental Science ProgrammeThe Chinese University of Hong KongShatinNew TerritoriesHong KongChina Fujian Provincial Key Laboratory of Photocatalysis-State Key Laboratory Breeding Base Fuzhou UniversityFuzhouFujian 350002China

Flake BiOBr was first prepared by a solution method at room temperature. Then, the produced BiOBr was calcined at different temperatures. It was found that BiOBr is not a stable compound. It transforms to plate-like Bi24031Brll at around 750 ℃ and the formed Bi24O31Br11 can further convert to rod-like a-Bi203 at around 850℃. The prepared compounds were characterized with X-ray diffraction （XRD）, N2 physical adsorption, scanning electron microscopy （SEM）, and UV-Vis diffuse reflectance spectra （DRS）, respectively. The photocatalytic activity of the produced bismuth oxybromides was evaluated by photocatalytic decomposition of acid orange Ⅱ under both visible light （λ〉420 nm） and UV light （λ=365 nm） irradiation. Results show that these compounds have different band gaps and different photocatalytic properties. The band gap energies of the as-prepared samples were found to be 2.82, 2.79, 2.60 and 3.15 eV for BiOBr, BiOBr/Bi24O31Br, Bi24O31Br, and a-Bi2O3, respectively. Under both UV light and visible light irradiation, the photocatalytic activity follows the order： BiOBr/Bi24O31Br mixture 〉 BiOBr 〉 Bi24031Br〉a-Bi2O3. The change in photocatalytic activity could be attributed to the different light absorption ability and microstructures of the photocatalysts.

关键词： transition states bismuth oxybromide photocatalytic activity acid orange II structure-activity rela-tionships

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FindCredPg: A novel method to find credible pages based on trust web graph

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14th Asia Pacific Web technology Conference, APWeb 2012

作者： Wang, Teng Zhu, Qing Wang, Shan Liang, Jingfan Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Information Renmin University of China Beijing China

ISBN: (纸本)9783642292521

Finding credible pages is a challenging problem on the Web. Our key observation in this paper is that credible pages usually link to credible content-related pages, which is different from a normal page usually links to normal pages in spam page detection. We propose a novel method to find credible pages based on the trust web graph we define. This method first measures the content correlation between pages connected by hyperlinks, then it combines web link structure with content correlation value of pages to build a trust web graph. At last, credible pages are found successfully by using trust relation of vertices on the trust web graph. We construct a real-world data set by crawling millions of pages on the web and run a set of experiments on this data set. Experiment results show that the accuracy of this method is near 80% and the efficiency is higher. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Hypertext systems

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Summarizing large-scale database schema using community detection

Summarizing large-scale database schema using community dete...

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作者： Wang, Xue Zhou, Xuan Wang, Shan School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China

Schema summarization on large-scale databases is a challenge. In a typical large database schema, a great proportion of the tables are closely connected through a few high degree tables. It is thus dificult to separate these tables into clusters that represent different topics. Moreover, as a schema can be very big, the schema summary needs to be structured into multiple levels, to further improve the usability. In this paper, we introduce a new schema summarization approach utilizing the techniques of community detection in social networks. Our approach contains three steps. First, we use a community detection algorithm to divide a database schema into subject groups, each representing a specific subject. Second, we cluster the subject groups into abstract domains to form a multi-level navigation structure. Third, we discover representative tables in each cluster to label the schema summary. We evaluate our approach on Freebase, a real world large-scale database. The results show that our approach can identify subject groups precisely. The generated abstract schema layers are very helpful for users to explore database. © 2012 Springer Science+Business Media, LLC & Science Press, China.

关键词： database systems

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A typology of online window shopping consumers 16

A typology of online window shopping consumers

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16th Pacific Asia Conference on information Systems, PACIS 2012

作者： Liu, Fang Wang, Rong Zhang, Ping Zuo, Meiyun School of Information Renmin University of China Beijing China School of Information Studies Syracuse University SyracuseNY United States School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Beijing China

Consumer online shopping behaviors are well attended in the IS and marketing literature. Yet, there is another group of individuals who spend a lot of time online but do not purchase anything. This online window shopping phenomenon is intriguing to both scholars and marketers yet it is less studied and little understood. Questions such as what the online window shopping consumers do during their visits, how to differentiate their activities and how to design marketing strategies to stimulate them to buy are all essential and beg for investigation. To address this gap, we propose a typology of online window shopping consumers based on the Consumer information Processing Model, then empirically validate and refine the typology using a set of clickstream data. The final typology contains four main types of online window shopper consumers: 1) promotion finders, 2) social & hedonic experience seekers, 3) information gatherers, and 4) learners & novices. This study extends consumer online behavior research in both e-commerce and social commerce by focusing on the specific group of consumers who only do online window shopping. Besides theoretical contributions, the findings also provide marketers and businesses with valuable references for designing targeted marketing strategies or promotional activities for online window shopping consumers.

关键词： Consumer behavior

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Efficient SPARQL query processing in mapreduce through data partitioning and indexing

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14th Asia Pacific Web technology Conference, APWeb 2012

作者： Nie, Zhi Du, Fang Chen, Yueguo Du, Xiaoyong Xu, Linhao Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China IBM Research China Beijing China

ISBN: (纸本)9783642292521

Processing SPARQL queries on single node is obviously not scalable, considering the rapid growth of RDF knowledge bases. This calls for scalable solutions of SPARQL query processing over Web-scale RDF data. There have been attempts for applying SPARQL query processing techniques in MapReduce environments. However, no study has been conducted on finding optimal partitioning and indexing schemes for distributing RDF data in MapReduce. In this paper, we investigate RDF data partitioning technique that provides effective indexing schemes to support efficient SPARQL query processing in MapReduce. Our extensive experiments over a huge real-life RDF dataset show the performance of the proposed partitioning and indexing schemes for efficient SPARQL query processing. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： MapReduce

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Improve top-K recommendation by extending review analysis

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14th Asia Pacific Web technology Conference, APWeb 2012

作者： Zhu, Qing Xing, Zhe Liang, Jingfan School of Information Renmin University of China Beijing 100872 China Key Laboratory for Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642292521

The Web has become the popular place for people to purchase product and acquire services, so collaborative filtering is one of the most important algorithms applied in e-commerce recommendation systems. Unfortunately, it is widely recognized that the traditional recommendation methods are inefficient when the user rating data is extremely sparse. In order to overcome the limitations, good recommendation tools are needed to help Web customers determine the products and satisfaction services. In this paper, we propose a multi-dimensional adaptive recommendation algorithm by extending opinion analysis to improve top-k recommendation. In the first step, the novel algorithm that uses extened opinion analysis, creatively combines three dimensional recommendation models: user-based, item-based and opinion-based collaborative filtering. It successfully integrates opinion mining technology with collaborative filtering algorithm. In the second step, we configured the dynamic measurement would help us determine the weight of three dimensions: user-based, item-based and opinion-based analysis, and hence get the final prediction result. The experimental results show that multi-dimensional recommendation can effectively alleviate the dataset sparsity problem and achieve better prediction accuracy compared to other traditional collaborative recommendation algorithms. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Collaborative filtering

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Journal of Convergence information technology 2012年第16期7卷 87-96页

作者： Minjuan, Zhong School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 China

With the increasing of XML data over the Internet, managing and analyzing huge amount of XML documents has played an important role for information management. Clustering as an intelligent technique has been utilized as an excellent way of grouping the documents by their content or structure. However, the key problem is how to measure similarity between XML documents. In this paper, we propose an extended vector space model and on this basis put forward an effective semantic similarity measurement method combining content and structure semantics, in which a variety of XML document features impacting similarity measurement, such as term element frequency, term inverse element frequency, semantic weight of tag and level information of the term, are analyzed. In addition, information gain, for clustering quality evaluation are introduced motivated by the fact that collection has no classification information in advance. Experiment results show that proposed similarity method (EVSM_SS) outperforms the content and structure integration measurement based on structure path (VSM_SP) as well as traditional document clustering measurement (CO) in information gain and produce better clustering quality.

关键词： XML

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