Xiangfeng Luo

Shanghai University, Shanghai, Shanghai Shi, China

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Publications (49)4.51 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: Association Link Network (ALN) is a kind of Semantic Link Network built by mining the association relations among multimedia Web resources for effectively supporting Web intelligent application such as Web-based learning, and semantic search. This paper explores the Small-World properties of ALN to provide theoretical support for association learning (i.e., a simple idea of “learning from Web resources”). First, a filtering algorithm of ALN is proposed to generate the filtered status of ALN, aiming to observe the Small-World properties of ALN at given network size and filtering parameter. Comparison of the Small-World properties between ALN and random graph shows that ALN reveals prominent Small-World characteristic. Then, we investigate the evolution of Small-World properties over time at several incremental network sizes. The average path length of ALN scales with the network size, while clustering coefficient of ALN is independent of the network size. And we find that ALN has smaller average path length and higher clustering coefficient than WWW at the same network size and network average degree. After that, based on the Small-World characteristic of ALN, we present an Association Learning Model (ALM), which can efficiently provide association learning of Web resources in breadth or depth for learners.
    World Wide Web 03/2014; · 1.20 Impact Factor
  • Feiyue Ye, Feng Zhang, Xiangfeng Luo, Lingyu Xu
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    ABSTRACT: As a free online encyclopedia with a large-scale of knowledge coverage, rich semantic information and quick update speed, Wikipedia brings new ideas to measure semantic correlation. In this paper, we present a new method for measuring the semantic correlation between words by mining rich semantic information that exists in Wikipedia. Unlike the previous methods that calculate semantic relatedness merely based on the page network or the category network, our method not only takes into account the semantic information of the page network, also combines the semantic information of the category network, and it improve the accuracy of the results. Besides, we analyze and evaluate the algorithm by comparing the calculation results with famous knowledge base (e.g., Hownet) and traditional methods based on Wikipedia on the same test set, and prove its superiority.
    Computer and Information Science (ICIS), 2013 IEEE/ACIS 12th International Conference on; 01/2013
  • Feiyue Ye, Haibo Tang, Xiangfeng Luo
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    ABSTRACT: Repeated pattern is a common phenomenon in query result pages of deep web sites. The deep web back-end data can be accessed by mining repeated patterns. So far, most of the algorithms of discovering repeated pattern use traditional web information extraction methods. But the recall percentage and accuracy are not high. How to obtain the repeated pattern accurately and completely is still a difficulty. We propose a method based on the largest block strategy to discover such pattern. The core of the method is using the largest block strategy to discover the repeated pattern layer. We can quickly navigate to the region of the entity data, and then analyze the sub tree in this area, finally, get the simplified repeated pattern of the deep web site. According to the results of the experiment, this method can get the repeated pattern data more accurately and more completely than the traditional methods. It can also address the multi-pattern problem which has not been solved yet in other methods.
    Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on; 01/2012
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    ABSTRACT: Using thirteen satellites sea surface temperature (SST) from infrared radiometers (AVHRR, MODIS) and microwave radiometers (TMI, AMSR), a set of high-quality, cloud-free, high-resolution(0.25°) merged SST product was generated through a method of extended revisal point. The area of merged SST product and extended revisal point product [15.875-40.125°N, 105.875-130.125°E] cover the whole China Sea. The experimental results show that the number of extension correct point will be hundreds of thousands times as many as in-situ SST data. It only has a small deviation by comparison with in-situ SST data, and the precision between the two is similar. Therefore, extension correct point can replace in-situ data under certain conditions. This study will offer a wider SST reference corrections data for quality evaluation, multi-source remote sensing, and assimilation technology.
    Cloud and Green Computing (CGC), 2012 Second International Conference on; 01/2012
  • Feiyue Ye, Hongxin Cao, Xiangfeng Luo
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    ABSTRACT: This paper introduces the concept algebra (CA) theory as a basis for the conceptual representation and the derivation of text processing to realize a semantic based retrieval system. We also take advantage of Hownet to create the concept attributes space for concept algebra. With the help of LTP, we get the key words and their dependent relations of every sentence to build the CA concept representation of the content with a five-tuple. Concepts make it possible to express both the keyword itself and the semantic relation with its context. According to the demands of text retrieval, some CA operations are optimized to calculate the relations and similarity between concepts. Besides, a text retrieval system framework which processes information based on the concept relations at a concept level is also proposed to verify the advantages of our method.
    Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on; 01/2012
  • Xiangfeng Luo, Zheng Xu, Jie Yu, Xue Chen
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    ABSTRACT: Association Link Network (ALN) aims to establish associated relations among various resources. By extending the hyperlink network World Wide Web to an association-rich network, ALN is able to effectively support Web intelligence activities such as Web browsing, Web knowledge discovery, and publishing, etc. Since existing methods for building semantic link on Web resources cannot effectively and automatically organize loose Web resources, effective Web intelligence activities are still challenging. In this paper, a discovery algorithm of associated resources is first proposed to build original ALN for organizing loose Web resources. Second, three schemas for constructing kernel ALN and connection-rich ALN (C-ALN) are developed gradually to optimize the organizing of Web resources. After that, properties of different types of ALN are discussed, which show that C-ALN has good performances to support Web intelligence activities. Moreover, an evaluation method is presented to verify the correctness of C-ALN for semantic link on documents. Finally, an application using C-ALN to organize Web services is presented, which shows that C-ALN is an effective and efficient tool for building semantic link on the resources of Web services.
    IEEE Transactions on Automation Science and Engineering 08/2011; · 1.67 Impact Factor
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    ABSTRACT: With the increase of information scale of web events on the time, it is extremely difficult and challenging to grasp the semantics of web events artificially, because of the limitation of the time and energy of human beings. Herein, we propose a method to map the web event to keyword level association link network (KALN) for deep analysis of the semantics of web events, such as the evolution semantics of web events. Firstly, the original KALN is constructed at a given time by traditional data mining technologies. Then, the hierarchical KALN, consisted of Theme Layer Network, Backbone Layer Network and Tidbit Layer Network, is built based on the original KALN by information entropy to identify the different semantic levels of the web event, including stable semantics, sub-stable semantics and unstable semantics. With the semantic analysis of hierarchical KALN, human could easily gain a thorough understanding of the web event. Finally, experiments show that our method can effectively capture the different level semantics of web events.
    IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing, DASC 2011, 12-14 December 2011, Sydney, Australia; 01/2011
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    ABSTRACT: Web search is a key information retrieval method for human beings in current society, both in the fields of academic and commercial activities. Due to "one-size-fits-all" approach limit to search results obtainment, there are still challenges to give personalized web service with high precision in traditional web search process. Herein, a new framework is proposed to advance traditional search process into a new paradigm, i.e. interactive search. First, a cognitive model of interaction process about one search step is developed by the imitation of human search behaviors. Then based on the theory of interactive computing, an interactive search model is introduced to formalize successive search sessions which include several search steps. Third, based on human's cognitive mechanism such as the spreading activation model and user memory theory, a user model is designed to capture user's search activities which can aid the interactive search process effectively. Last, by the help of Associated Link Network, an information gradient based rank algorithm is proposed aiming at maximizing the quantity of web information supply. The efficiency of our proposed interactive search service is verified by the experimental results.
    IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing, DASC 2011, 12-14 December 2011, Sydney, Australia; 01/2011
  • Xiangfeng Luo, Zheng Xu, Jie Yu, Xue Chen
    IEEE T. Automation Science and Engineering. 01/2011; 8:482-494.
  • Jun Zhang, Xiangfeng Luo, Xiang He, Chuanliang Cai
    IJCINI. 01/2011; 5:80-96.
  • Zheng Xu, Xiangfeng Luo, Jie Yu, Weimin Xu
    Concurrency and Computation: Practice and Experience. 01/2011; 23:1101-1113.
  • Xinhuai Tang, Zhaoteng Song, Xiangfeng Luo
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    ABSTRACT: OWL-S is designed to support semantic and automated composition of Web services. AFLOW is a composition system, based on OWL-S, combining AI planning and workflow technology. In this paper, we discuss the implementation of the AI planning subsystem in the AFLOW, supporting higher dynamic and automation of composition. And we describe how an AI planning system (SHOP2) can be used with OWL-S Web service type descriptions in AFLOW to automatically compose Web services and support partial concurrency in OWL-S.
    Seventh International Conference on Semantics Knowledge and Grid (SKG 2011), Beijing, China, October 24-26, 2011; 01/2011
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    ABSTRACT: The acquisition of deep textual semantics is a key issue on the process of text understanding which improves the performances of e-learning, web search and web services significantly. Though many methods have been developed to acquire textual semantics, the acquisition of deep textual semantics is still a challenge issue. Herein, the acquisition method of deep textual semantics is developed to enhance the capability of text understanding of machine, including two parts:1) how to obtain and organize the domain knowledge extracted from domain text set; 2) how to stimulate the domain knowledge for obtaining the deep textual semantics. The activation process involves two cognitive mechanisms; one is the Landscape model and the other is human memory system model. The former model is a human reading model. The later model describes the memory change in the text reading process. Generalized semantic field is proposed to store the domain knowledge as the form of Long Time Memory (LTM). Specialized semantic field, which is acquired by the interaction between the text fragment and the domain knowledge, is introduced to describe the change process of textual semantics. By their mutual actions, we can get the deep textual semantics which enhances the capability of text understanding of machine; therefore, the machine can understand the text more precisely and correctly than those methods which only obtain surface textual semantics.
    Proceedings of the 10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011, 18-20 August 2011, Banff, Alberta, Canada; 01/2011
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    ABSTRACT: The measurement of textual complexity is a fundamental issue on e-learning, online question-answering, web search and browsing, etc. But it is still a challenge because the measuring process includes a series of cognitive mechanisms. According to the properties of cognitive principles in human text reading process, the different derivatives of textual keywords are given. Based on the categorical invariance in human conception learning, textual invariance is defined, and then the measuring method of textual complexity is developed which is consistent with the view of categorical invariance in human concept learning. Experiments prove that there is a strong correlation between the text understanding difficulty given by human and the textual complexity measured by our method. That is to say, the proposed method can reflect human's reading experience to some extent.
    Proceedings of the 10th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2011, 18-20 August 2011, Banff, Alberta, Canada; 01/2011
  • Zhilin Wang, Xinhuai Tang, Xiangfeng Luo
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    ABSTRACT: Cloud computing has emerged as a new paradigm, which is the long-held dream of computing as utility, customer get it on an on-demand model. When discuss about performance requirement and QoS (Quality of Service) of service, it is hard to tackle these problem in a round consideration. In this work we propose an SLA-aware (Service Level Agreement aware) framework ¨C cloud service provider (CSP) for cloud service (cloud infrastructure) delivery, and making allowance for the benefit of stakeholder of cloud service provider and service consumer. By using our proposed system and hierarchy SLA monitoring model we reached our win-win objective which is maximum revenue of cloud provider and minimum SLA violation.
    Seventh International Conference on Semantics Knowledge and Grid (SKG 2011), Beijing, China, October 24-26, 2011; 01/2011
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    ABSTRACT: From a point of view, the site ranking method based on Page Rank, website traffic, or field relevance can give sites a reasonable measure of ranking. But in the study of vertical search engine technology, such assessment methods can't give a true evaluation of the ranking for sites in specific fields. To address the issue above, in this paper, we propose a new Field-Sensitive Site Ranking method, which is based on Analytic Hierarchy Process method and weighs five factors of web sites. Firstly, we elaborate these factors and quantify their effects on site ranking, then build a field-sensitive site ranking mathematical model and calculate site ranking. Finally, we apply this website ranking method to a sample data set, verifying its validity and accuracy.
    Computational and Information Sciences (ICCIS), 2011 International Conference on; 01/2011
  • Zheng Xu, Xiangfeng Luo, Jie Yu, Weimin Xu
    Concurrency and Computation: Practice and Experience. 01/2011; 23:2496-2510.
  • Fangfang Liu, Yan Chi, Jie Yu, Xiangfeng Luo, Zheng Xu
    Int. J. Web Service Res. 01/2011; 8:29-46.
  • Xiangfeng Luo, Chuanliang Cai, Qingliang Hu
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    ABSTRACT: The essential abilities of text knowledge representation, such as automatic construction, carrying abundant semantics and flexible reasoning, should be held due to the rapid growth of web resources and the requirements of the reasoning-based web services. However, current text knowledge representation models either lose many textual semantics or cannot be constructed automatically. To solve the above issues, text knowledge representation model is proposed based on the concept algebra of human concept learning. Then, the degree-2 power series hypothesis is developed and the reasoning ability of text representation is proposed. Finally, the results compared with current knowledge representation models show that our model performs better than other models in representing text knowledge.
    Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on; 08/2010
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    ABSTRACT: Due to the lack of associated links among web resources, it is hard for knowledge-based system to provide flexible associated services for users. To solve this problem, Associated Semantic Overlay (ASO) is proposed to semantically organize the loose web domain resources and provide support for associated services. First, using the Element Fuzzy Cognitive Maps (E-FCM) as the semantic representation of web resources, mapping from keywords to web resources is built to make ASO appropriate for the discovery of associated services. Secondly, based on domain keywords and domain association rules, an efficient computing approach of associated links among web resources is presented to automatically build the ASO, which can assist the discovery of associated services. Experimental results demonstrate that ASO can efficiently provide associated services for users.
    Advanced Intelligent Computing Theories and Applications, 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, August 18-21, 2010. Proceedings; 01/2010