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An improved bp neural network algorithm based on factor analysis

Journal of Convergence Information Technology 2010年第4期5卷

作者： Ding, Shifei Jia, Weikuan Su, Chunyang Liu, Xiaoliang Chen, Jinrong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Back-Propagation (BP) neural network, as one of the most mature and most widespread algorithms, has the ability of large scale computing and has unique advantages when dealing with nonlinear high dimensional data. But when we manipulate high dimensional data with BP neural network, many feature variables provide enough information, but too many network inputs go against designing of the hidden-layer of the network and take up plenty of storage space as well as computing time, and in the process interfere the convergence of the training network, even influence the the accuracy of recognition finally. Factor analysis (FA) is a multivariate analysis method which transforms many feature variables into few synthetic variables. Aiming at the characteristics that the samples processed have more feature variables, combining with the structure feature of BP neural network, a FA-BP neural network algorithm is proposed. Firstly we reduce the dimensionality of the feature factor using FA, and then regard the features reduced as the input of the BP neural network, carry on network training and simulation with low dimensional data that we get. This algorithm here can simplify the network structure, improve the velocity of convergence, and save the running time. Then we apply the new algorithm in the field of pest prediction to emulate. The results show that under the prediction precision is not reduced, the error of the prediction value is reduced by using the new algorithm, and therefore the algorithm is effective.

关键词： Neural networks

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An intelligent Call Center Platform for Mobile Communication Enterprises

An Intelligent Call Center Platform for Mobile Communication...

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WRI International Conference on Communications and Mobile computing, CMC

作者： Weimin Wang Liangliang Liu Dongsheng Wang Yanan Cao Yuming Wu Baoyuan Qi Dongchun Qiao Jingyang Guo Yufei Zheng Cungen Cao Li Jianghua Shi Yuan Li Ruilin Sang Changqin Shen Nan The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Guangdong Communication Group Customer Service Center Guangzhou China

ISBN: (纸本)9781424463275

In this paper, we introduced an intelligent call center platform (ICCP) for communication enterprises. The platform is based on two broad suites of technologies: Knowledge management and natural language processing. First, we designed an enterprise knowledge modeling technology, and provided a knowledge management system for managing customer service knowledge. Then mobile customers are allowed to send Chinese queries, through either Internet tools (e.g. MSN, QQ, BBS and Fetion) or Wireless SM devices (e.g. mobile phones), to a multi-tier natural language understanding engine, and the engine retrieves the knowledge bases to find correct answers after understanding the queries. The ICCP has been successfully used in a domestic communication group since March 2009, and achieved a satisfactory performance.

关键词： Mobile communication Knowledge management Search engines Natural language processing Process design Technology management Customer service Internet Samarium Mobile handsets

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Single-side-band optical modulation in SCM systems for high-speed optical transmission

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Optoelectronics Letters 2009年第1期5卷 48-50页

作者：李忠义廖同庆 Key Laboratory on Intelligent Computing & Signal Processing of Ministry of Education Anhui University

In order to decrease dispersion penalty and increase the optical bandwidth efficiency,an optical single-side-band modulation(SSBM) scheme in sub-carrier multiplexing(SCM) is *** principle of the SSBM is analytically presented,and a configuration for generating optical SSB signal is proposed using a balanced Mach-Zehnder electro-optic modulator.

关键词： Electrooptical devices

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Extracting comparative commonsense from the web

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作者： Cao, Yanan Cao, Cungen Zang, Liangjun Wang, Shi Wang, Dongsheng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Road Zhongguancun Beijing 100190 China Graduate University of Chinese Academy of Sciences No. 19 Yu Quan Road Shi Jing Shan Distinct Beijing 100049 China

ISBN: (纸本)3642163262

Commonsense acquisition is one of the most important and challenging topics in Artificial Intelligence. Comparative commonsense, such as "In general, a man is stronger than a woman", denotes that one entity has a property or quality greater or less in extent than that of another. This paper presents an automatic method for acquiring comparative commonsense from the World Wide Web. We firstly extract potential comparative statements from related texts based on multiple lexico-syntactic patterns. Then, we assess the candidates using Web-scale statistical features. To evaluate this approach, we use three measures: coverage of the web corpora, precision and recall which achieved 79.2%, 76.4% and 83.3%, respectively in our experiments. And the experimental results show that this approach profits significantly when the semantic similarity relationships are involved in the commonsense assessment. © 2010 IFIP.

关键词： Semantics

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A noise handling method for hyper surface classification

A noise handling method for hyper surface classification

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Tingting Li Fuzhen Zhuang Qing He Chinese Academy and Sciences China Chinese Academy of Sciences Beijing Beijing CN Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China

Hyper surface classification (HSC) based on Jordan Curve Theorem is proven to be a simple and effective method to classify large datasets. Like most of classification algorithms, noise could also impact its accuracy even if the HSC algorithm limits the influence of noise in a local small region. In this paper, we propose a method that intuitively captures the primary goal of improving the accuracy of HSC when trained on noisy training datasets. The proposed method uses a separate pruning set to test whether the hyper surfaces covering few samples are assigned wrong labels due to the existence of noise. And then reassigns them appropriate labels if necessary. We compare the performance of HSC with and without the noise handling method. The promising experimental results indicate that the noise handling method can improve the accuracy of HSC when trained on noisy datasets, while keeping good performance when it is applied to datasets without noise. At the same time, it also reduces the model complexity of HSC to some extent.

关键词： Noise Accuracy Training Surface treatment Noise measurement Classification algorithms Iris

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Web Service Composition on the Environment Level

Web Service Composition on the Environment Level

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Guangjun Cai The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

Service-oriented computing (SOC) promises a world of cooperating services loosely connected, creating dynamic business processes and agile applications. Service composition plays a very important role in it. One important problem related to service composition is about what the content of service description is. Most approaches focus on the description about web services themselves, and fail to consider the behaviour of the services in composition. This paper introduces a composition approach on the environment level. The basic idea of it is to develop a model-based approach by using the stability character of environment to encapsulate the changing of the service and the request. Our approach both facilitate to improve the composition efficiency and is more appropriate for compositing complex services or behaviour services based on its’ behaviour. A running travel example is used to illustrate our approach.

关键词： Service-oriented computing environment level service composition service behaviour

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A visual search system based on multi-scale population cell coding

A visual search system based on multi-scale population cell ...

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IEEE International Conference on Cognitive Informatics

作者： Fang, Fang Miao, Jun Qing, Laiyun Gao, Wen School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science and Engineering Graduate University of the Chinese Academy of Sciences Beijing 100049 China Institute for Digital Media Peking University Beijing 100871 China

ISBN: (纸本)9781424480401

Gaze movement plays an important role in human visual search system. How to simulate such a system to efficiently encode and decode gaze movement for target searching is a meaningful issue. There are two key points that should be addressed for this issue. First, eye movement is affected by the visual context that includes more than one object in images. It is important to study how to encode the spatial relationship between the target and the other objects, and decode the spatial relationship to drive the gaze moving to the target. Second, the human retina has a non-uniform distribution of light sensing neurons, which can be viewed as a composition of neuron arrays in different spatial resolutions. When a system searches a target, how many scales of visual fields should be involved to sense the image stimulus? In this paper, we propose a visual search system using the population cell coding mechanism and the multi-scale visual field as sensing input. As an example, the system is applied to human eye center searching. An experimental comparison of a Full-scale visual field coding system and a Gradual-scale coding system is carried out. The experiment results show the Gradual-scale coding system performs better than Full-scale coding system for target searching. © 2010 IEEE.

关键词： Eye movements

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A Laplacian eigenmaps based semantic similarity measure between words

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作者： Wu, Yuming Cao, Cungen Wang, Shi Wang, Dongsheng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing 100-190 China Graduate University of Chinese Academy of Sciences No. 19 Yu Quan Road Shi Jing Shan Distinct Beijing 100-049 China

ISBN: (纸本)3642163262

The measurement of semantic similarity between words is very important in many applicaitons. In this paper, we propose a method based on Laplacian eigenmaps to measure semantic similarity between words. First, we attach semantic features to each word. Second, a similarity matrix ,which semantic features are encoded into, is calculated in the original high-dimensional space. Finally, with the aid of Laplacian eigenmaps, we recalculate the similarities in the target low-dimensional space. The experiment on the Miller-Charles benchmark shows that the similarity measurement in the low-dimensional space achieves a correlation coefficient of 0.812, in contrast with the correlation coefficient of 0.683 calculated in the high-dimensional space, implying a significant improvement of 18.9%. © 2010 IFIP.

关键词： Semantics

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D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification

D-LDA: A Topic Modeling Approach without Constraint Generati...

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IEEE International Conference on Data Mining (ICDM)

作者： Fuzhen Zhuang Ping Luo Zhiyong Shen Qing He Yuhong Xiong Zhongzhi Shi Chinese Academy and Sciences China Hewlett Packard Laboratories China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Innovation Works USA

We study what we call semi-defined classification, which deals with the categorization tasks where the taxonomy of the data is not well defined in advance. It is motivated by the real-world applications, where the unlabeled data may also come from some other unknown classes besides the known classes for the labeled data. Given the unlabeled data, our goal is to not only identify the instances belonging to the known classes, but also cluster the remaining data into other meaningful groups. It differs from traditional semi-supervised clustering in the sense that in semi-supervised clustering the supervision knowledge is too far from being representative of a target classification, while in semi-defined classification the labeled data may be enough to supervise the learning on the known classes. In this paper we propose the model of Double-latent-layered LDA (D-LDA for short) for this problem. Compared with LDA with only one latent variable y for word topics, D-LDA contains another latent variable z for (known and unknown) document classes. With this double latent layers consisting of y and z and the dependency between them, D-LDA directly injects the class labels into z to supervise the exploiting of word topics in y. Thus, the semi-supervised learning in D-LDA does not need the generation of pair wise constraints, which is required in most of the previous semi-supervised clustering approaches. We present the experimental results on ten different data sets for semi-defined classification. Our results are either comparable to (on one data sets), or significantly better (on the other nine data set) than the six compared methods, including the state-of-the-art semi-supervised clustering methods.

关键词： Data models Mathematical model Clustering algorithms Analytical models Companies Equations Web pages

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Combining the Missing Link: An Incremental Topic Model of Document Content and Hyperlink

Combining the Missing Link: An Incremental Topic Model of Do...

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International Asia-Pacific Web Conference (APWEB)

作者： Huifang Ma Zhixin Li Zhongzhi Shi Chinese Academy and Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

The content and structure of linked information such as sets of web pages or research paper archives are dynamic and keep on changing. Even though different methods are proposed to exploit both the link structure and the content information, no existing approach can effectively deal with this evolution. We propose a novel joint model, called Link-IPLSI, to combine texts and links in a topic modeling framework incrementally. The model takes advantage of a novel link updating technique that can cope with dynamic changes of online document streams in a faster and scalable way. Furthermore, an adaptive asymmetric learning method is adopted to freely control the assignment of weights to terms and citations. Experimental results on two different sources of online information demonstrate the time saving strength of our method and indicate that our model leads to systematic improvements in the quality of classification and link prediction.

关键词： Laboratories intelligent structures Information processing Computers Web pages Programmable control Adaptive control Learning systems Predictive models Data mining

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