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Journal of Software 2013年第4期8卷 834-841页

作者： Zhu, Hong Ding, Shifei Zhao, Han Bao, Lina School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China School of Medical Information Xuzhou Medical College Xuzhou 221000 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

For high dimensional data, the redundant attributes of samplers will not only increase the complexity of the calculation, but also affect the accuracy of final result. The existing attribute reduction methods are encountering bottleneck problem of timeliness and spatiality. In order to looking for a relatively coarse attributes granularity of problem solving, this paper proposes an efficient attribute granulation method to remove redundancy attribute. The method calculates the similarity of attributes according attribute discernibility first, and then clusters attributes into several group through affinity propagation clustering algorithm. At last, representative attributes are produced through some algorithms to form a coarser attribute granularity. Experimental results show that the attribute granulation method based on affinity propagation clustering algorithm(AGAP) method is a more efficient algorithm than traditional attribute reduction algorithm(AR). © 2013 ACADEMY PUBLISHER.

关键词： Granulation

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Dynamic description logic based semantics web service composition

Dynamic description logic based semantics web service compos...

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9th International Conference on Semantics, Knowledge and Grids, SKG 2013

作者： Zhang, Jianhua Wang, Wenjie Shi, Zhongzhi Tian, Dongping Yue, Jinpeng Zhang, Bo Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479930128

Web service composition is one of the fundamental technologies in implementing Service Oriented Architecture (SOA) based applications. Description Logic based Web service composition can easily express the static knowledge, however it is lack the dynamic knowledge support. Dynamic Description Logic extends from Description Logic and it can represent both static and dynamic knowledge. In this paper, we propose a Web service composition method base on AI planning which introduce the action dimension to the Web service composition. Finally, we give a simple example to show the algorithm's validity. © 2013 IEEE.

关键词： Computer circuits

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Time evolving graphical password for securing mobile devices 13

Time evolving graphical password for securing mobile devices

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8th ACM SIGSAC Symposium on information, Computer and Communications Security, ASIA CCS 2013

作者： Wang, Zhan Jing, Jiwu Li, Liang State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781450317672

Increasingly widespread use of mobile devices for processing monetary transactions and accessing business secrets has created a great demand on securing mobile devices. Poorly designed authentication mechanisms (e.g., screen lock and SIM card lock) on mobile devices either make users feel a hassle to lock the devices, or are vulnerable to attacks, such as shoulder surfing and smudge attack. In this paper, we propose a new login option for unlocking mobile devices called Time-Evolving Graphical Password (TEGP), which improves the strength of the password gradually over time by evolving the distortion degree of the images in the challenge portfolio without changing the pass images. By taking advantage of the extraordinary human ability to recall images, TEGP authenticates users by asking them to recognize the pass images which are transformed from the images uploaded by the user at registration. To achieve desired security and remain the usability, we present two metrics, information Retention Rate (IRR) and Password Diversity Score (PDS), to advise the selection and distortion of the pass images and decoy images. Our experimental results show the memorability from the perspective of users, and the ability of TEGP to defend against various attacks. © 2013 ACM.

关键词： Edge detection

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Semantic separator learning and its applications in unsupervised Chinese text parsing

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Frontiers of Computer Science 2013年第1期7卷 55-68页

作者： Yuming WU Xiaodong LUO Zhen YANG Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of the Chinese Academy of Sciences Beijing 100049 China China Telecom Corporation Limited Shanghai Branch Shanghai 200120 China Shanghai Research Institute of China Telecom Corporation Limited Shanghai 200120 China

Grammar learning has been a bottleneck problem for a long time. In this paper, we propose a method of seman- tic separator learning, a special case of grammar learning. The method is based on the hypothesis that some classes of words, called semantic separators, split a sentence into sev- eral constituents. The semantic separators are represented by words together with their part-of-speech tags and other infor- mation so that rich semantic information can be involved. In the method, we first identify the semantic separators with the help of noun phrase boundaries, called subseparators. Next, the argument classes of the separators are learned from cor- pus by generalizing argument instances in a hypernym space. Finally, in order to evaluate the learned semantic separators, we use them in unsupervised Chinese text parsing. The exper- iments on a manually lab.led test set show that the proposed method outperforms previous methods of unsupervised text parsing.

关键词： semantic separator separator learning unsuper vised text parsing

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Flexible navigation in smartphones and tablets using scalab.e storyboards 13

Flexible navigation in smartphones and tablets using scalabl...

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3rd ACM International Conference on Multimedia Retrieval, ICMR 2013

作者： Zheng, Shuai Herranz, Luis Jiang, Shuqiang Key Lab. of Intelligent Information Processing Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Software Engineering Beijing Jiaotong University Beijing 100044 China

ISBN: (纸本)9781450320337

In this demo paper we present a multiscale browsing interface for handheld devices, in which the user can interactively change the scale of the storyboard to easily adjust the amount of information desired. Conventional and hierarchical storyboards provide one or very few possible lengths. In contrast, scalab.e storyboards allow the number of images and the storyboard itself to be adapted to the device constraints (e.g. aspect ratio, resolution) and navigation state with much finer granularity. Several levels and modes, including segment of interest, are provided for more intuitive and convenient navigation. © 2013 Authors.

关键词： Aspect ratio

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Cross-view graph embedding

Cross-view graph embedding

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Huang, Zhiwu Shan, Shiguang Zhang, Haihong Lao, Shihong Chen, Xilin Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China OMRON Social Solutions Co. Ltd. Kyoto Japan

ISBN: (纸本)9783642374432

Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) under the proposed framework. Different from previous cross-view methods only preserving inter-view discriminant information or the intra-view local structure, CLODA preserves the local structure and the discriminant information of both intra-view and inter-view. Extensive experiments are conducted to evaluate our algorithms on two cross-view face recognition problems: face recognition across poses and face recognition across resolutions. These real-world face recognition experiments demonstrate that our framework achieves impressive performance in the cross-view problems. © 2013 Springer-Verlag.

关键词： Face recognition

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Shared structure learning for multiple tasks with multiple views

Shared structure learning for multiple tasks with multiple v...

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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013

作者： Jin, Xin Zhuang, Fuzhen Wang, Shuhui He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9783642409905

Real-world problems usually exhibit dual-heterogeneity, i.e., every task in the problem has features from multiple views, and multiple tasks are related with each other through one or more shared views. To solve these multi-task problems with multiple views, we propose a shared structure learning framework, which can learn shared predictive structures on common views from multiple related tasks, and use the consistency among different views to improve the performance. An alternating optimization algorithm is derived to solve the proposed framework. Moreover, the computation load can be dealt with locally in each task during the optimization, through only sharing some statistics, which significantly reduces the time complexity and space complexity. Experimental studies on four real-world data sets demonstrate that our framework significantly outperforms the state-of-the-art baselines. © 2013 Springer-Verlag.

关键词： Learning systems

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A motivational system for mind model CAM

A motivational system for mind model CAM

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2013 AAAI Fall Symposium

作者： Shi, Zhongzhi Zhang, Jianhua Yue, Jinpeng Qi, Baoyuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781577356417

A motivation model is proposed in the paper. Based on the model we develop a motivational system for mind model CAM. Through the application in automatic navigation of animal robots shows the motivation system is useful to solve the dynamic and complexity automatic problem. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Motivation

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Phrase filtering for content words in hierarchical phrase-based model

Phrase filtering for content words in hierarchical phrase-ba...

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14th Workshop on Chinese Lexical Semantics, CLSW 2013

作者： Wang, Xing Xie, Jun Song, Linfeng Lv, Yajuan Yao, Jianmin School of Computer Science AndTechnology Soochow University Suzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783642451843

When hierarchical phrase-based statistical machine translation systems are used for language translation, sometimes the translations' content words were lost: source-side content words is empty when translated into target texts during decoding. Although the translations' BLEU score is very high, it is difficult to understand the translations because of the loss of the content words. In this paper, we propose a basic and efficient method for phrase filtering, with which the phrase' content words translation are checked to decide whether to use the phrase in decoding or not. The experimental results show that the proposed method alleviates the problem of the loss content words' and improves the BLEU scores. © 2013 Springer-Verlag.

关键词： Decoding

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Concept learning for cross-domain text classification: A general probabilistic framework

Concept learning for cross-domain text classification: A gen...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Zhuang, Fuzhen Luo, Ping Yin, Peifeng He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Hewlett Packard Labs China Pennsylvania State University United States

ISBN: (纸本)9781577356332

Cross-domain learning targets at leveraging the knowledge from source domains to train accurate models for the test data from target domains with different but related data distributions. To tackle the challenge of data distribution difference in terms of raw features, previous works proposed to mine high-level concepts (e.g., word clusters) across data domains, which shows to be more appropriate for classification. However, all these works assume that the same set of concepts are shared in the source and target domains in spite that some distinct concepts may exist only in one of the data domains. Thus, we need a general framework, which can incorporate both shared and distinct concepts, for cross-domain classification. To this end, we develop a probabilistic model, by which both the shared and distinct concepts can be learned by the EM process which optimizes the data likelihood. To validate the effectiveness of this model we intentionally construct the classification tasks where the distinct concepts exist in the data domains. The systematic experiments demonstrate the superiority of our model over all compared baselines, especially on those much more challenging tasks.

关键词： Classification (of information)

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