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An Approach for Diagnosing Unexpected Faults in Web Service Flows

An Approach for Diagnosing Unexpected Faults in Web Service ...

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International Conference on Grid and Cooperative computing (GCC)

作者： Xu Han Zhongzhi Shi Wenjia Niu Fen Lin Donglei Zhang Key Lab. of Intell. Inf. Process. Chinese Acad. of Sci. Beijing Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Potential faults have greatly reduced the dependability of business processes, so fault diagnosis is becoming an important issue which aims at supporting self-healing service flow execution. The existing fault handling mechanism provided by BPEL can only identify the faults which have been pre-defined in standards or by users. However, unexpected faults are also the main cause of failures in service flow execution. Therefore an effective diagnosis approach is needed to solve this problem. In this paper, we propose a logic-based approach for diagnosing unexpected faults in Web service flows. This approach uses dynamic description logic (DDL) to model business processes, and diagnoses faults based on DDL reasoning. We provide the DDL-based diagnosing algorithm, which takes process description and runtime information as inputs, and returns the related information of possible faults as the result. Moreover, to improve the efficiency of online diagnosis, the incremental DDL-based diagnosing algorithm is presented. Experimental results on a demo system show the effectiveness of this approach.

关键词： Web services Fault diagnosis Logic Grid computing lab.ratories information processing Computers Testing Runtime Engines

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Focused crawling with heterogeneous semantic information

Focused crawling with heterogeneous semantic information

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2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008

作者： Huang, Rui Lin, Fen Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China Graduate University Chinese Academy of Sciences 100049 Beijing China

ISBN: (纸本)9780769534961

Focused crawlers selectively retrieve Web documents that are relevant to a predefined set of topics. To intelligently make predictions and decisions about relevant URLs and web pages, different topic models have been introduced to represent topic-specific knowledge. Yet it is difficult to support semantic interoperability among different models. Moreover, some manually specified additional semantic information, such as semantic markups and social annotations, could not be effectively used to improve crawling. This paper proposes to boost focused crawling with four kinds of semantic models and semantic information, including thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and different kinds of additional information for relevance prediction and ranking. Experiments show that the proposed model and framework effectively integrates heterogeneous semantic information for focused crawling. © 2008 IEEE.

关键词： Websites

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Word lattice reranking for Chinese word segmentation and part-of-speech tagging

Word lattice reranking for Chinese word segmentation and par...

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22nd International Conference on Computational Linguistics, Coling 2008

作者： Jiang, Wenbin Mi, Haitao Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781905593446

In this paper, we describe a new reranking strategy named word lattice reranking, for the task of joint Chinese word segmentation and part-of-speech (POS) tagging. As a derivation of the forest reranking for parsing (Huang, 2008), this strategy reranks on the pruned word lattice, which potentially contains much more candidates while using less storage, compared with the traditional n-best list reranking. With a perceptron classifier trained with local features as the baseline, word lattice reranking performs reranking with non-local features that can't be easily incorporated into the perceptron baseline. Experimental results show that, this strategy achieves improvement on both segmentation and POS tagging, above the perceptron baseline and the n-best list reranking. © 2008. Licensed to the Coling.

关键词： Computational linguistics

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Refinements in BTG-based Statistical Machine Translation 3

Refinements in BTG-based Statistical Machine Translation

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3rd International Joint Conference on Natural Language processing, IJCNLP 2008

作者： Xiong, Deyi Zhang, Min Aw, Aiti Mi, Haitao Liu, Qun Lin, Shouxun Human Language Technology Institute for Infocomm Research 21 Heng Mui Keng Terrace 119613 Singapore Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100080 China

Bracketing Transduction Grammar (BTG) has been well studied and used in statistical machine translation (SMT) with promising results. However, there are two major issues for BTG-based SMT. First, there is no effective mechanism availab.e for predicting orders between neighboring blocks in the original BTG. Second, the computational cost is high. In this paper, we introduce two refinements for BTG-based SMT to achieve better reordering and higher-speed decoding, which include (1) reordering heuristics to prevent incorrect swapping and reduce search space, and (2) special phrases with tags to indicate sentence beginning and ending. The two refinements are integrated into a well-established BTG-based Chinese-to- English SMT system that is trained on largescale parallel data. Experimental results on the NIST MT-05 task show that the proposed refinements contribute significant improvement of 2% in BLEU score over the baseline system. © 2008 IJCNLP 2008 - 3rd International Joint Conference on Natural Language processing, Proceedings of the Conference. All rights reserved.

关键词： Computer aided language translation

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A cascaded linear model for joint Chinese word segmentation and part-of-speech tagging

A cascaded linear model for joint Chinese word segmentation ...

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46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT

作者： Jiang, Wenbin Huang, Liang Liu, Qun Lü, Yajuan Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Department of Computer and Information Science Levine Hall University of Pennsylvania 3330 Walnut Street Philadelphia PA 19104 United States

ISBN: (纸本)9781932432046

We propose a cascaded linear model for joint Chinese word segmentation and partof- speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded model is able to efficiently utilize knowledge sources that are inconvenient to incorporate into the perceptron directly. Experiments show that the cascaded model achieves improved accuracies on both segmentation only and joint segmentation and part-of-speech tagging. On the Penn Chinese Treebank 5.0, we obtain an error reduction of 18.5% on segmentation and 12% on joint segmentation and part-of-speech tagging over the perceptron-only baseline. © 2008 Association for Computational Linguistics.

关键词： Computational linguistics

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Forest-based translation

Forest-based translation

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46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT

作者： Mi, Haitao Huang, Liang Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Department of Computer and Information Science Levine Hall University of Pennsylvania 3330 Walnut Street Philadelphia PA 19104 United States

ISBN: (纸本)9781932432046

Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than its string-based counterpart. However, current tree-based systems suffer from a major drawback: they only use the 1-best parse to direct the translation, which potentially introduces translation mistakes due to parsing errors. We propose a forest-based approach that translates a packed forest of exponentially many parses, which encodes many more alternatives than standard n-best lists. Large-scale experiments show an absolute improvement of 1.7 BLEU points over the 1-best baseline. This result is also 0.8 points higher than decoding with 30-best parses, and takes even less time. © 2008 Association for Computational Linguistics.

关键词： Syntactics

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PKU at ImageCLEF 2008: Experiments with query extension techniques for text-based and content-based image retrieval

PKU at ImageCLEF 2008: Experiments with query extension tech...

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2008 Working Notes for CLEF Workshop, CLEF 2008 - Co-located with the 12th European Conference on Digital Libraries, ECDL 2008

作者： Zhou, Zhi Tian, Yonghong Li, Yuanning Liu, Ting Huang, Tiejun Gao, Wen Institute of Digital Media School of EE and CS Peking University Beijing100871 China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing100190 China Graduate University Chinese Academy of Sciences Beijing100080 China

In this paper, we present our solutions for the WikipediaMM task at ImageCLEF 2008. The aim of this task is to investigate effective retrieval approaches in the context of a large-scale and heterogeneous collection of Wikipedia images that are searched by textual queries (and/or sample images and/or concepts) describing a user's information need. We first experimented with a text-based image retrieval approach with query extension, where the expansion terms are automatically selected from a knowledge base that is (semi-)automatically constructed from Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to effectively enhance the semantics of queries. Encouragingly, the experimental results rank in the first place among all submitted runs. The second approach we experimented with is content-based image retrieval (CBIR), in which we first train 1-vs-all classifiers for all query concepts by using the training images obtained by Yahoo! search, and then treat the retrieval task as visual concept detection in the given Wikipedia image set. By comparison, this approach performs better than other submitted CBIR runs. Finally, we experimented with a cross-media image retrieval approach by combining and re-ranking text-based and content-based retrieval results. Despite the final experimental results were not formally submitted before the deadline, this approach performs remarkably better than the text-based retrieval or CBIR approaches.

关键词： Content based retrieval

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Forest-based translation rule extraction

Forest-based translation rule extraction

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2008 Conference on Empirical Methods in Natural Language processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation

作者： Mi, Haitao Huang, Liang Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Dept. of Computer and Information Science University of Pennsylvania Levine Hall 3330 Walnut St. Philadelphia PA 19104 United States

Translation rule extraction is a fundamental problem in machine translation, especially for linguistically syntax-based systems that need parse trees from either or both sides of the bitext. The current dominant practice only uses 1-best trees, which adversely affects the rule set quality due to parsing errors. So we propose a novel approach which extracts rules from a packed forest that compactly encodes exponentially many parses. Experiments show that this method improves translation quality by over 1 BLEU point on a state-of-the-art tree-to-string system, and is 0.5 points better than (and twice as fast as) extracting on 30- best parses. When combined with our previous work on forest-based decoding, it achieves a 2.5 BLEU points improvement over the baseline, and even outperforms the hierarchical system of Hiero by 0.7 points. © 2008 Association for Computational Linguistics.

关键词： Hierarchical systems

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Locally Assembled Binary (lab. Feature with Feature-centric Cascade for Fast and Accurate Face Detection

Locally Assembled Binary (LAB) Feature with Feature-centric ...

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26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.11

作者： Shengye Yan Shiguang Shan Xilin Chen Wen Gao Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy of Sciences (CAS) Beijing China School of EE& Peking University Beijing China Digital Media Research Center Institute of Computing Technology Chinese Academy and Sciences Beijing China

In this paper, we describe a novel type of feature for fast and accurate face detection. The feature is called Locally Assembled Binary (lab. Haar feature. lab.feature is basically inspired by the success of Haar feature and Local Binary Pattern (LBP) for face detection, but it is far beyond a simple combination. In our method, Haar features are modified to keep only the ordinal relationship (named by binary Haar feature) rather than the difference between the accumulated intensities. Several neighboring binary Haar features are then assembled to capture their co-occurrence with similar idea to LBP. We show that the feature is more efficient than Haar feature and LBP both in discriminating power and computational cost. Furthermore, a novel efficient detection method called feature-centric cascade is proposed to build an efficient detector, which is developed from the feature-centric method. Experimental results on the CMU+MIT frontal face test set and CMU profile test set show that the proposed method can achieve very good results and amazing detection speed.

关键词： Assembly Face detection Computer vision Detectors Content addressable storage Computational efficiency Testing intelligent robots Humans Skin

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Manifold-Manifold Distance with Application to Face Recognition based on Image Set

Manifold-Manifold Distance with Application to Face Recognit...

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26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), vol.9

作者： Ruiping Wang Shiguang Shan Xilin Chen Wen Gao Graduate School of Chinese Academy of Sciences Beijing China Digital Media Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China School of EE&CS Peking University Beijing China

In this paper, we address the problem of classifying image sets, each of which contains images belonging to the same class but covering large variations in, for instance, viewpoint and illumination. We innovatively formulate the problem as the computation of Manifold-Manifold Distance (MMD), i.e., calculating the distance between nonlinear manifolds each representing one image set. To compute MMD, we also propose a novel manifold learning approach, which expresses a manifold by a collection of local linear models, each depicted by a subspace. MMD is then converted to integrating the distances between pair of subspaces respectively from one of the involved manifolds. The proposed MMD method is evaluated on the task of Face Recognition based on Image Set (FRIS). In FRIS, each known subject is enrolled with a set of facial images and modeled as a gallery manifold, while a testing subject is modeled as a probe manifold, which is then matched against all the gallery manifolds by MMD. Identification is achieved by seeking the minimum MMD. Experimental results on two public face databases, Honda/UCSD and CMU MoBo, demonstrate that the proposed MMD method outperforms the competing methods.

关键词： Face recognition Probes Image converters Content addressable storage Testing Cameras Image storage Video sequences Image recognition Object recognition

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