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Application of dynamic service composition in web question answering

International Journal of Wireless and Mobile computing 2012年第3期5卷 300-307页

作者： Wang, Liu Liao, Lejian Li, Peng School of Computer Science Beijing Institute of Technology Beijing Key Lab. of Intelligent Information Beijing 100081 China

Web Question Answering (WQA) and Web Service (WS) are parallel fields in intelligent web computing. In network services, they are used widely, and they are rarely combined together. For many intelligent web applications, however, using them together tends to be important. This paper based on the study of significant techniques of WQA, WS and Hierarchical Task Network (HTN), including Natural Language processing (NLP), Web Service Ontology and a planner of HTN, gives a proposal of WQA framework. This framework combines NLP, predicate logic, Semantic Web description and an HTN planner-SHOP2, turning question answering into a planning problem by question mapping and service planning. It addresses a transition from natural language to semantic expression, composites web services dynamically by using SHOP2, and obtains the answering that meets customers' question by executing the web services sequence. Copyright © 2012 Inderscience Enterprises Ltd.

关键词： Web services

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Hierarchical Chunk-to-String Translation 12

Hierarchical Chunk-to-String Translation

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Annual meeting of the Association for Computational Linguistics

作者： Yang Feng Dongdong Zhang Mu Li Ming Zhou Qun Liu University of Sheffield Sheffield UK Microsoft Research Asia Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences

ISBN: (纸本)9781622761715

We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrase-based model and the tree-to-string model, to combine the merits of the two models. With the help of shallow parsing, our model learns rules consisting of words and chunks and meanwhile introduce syntax cohesion. Under the weighed synchronous context-free grammar defined by these rules, our model searches for the best translation derivation and yields target translation simultaneously. Our experiments show that our model significantly outperforms the hierarchical phrase-based model and the tree-to-string model on English-Chinese Translation tasks.

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${\rm S}^{3}{\rm MKL}$: Scalab.e Semi-Supervised Multiple Kernel Learning for Real-World Image Applications

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IEEE Transactions on Multimedia 2012年第4期14卷 1259-1274页

作者： Shuhui Wang Qingming Huang Shuqiang Jiang Qi Tian Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Texas-San Antonio San Antonio TX USA

We study the visual learning models that could work efficiently with little ground-truth annotation and a mass of noisy unlab.led data for large scale Web image applications, following the subroutine of semi-supervised learning (SSL) that has been deeply investigated in various visual classification tasks. However, most previous SSL approaches are not able to incorporate multiple descriptions for enhancing the model capacity. Furthermore, sample selection on unlab.led data was not advocated in previous studies, which may lead to unpredictable risk brought by real-world noisy data corpse. We propose a learning strategy for solving these two problems. As a core contribution, we propose a scalab.e semi-supervised multiple kernel learning method (S 3 MKL) to deal with the first problem. The aim is to minimize an overall objective function composed of log-likelihood empirical loss, conditional expectation consensus (CEC) on the unlab.led data and group LASSO regularization on model coefficients. We further adapt CEC into a group-wise formulation so as to better deal with the intrinsic visual property of real-world images. We propose a fast block coordinate gradient descent method with several acceleration techniques for model solution. Compared with previous approaches, our model better makes use of large scale unlab.led images with multiple feature representation with lower time complexity. Moreover, to address the issue of reducing the risk of using unlab.led data, we design a multiple kernel hashing scheme to identify the “informative” and “compact” unlab.led training data subset. Comprehensive experiments are conducted and the results show that the proposed learning framework provides promising power for real-world image applications, such as image categorization and personalized Web image re-ranking with very little user interaction.

关键词： Kernel Visualization Training Data models Noise measurement Training data Learning systems

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Mechanism of concept learning in topologized knowledge granular space based on GrC

Mechanism of concept learning in topologized knowledge granu...

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IEEE International Conference on Granular computing (GRC)

作者： Zuqiang Meng Zhongzhi Shi Shimo Shen College of Computer Electronics and Information Guangxi University Nanning China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Concept learning in information systems is actually performed in knowledge granular space on information systems. But no much attention has been paid to study such a knowledge granular space and its structure so far, and its structure characteristics are still poorly understood. In this paper, the granular space is firstly topologized and is decomposed into granular worlds. Then it is modeled as a bounded lattice. Finally, by using graph theory, the bounded lattice obtained is expressed as a hass graph, and the mechanism of concept learning in information systems can be visually explained. With related properties of topological space, bounded lattice and graph theory, the "mysterious" granular space can be delved more deeply into. This work can form a basis for designing concept learning algorithm as well as can richen the theory system for granular computing.

关键词： Computational modeling Iron Lattices Ice

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Using Syntactic Head information in Hierarchical Phrase-Based Translation 12

Using Syntactic Head Information in Hierarchical Phrase-Base...

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Workshop on Statistical Machine Translation

作者： Junhui Li Zhaopeng Tu Guodong Zhou Josef van Genabith Centre for Next Generation Localisation School of Computing Dublin City University Key Lab. of Intelligent Info. Processing Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Technology Soochow University China

ISBN: (纸本)9781622765928;1622765923

Chiang's hierarchical phrase-based (HPB) translation model advances the state-of-the-art in statistical machine translation by expanding conventional phrases to hierarchical phrases - phrases that contain sub-phrases. However, the original HPB model is prone to over-generation due to lack of linguistic knowledge: the grammar may suggest more derivations than appropriate, many of which may lead to ungrammatical translations. On the other hand, limitations of glue grammar rules in the original HPB model may actually prevent systems from considering some reasonable derivations. This paper presents a simple but effective translation model, called the Head-Driven HPB (HD-HPB) model, which incorporates head information in translation rules to better capture syntax-driven information in a derivation. In addition, unlike the original glue rules, the HD-HPB model allows improved reordering between any two neighboring non-terminals to explore a larger reordering search space. An extensive set of experiments on Chinese-English translation on four NIST MT test sets, using both a small and a large training set, show that our HD-HPB model consistently and statistically significantly outperforms Chiang's model as well as a source side SAMT-style model.

关键词： Syntactic information Hierarchical Phrase-Based Translations syntax Translation machine translation Translation Process Hierarchical Rule train stock Glues derivation Head

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Head-Driven Hierarchical Phrase-based Translation 12

Head-Driven Hierarchical Phrase-based Translation

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Annual Meeting of The Association for Computational Linguistics

ISBN: (纸本)9781622761715

This paper presents an extension of Chiang's hierarchical phrase-based (HPB) model, called Head-Driven HPB (HD-HPB), which incorporates head information in translation rules to better capture syntax-driven information, as well as improved reordering between any two neighboring non-terminals at any stage of a derivation to explore a larger reordering search space. Experiments on Chinese-English translation on four NIST MT test sets show that the HD-HPB model significantly outperforms Chiang's model with average gains of 1.91 points absolute in BLEU.

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A Group key assignment scheme based on multi-dimensional space circle properties

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International Journal of Advancements in computing technology 2012年第16期4卷 508-514页

作者： Ge, Lina School of information science and engineering Guangxi University for nationalities Nanning Guangxi 530006 China Science Computing and Intelligent Information Processing of Guangxi higer education key lab. Guangxi Teacher Education University Nanning 530023 China

A group key assignment scheme based on multi-dimensional space circle properties is proposed, which enable the members of a group to obtain the group key by both the public information published on the notice board and the secret information of their own. The proposed scheme can be divided into three phases: user registration, group key assignment, and group key computation. The proposed scheme has such advantages as easy operations of group key update and member's join/leave, and the security properties of forward secrecy and backward secrecy.

关键词： Geometric approach Group key assignment Multi-dimensional space circle properties

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Towards collecting commonsense knowledge with hint questions

Towards collecting commonsense knowledge with hint questions

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

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

ISBN: (纸本)9780769547947

Accumulating commonsense knowledge (CK) has proven very useful for many natural language processing tasks. So far the most reliable way of acquisition is still relying on knowledge contributors to offer CK. Unfortunately, knowledge contributors often fail to think of much CK because this knowledge is usually taken for granted by people. In this paper, we explore the issue of reminding knowledge contributors by means of hint questions. Specifically, we investigate what kinds of CK are easily ignored, analyze its reason and suggest possible solution. We hope to sketch sources of the research problem and suggest possible ways forward. © 2012 IEEE.

关键词： Natural language processing systems

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Challenges and Opportunities for Trust Management in Crowdsourcing

Challenges and Opportunities for Trust Management in Crowdso...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Han Yu Zhiqi Shen Chunyan Miao Bo An School of Computer Engineering Nanyang Technological University Singapore The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Crowd sourcing (CS) systems offer a new way for businesses and individuals to leverage on the power of mass collab.ration to accomplish complex tasks in a divide-and-conquer manner. In existing CS systems, no facility has been provided for analyzing the trustworthiness of workers and providing decision support for allocating tasks to workers, which leads to high dependency of the quality of work on the behavior of workers in CS systems as shown in this paper. To address this problem, trust management mechanisms are urgently needed. Traditional trust management techniques are focused on identifying the most trustworthy service providers (SPs) as accurately as possible. Little thoughts were given to the question of how to utilize these SPs due to two common assumptions: 1) an SP can serve an unlimited number of requests in one time unit, and 2) a service consumer (SC) only needs to select one SP for interaction to complete a task. However, in CS systems, these two assumptions are no longer valid. Thus, existing models cannot be directly used for trust management in CS systems. This paper takes the first step towards a systematic investigation of trust management in CS systems by extending existing trust management models for CS trust management and conducting extensive experiments to study and analyze the performance of various trust management models in crowd sourcing. In this paper, the following key contributions are made. We 1) propose extensions to existing trust management approaches to enable them to operate in CS systems, 2) design a simulation test-bed based on the system characteristics of Amazon's Mechanical Turk (AMT) to make evaluation close to practical CS systems, 3) discuss the effect of incorporating trust management into CS system on the overall social welfare, and 4) identify the challenges and opportunities for future trust management research in CS systems.

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Properties and axiomatization of fuzzy rough sets based on fuzzy covering

Properties and axiomatization of fuzzy rough sets based on f...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ming-Fen Wu Hao-Han Han Yan-Fei Si School of Computer Science Wuyi University Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Some expanded fuzzy rough sets models have been investigated to handle fuzzy databases with uncertain, imprecise and incomplete real-valued information. In this paper, we make further research on fuzzy rough sets models in fuzzy environment, and we generalize rough fuzzy sets model based on a covering to fuzzy rough sets model based on a fuzzy covering. The lower and upper approximations of fuzzy subsets are defined based on a fuzzy covering, and basic properties are investigated. Then, the axiom definition of the lower approximation operator is given. It is shown that the rough fuzzy sets model based on a covering is a special instance of the fuzzy rough sets model based on a fuzzy covering.

关键词： Abstracts

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