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检索条件"任意字段=7th International Conference on Advanced Language Processing and Web Information Technology"

共 1374 条记录，以下是941-950 订阅

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Cognitive knowledge status of learning path in C++ programming language based on Rule Space Model for college students

Cognitive knowledge status of learning path in C++ programmi...

引用

international conference on Networked Computing and advanced information Management (NCM)

作者： Wen-Chih Chang Ruo-Jie Zhan Department Information Management Chung Hua University Taiwan Industrial Technology and Research Institute Taiwan

these instructions give you basic guidelines for preparing papers for conference proceedings. Programming language is a practical course, which trains students' logical thinking and problem solving. It involves logical design, problem analysis and problem solving. therefore, to promote students' programming, debugging and basic concepts understanding is an important issue. Programming language is one of the basic courses. Students learn the information planning, managing and manipulation from variable declaration, data processing, and flow control and output progress. this study applied Rule Space Model to generalize, analyze and study the C++ teaching concepts. Students are evaluated and found out the cognition mistakes. this study assisted find out the learning routes and help learning actively. the experimental objectives are 100 freshmen of the information Management Department, who studied Programming language (I) course. the experiment result showed the Knowledge attributes which students mastered and the two learning routes in programming language. According to the student learning analysis table from the knowledge structure, students can realize the weakness and follow teachers' instructions and suggestions. Based on the analysis result, teachers design the appropriate learning route for students and provide sufficient practical practice, engage team competitions and motivate students to promote the learning performance.

关键词： Programming Education Object oriented modeling Unified modeling language Arrays Control systems

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Distributed continuous queries over web service event streams

Distributed continuous queries over Web service event stream...

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international conference on Next Generation web Services Practices (NWeSP)

作者： Waldemar Hummer Benjamin Satzger Philipp Leitner Christian Inzinger Schahram Dustdar Distributed Systems Group Vienna University of Technology Austria

Complex Event processing over web service event streams poses huge challenges with regard to efficient, scalable execution as well as expressive models and languages that account for the dynamics in long-running queries. We present a distributed query platform that tackles these problems. Our novel query model permits to specify inputs that provide data for other inputs and need to be processed first. An XQuery language extension lets users easily express such dependencies, which are then continuously resolved with the required data at runtime. Query specifications are abstracted from physical deployment, allowing the platform to distribute the execution and to elastically scale up and down. We evaluate several aspects of our prototype in a Cloud computing environment.

关键词： web services Subscriptions Data models XML Companies Unified modeling language Monitoring

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Developing a model of citizens' perception of e-government system performance and their attained benefit

Developing a model of citizens' perception of e-government s...

引用

作者： Al-Haddad, Shatha Hyland, Peter N. School of Information Systems and Technology University of Wollongong NSW Wollongong Australia

ISBN: (纸本)9789898425515

Governments world wide have been, increasingly, implementing e-government initiatives for their potential significant benefits;among which is delivering better services to citizens through increasing citizens' convenience, satisfaction, and independency;and saving their time, effort, and cost. Achieving each benefit is an objective to these governments;and fulfilling each objective is considered a critical success factor. Hence, governments need to assess whether they were able to obtain their preset goals, and to which degree they were able to do so. this study merely focuses on the citizens' perspective of the evaluation. However, the relevant literature seem to lack adequate studies that propose such evaluation tool that is sufficient and has been reliably validated. therefore, the purpose of this study is to fill this gap by proposing a conceptual model which measures the e-government performance from citizens' perspective and their psychological and tangible benefits. While developing the model we also consider the attributes which impact citizens' perceptions and obtained values which, in turn, influence their adoption.

关键词： Government data processing

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the design of computer aided medical diagnosis system based on maximum entropy

The design of computer aided medical diagnosis system based ...

引用

IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Faguo Zhou Enshen Wu School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing China Logistics Services Industry Group Liaocheng University Liaocheng China

In recent decades, with the continuous improvement of computer performance, in medicine, biology and other fields, its applications are paid more and more attention to by researchers and scholars. Aided medical diagnosis and treatment system based on computer has already become a hotspot. In this paper, the aided medical diagnosis system based on knowledge base and maximum entropy is put forward. And this system will become important aids of medical diagnosis and treatment.

关键词： Medical diagnostic imaging

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Complex emotion categorization and tagging for Chinese

Complex emotion categorization and tagging for Chinese

引用

IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Peilin Jiang Fuji Ren Fei Wang Nanning Zheng Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China Graduate School of Advanced Technology and Science University of Tokushima Tokushima Japan Department of Information Science & Intelligent Systems University of Tokushima Tokushima Japan

To understand emotion and make machine emotion is one of the goals of affective computing. In order to understand language from interface of machine, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. In this paper, a novel method to analyze emotion category is proposed according to the statistics of affective word hierarchy in Dictionary of contemporary Chinese. the emotion hierarchy is called complex emotion. Firstly, over 7,000 common affective words have be annotated and their detailed explanations had been collected for an affective lexicon, then we analyze the consistent relationship in the affective lexicon and consequently 52 salient complex emotion state hierarchies are categorized and tagged by a lexical affective clustering algorithm. the complex emotions are compared to the traditional definitions of basic emotions in psychology and have been evaluated to be valid by kappa value in the experiment. Moreover we also have tagged the semantic orientation for the collected words.

关键词： Psychology Dictionaries Educational institutions Semantics Clustering algorithms Tagging Presses

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Reverse universal triple I method of (1,1,2) type for the Lukasiewicz implication

Reverse universal triple I method of (1,1,2) type for the Lu...

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IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Yiming Tang Fuji Ren Xiao Sun Yanxiang Chen Information and Communication Engineering Postdoctoral Research Station Hefei University of Technology Hefei China Institute of Technology and Science University of Tokushima Tokushima Japan School of Computer and Information Hefei University of Technology Hefei China

A new fuzzy reasoning method called the reverse universal triple I method of (1,1,2) type (reverse universal triple I method for short) is proposed and investigated by means of the famous Lukasiewicz implication, which contains the reverse triple I method as its special case. the reverse triple I principles are improved, and the optimal solutions of reverse universal triple I method are obtained for Fuzzy Modus Ponens (FMP) and Fuzzy Modus Tollens (FMT). Furthermore, it is found that the reverse universal triple I method has the reversibility property. Lastly, the reverse universal triple I method is further generalized to the alpha-reverse universal triple I method, and the related principles and optimal solutions are achieved.

关键词： Artificial intelligence

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Learning the weight of the query term from the relevance feedback

Learning the weight of the query term from the relevance fee...

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IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Bingqing Wang Yaqian Zhou Qi Zhang Xuanjing Huang Institute of Media Computing and Web Intelligence School of Computer Science and Technology Fudan University Shanghai China

We address the problem of assigning each query word an appropriate weight in the retrieval function. Term weight assignment is important, which depends on the relationship among the query words and also impacts the retrieval performance directly. However, various retrieval models can be adopted by the system, which requires different approaches to set term weight and those empirical settings can not ensure to improve the retrieval quality. We propose an unified approach for different retrieval functions to set a unique weight to each individual word. We explore the popular retrieval functions and propose to regard the retrieval function as a linear classification model, which is aimed to predicate the relevance of the document. thus the parameters in the learning model can be explained as the term weight in the retrieval model. For each query topic, we adopt the generative model and the discriminative model to estimate the term weight by taking the relevance feedback information as the training data. Our analysis gives more insight into the Rocchio's framework on relevance feedback, which can be taken as a special case in the generative model. Experimental results on the benchmark datasets show that by estimating proper weight to each query word, our approach can outperform the baseline methods of BM25 and obtain an equivalent performance with the probability language model.

关键词： Tuners

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A collocation based approach for prepositional phrase identification

A collocation based approach for prepositional phrase identi...

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IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Dongfeng Cai Ling Zhang Qiaoli Zhou Yue Zhao Knowledge Engineering Research Center Shenyang AeroSpace University Shenyang China Department of Information Systerms and Management Hiroshima Institute of Technology Japan

Prepositional phrase (PP) consists of two parts which are a preposition as the leading part and a word or phrase as the tail part. In accordance with this fact, this paper proposes a new approach for identifying PP. In this method, PP identification is transformed into the collocation identification of preposition itself and the right boundary word. the Cascaded Conditional Random Fields (CCRFs) is used in this approach. With the Penn Chinese Treebank 5.1 as our experiment corpus, the F 1 rises to 94.63%. this approach obtains breakthrough in this specific field as the current F 1 is about 8.6% higher than any publicly published paper.

关键词： Educational institutions Tagging

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HO2IEV: Heavyweight ontology based web information extraction technique for visionless users

HO2IEV: Heavyweight ontology based web information extractio...

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international conference on Networked Computing and advanced information Management (NCM)

作者： Ahmad C. Bukhari Abid Ali Fareedi Yong Gi. Kim Department of Computer Science Research Institute of Computer Science and Information Communication Gyeongsang National University Jinju Kyungnam South Korea School of Engineering Jönköping University Jonkoping Sweden

As the internet grows rapidly, millions of web pages are being added on a daily basis. the extraction of precise information is becoming more and more difficult as the volume of data on the internet increases. Several search engines and information fetching tools are available on the internet, all of which claim to provide the best crawling facilities. For the most part, these search engines are keyword based. this poses a problem for visually impaired people who want to get the full use from online resources available to other users. Visually impaired users require special aid to get along with any given computer system. Interface and content management are no exception, and special tools are required to facilitate the extraction of relevant information from the internet for visually impaired users. the HO 2 IEV (Heavyweight Ontology Based information Extraction for Visually impaired User) architecture provides a mechanism for highly precise information extraction using heavyweight ontology and built-in vocal command system for visually impaired internet users. Our prototype intelligent system not only integrates and communicates among different tools, such as voice command parsers, domain ontology extractors and short message engines, but also introduces an autonomous mechanism of information extraction (hereafter referred to as IE) using heavyweight ontology. In this paper we designed domain specific heavyweight ontology using OWL (web Ontology language) for ontology modeling and PAL (Protégé Axiom language) for axiom writing. We introduced a novel autonomous mechanism for IE by developing prototype software. A series of experiments were designed for the testing and analysis of the performance of heavyweight ontology in general, and our information extraction prototype specifically.

关键词： Ontologies Data mining Crawlers Internet web pages Prototypes Servers

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Unilateral semi-supervised learning of extended hidden vector state for Persian language Understanding

Unilateral semi-supervised learning of extended hidden vecto...

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IEEE international conference on Natural language processing and Knowledge Engineering (NLP-KE)

作者： Fattaneh Jabbari Hossein Sameti Mohammad Hadi Bokaei Speech Processing Laboratory Department of Computer Engineering Sharif University of Technology Tehran Iran

the key element of a spoken dialogue system is Spoken language Understanding (SLU) part. HVS and EHVS are two most popular statistical methods employed to implement the SLU part which need lightly annotated data. Since annotation is a time consuming, we present a novel semi-supervised learning for EHVS to reduce the human labeling effort using two different statistical classifiers, SVM and KNN. Experiments are done on a Persian corpus, the University information Kiosk corpus. the experimental results show improvements in performance of semi-supervised EHVS, trained by both labeled and unlabeled data, compared to EHVS trained by just initially labeled data. the performance of EHVS improves 13.41% in the case of SVM classifier and 5.16% in the case of KNN. this demonstrates effectiveness and feasibility of the proposed approach.

关键词： Support vector machines Semantics Hidden Markov models Training Accuracy Vectors Labeling

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