跨文化交际视域下中日口语语体对比研究

口语语体在外语学习中有着重要的意义。该论文从对日汉语和日语学习角度出发,重点论述两点意义:一是中日文语言形态不同,深入认识口语语体能准确掌握各场合的用语方法;二是中日社会文化背景不同,深入认识口语语体能理解承载语言的文化,避免因文化认知缺乏导致的沟通误解。论文具体通过口语语体中的中日文近义词、省略表达、文化背景3个方面的对比研究揭示跨文化交际视域下中日口语语体的思维规律,以期应用于外语教育更好地向世界讲好中国故事。

词汇学知识在英语阅读中的应用探讨

从英语阅读教学的实际出发,拟从"把握""第三词汇"、"注意英语词汇的转换"、"捕捉语义与语体及搭配的关系"、"时刻想到语言在不断地发展"五个方面进行探讨,说明大学生如果能够了解或掌握一些英语词汇学知识,对于大幅度提高英语阅读能力将发挥重要的作用。

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

Design and implementation of semantic search engine Smartch

To integrate reasoning and text retrieval, the architecture of a semantic search engine which includes several kinds of queries is proposed, and the semantic search engine Smartch is designed and implemented. Based on a logical reasoning process and a graphic user-defined process, Smartch provides four kinds of search services. They are basic search, concept search, graphic user-defined query and association relationship search. The experimental results show that compared with the traditional search engine, the recall and precision of Smartch are improved. Graphic user-defined queries can accurately locate the information of user needs. Association relationship search can find complicated relationships between concepts. Smartch can perform some intelligent functions based on ontology inference.

Efficient semantic web service matching using common ontology

To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.

Context query and association discovery for collaborative environment

A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.

An Explorative Research into the Factors Affecting Chinese Students＇ Retention and Application of English New Words

Vocabulary has a direct impact on people＇s communication competence. A good mastery of an English word covers its pronunciation, spelling, part of speech, meaning and application. This article will focus only on factors affecting the retention and application of a word from the perspective of semantic disparities, different defining angles in English and Chinese, emotional coloring and styles, morphological changes, and collocation. The author hopes that this article will be able to provide some insights into vocabulary teaching.

Orthographic,Semantic,and Contextual Influences on Initial Processing and Learning of Novel Words During Reading:Evidence From Eye Movements

This study investigates how orthographic,semantic and contextual variables—including word length,concreteness,and contextual support—impact on the processing and learning of new words in a second language(L2)when first encountered during reading.Students learning English as a foreign language(EFL)were recruited to read sentences for comprehension,embedded with unfamiliar L2 words that occurred once.Immediately after this,they received a form recognition test,a meaning recall test,and a meaning recognition test.Eye-movement data showed significant effects of word length on both early and late processing of novel words,along with effects of concreteness only on late-processing eye-tracking measures.Informative contexts were read slower than neutral contexts,yet contextual support did not show any direct influence on the processing of novel words.Interestingly,initial learning of abstract words was better than concrete words in terms of form and meaning recognition.Attentional processing of novel L2 words,operationalized by total reading time,positively predicted L2 learners’recognition of new orthographic forms.Taken together,these results suggest:1)orthographic,semantic and contextual factors play distinct roles for initial processing and learning of novel words;2)online processing of novel words contributes to L2 learners’initial knowledge of unfamiliar lexical items acquired from reading.

Semantics-Based Compliance An a lys is o f N e two rk S e cu rity Policy Hie ra rch ie s

Network security policy and the automated refinement of its hierarchies aims to simplify the administration of security services in complex network environments. The semantic gap between the policy hierarchies reflects the validity of the policy hierarchies yielded by the automated policy refinement process. However, little attention has been paid to the evaluation of the compliance between the derived lower level policy and the higher level policy. We present an ontology based on Ontology Web Language （OWL） to describe the semantics of security policy and their implementation. We also propose a method of estimating the semantic similarity between a given

An OWL-based WordNet lexical ontology

This paper discribes a data representation for WordNet 2.1 based on Web Ontology Language (OWL). The main components of WordNet database are transformed as classes in OWL, and the relations between synsets or lexcial words are transformed as OWL properties. Our conversion is based on the data file of WordNet instead of the Prolog database. This work can be used to enrich the work in progress of standard conversion of WordNet to the RDF/OWL representation at W3C.

Applying a semantic information Petri Net modeling method to AUV systems design

This paper informally introduces colored object-oriented Petri Nets(COOPN) with the application of the AUV system.According to the characteristic of the AUV system's running environment,the object-oriented method is used in this paper not only to dispart system modules but also construct the refined running model of AUV system,then the colored Petri Net method is used to establish hierarchically detailed model in order to get the performance analyzing information of the system.After analyzing the model implementation,the errors of architecture designing and function realization can be found.If the errors can be modified on time,the experiment time in the pool can be reduced and the cost can be saved.

A Q-based integrating interaction framework system for multi-agent coordination

Interaction is one of the crucial features of multl-agent systems, in which there are two kinds of interaction： agent-to-agent and human-to-agent. In order to unify the two kinds of interaction while designing multi-agent systems, this paper introduces Q language-a scenario description language for designing interaction among agents and humans. Based on Q, we propose an integrating interaction framework system for multi-agent coordination, in which Q scenarios are used to uniformly describe both kinds of interactions. Being in accordance to the characteristics of Q language, the Q-based framework makes the interaction process open and easily understood by the users. Additionally, it makes specific applications of multi-agent systems easy to be established by application designers. By applying agent negotiation in agent-mediated e-commerce and agent cooperation in interoperable information query on the Semantic Web, we illustrate how the presented framework for multi-agent coordination is implemented in concrete applications. At the same time, these two different applications also demonstrate usability of the presented framework and verify validity of Q language.

An Edge-Based Approach for Semantic Matchmaking of Service Capabilities

Semantic Web Services is an emerging technology that promises to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Semantic matchmaking plays a vital role in the automated and dynamic discovery process of Semantic Web Services and consists in measuring the semantic distance between a requested service and an advertised one. In this paper, an innovative approach to effectively compute the semantic distance between Ontology Web Language for Services （OWL-S） annotated services is proposed. First, an edge-based method for measuring the semantic distance between Web Ontology Language （OWL） concepts is presented. Then, a comparison of the proposed measure and the one presented in a recent related work is made in order to show that our method is more efficient and fine-grained. Finally, some equations to compute semantic matchmaking of service capabilities, which are expressed in terms of inputs and outputs, are presented.

Video Concept Detection Based on Multiple Features and Classifiers Fusion

The rapid growth of multimedia content necessitates powerful technologies to filter, classify, index and retrieve video documents more efficiently. However, the essential bottleneck of image and video analysis is the problem of semantic gap that low level features extracted by computers always fail to coincide with high-level concepts interpreted by humans. In this paper, we present a generic scheme for the detection video semantic concepts based on multiple visual features machine learning. Various global and local low-level visual features are systelrtically investigated, and kernelbased learning method equips the concept detection system to explore the potential of these features. Then we combine the different features and sub-systen on both classifier-level and kernel-level fusion that contribute to a more robust system Our proposed system is tested on the TRECVID dataset. The resulted Mean Average Precision （MAP） score is rmch better than the benchmark perforrmnce, which proves that our concepts detection engine develops a generic model and perforrrs well on both object and scene type concepts.