基于本体的语义分析过程与方法的研究应用*

为了提高信息化环境下语义分析能力,将本体引入语义分析。通过对典型本体构建方法的比较与综合,形成一种持续优化的本体构建方法,在此基础上进行概念分析、关系推理。进一步对比基于本体的语义分析和其它语义分析方法,指出基于本体的语义分析更具系统性、针对性,推理能力强。最后,将基于本体的语义分析应用到软件缺陷分析系统中。结果表明,它能够集成到原有系统中并有效进行关系推理和冲突识别。     

ROMANSEVAL: Results for Italian by SENSE

The paper describes SENSE, a word sense disambiguation system thatmakes use of different types of cues to infer the most likelysense of a word given its context. Architecture and functioning ofthe system are briefly illustrated. Results are given for theROMANSEVAL Italian test corpus of verbs.     

Using Semantic Classification Trees for WSD

This paper describes the evaluation of a WSD method withinSENSEVAL. This method is based on Semantic Classification Trees (SCTs)and short context dependencies between nouns and verbs. The trainingprocedure creates a binary tree for each word to be disambiguated. SCTsare easy to implement and yield some promising results. The integrationof linguistic knowledge could lead to substantial improvement.     

异质环境中可靠组播的代理结构

文章提出了一种适于异质网络环境的可靠组播代理结构。这种代理结构将网络环境相异的可靠组播会话分解成若干个网络环境相似的子会话,从而缓解了异质网络环境的异构问题。不仅如此,通过在可靠组播代理中引入应用程序的语义,实现了语义可靠性,即应用程序能够根据语义控制它所需要的数据可靠性。     

汉英翻译系统英文生成中选词模型的设计

本文描述了一种基于实例比较,辅以语义模式匹配的英文选词模型的设计。首先,我们讨论了汉英翻译系统英文生成中选词的重要性,然后比较了几种可能的选词策略并提出我们的选词模型,接着我们较详细地描述了生成词典的结构以及选词算法。文中,我们还简要介绍了我们所使用的语义知识资源——《知网》。     

义类自动标注方法的研究

句法分析不能满足汉语分析的需要,句法和语义相结合的分析方法适用于汉语分析。分析的基础要有一部语法语义词典。目前的机读词典多是语法词典,因而需要在语法词典中加入词的语义信息。《同义词词林》是一部较好的义类词典,但没有语法信息,可以《同义词词林》的分类体系对语法词典进行义类标注,得到语法语义词典。这一过程中有不一致的情况,特别地,对《同义词词林》中未收录的词就不能直接标注义类。本文采用《同义词词林》的分类体系,研究设计了一个汉语词自动义类标注算法,对北大《现代汉语语法信息词典》进行自动义类标注。实验结果较为满意,得到91%的准确率。     

Multi-Modal Dialog Scene Detection Using Hidden Markov Models for Content-Based Multimedia Indexing

A class of audio-visual data (fiction entertainment: movies, TV series) is segmented into scenes, which contain dialogs, using a novel hidden Markov model-based (HMM) method. Each shot is classified using both audio track (via classification of speech, silence and music) and visual content (face and location information). The result of this shot-based classification is an audio-visual token to be used by the HMM state diagram to achieve scene analysis. After simulations with circular and left-to-right HMM topologies, it is observed that both are performing very good with multi-modal inputs. Moreover, for circular topology, the comparisons between different training and observation sets show that audio and face information together gives the most consistent results among different observation sets.     

Metrics for shot boundary detection in digital video sequences

The detection of shot boundaries in video sequences is an important task for generating indexed video databases. This paper provides a comprehensive quantitative comparison of the metrics that have been applied to shot boundary detection. In addition, several standardized statistical tests that have not been applied to this problem, as well as three new metrics, are considered. A mathematical framework for quantitatively comparing metrics is supplied. Experimental results based on a video database containing 39,000 frames are included.     

句法评分和语义评分

本文使用句法评分和语义评分对句法分析和语义分析阶段进行消歧。句法评分和语义评分可以和传统的句法语义分析阶段结合起来,更有效地对自然语言进行分析。这是规则方法和统计方法相结合的一种行之有效的方法。对于句法语义评分,使用最大可能原理和K-best方法进行实验,实验结果表明:对于训练集和测试集,两种方法在考虑一个左上文或一个左右上下文时都比不考虑上下文的正确率高。所有训练集的正确率比测试集的正确率高。对于训练集,当语料规模越来越大时,正确率也逐渐在增加。     

基于神经网络的语义Web服务发现机制

面对目前互联网上动态多样的Web服务,如何发现最大符合用户请求的服务成为一个具有挑战性的课题。Web服务发现主要包括服务的匹配和服务的选择,虽然目前基于OWL-S和语义相似度的服务发现方法在一定程度上改进了传统的基于关键字和简单分类的服务发现机制,但也存在着在综合评价服务相似度时缺乏合理的权值分配的问题。因此,构建Web服务本体,利用神经网络合理分配各个相似度向量的权值,能够更好地发现与请求匹配的服务。