Language and Space: a two-level semantic approach based on principles of ontological engineering

An increasing number of applications for dialogue systems presuppose an ability to deal appropriately with space. Dialogues with assistance systems, intelligent mobility devices and navigation systems all commonly involve the use of spatial language. For smooth interaction, this spatial language cannot be interpreted ‘in the abstract’—it must instead be related directly to a user’s physical location, orientation, goals and needs and be embedded appropriately in a system’s interaction. This is far from straightforward. The situated interpretation of natural language concerning space, spatial relationships and spatial activities represents an unsolved challenge at this time. Despite extensive work on spatial language involving many disciplines, there are no generally accepted accounts that provide support for the kind of flexible language use observed in real human-human spatial dialogues. In this paper, I review some recent approaches to the semantics for natural language expressions concerning space in order to motivate a two-level semantic-based approach to the interpretation of spatial language. This draws on a new combination of natural language processing and principles of ontological engineering and stands as a foundation for more sophisticated and natural dialogue system behavior where spatial information is involved.     

Semantic Web search based on ontological conjunctive queries

Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, called Serene, which allows for a semantic processing of Web search queries, and for evaluating complex Web search queries that involve reasoning over the Web. More specifically, we first add ontological structure and semantics to Web pages, which then allows for both attaching a meaning to Web search queries and Web pages, and for formulating and processing ontology-based complex Web search queries (i.e., conjunctive queries) that involve reasoning over the Web. Here, we assume the existence of an underlying ontology (in a lightweight ontology language) relative to which Web pages are annotated and Web search queries are formulated. Depending on whether we use a general or a specialized ontology, we thus obtain a general or a vertical Semantic Web search interface, respectively. That is, we are actually mapping the Web into an ontological knowledge base, which then allows for Semantic Web search relative to the underlying ontology. The latter is then realized by reduction to standard Web search on standard Web pages and logically completed ontological annotations. That is, standard Web search engines are used as the main inference motor for ontology-based Semantic Web search. We develop the formal model behind this approach and also provide an implementation in desktop search. Furthermore, we report on extensive experiments, including an implemented Semantic Web search on the Internet Movie Database.     

汉语中方位参考点恢复研究

方位参考点恢复是自然语言空间语义理解中十分重要问题 .方位参考点恢复是在篇章中找方位词的参考点并补充上,得到完整的空间表达式 .目前,自然语言处理技术大多面向句子级,导致省略参考点空间表达式独立出现,使空间语义理解困难 .方位参考点恢复无疑可以解决类似问题 .在此提出基于有限知识的方位参考点恢复方法 .在句法分析基础上,以知网为常识库,结合有限知识识别空间表达式以及恢复方位参考点 .实验结果表明该方法比较令人满意 .     

Ontology and rule-based natural language processing approach for interpreting textual regulations on underground utility infrastructure

The nation’s massive underground utility infrastructure must comply with a multitude of regulations. The regulatory compliance checking of underground utilities requires an objective and consistent interpretation of the regulations. However, utility regulations contain a variety of domain-specific terms and numerous spatial constraints regarding the location and clearance of underground utilities. It is challenging for the interpreters to understand both the domain and spatial semantics in utility regulations. To address the challenge, this paper adopts an ontology and rule-based Natural Language Processing (NLP) framework to automate the interpretation of utility regulations – the extraction of regulatory information and the subsequent transformation into logic clauses. Two new ontologies have been developed. The urban product ontology (UPO) is domain-specific to model domain concepts and capture domain semantics on top of heterogeneous terminologies in utility regulations. The spatial ontology (SO) consists of two layers of semantics – linguistic spatial expressions and formal spatial relations – for better understanding the spatial language in utility regulations. Pattern-matching rules defined on syntactic features (captured using common NLP techniques) and semantic features (captured using ontologies) were encoded for information extraction. The extracted information elements were then mapped to their semantic correspondences via ontologies and finally transformed into deontic logic (DL) clauses to achieve the semantic and logical formalization. The approach was tested on the spatial configuration-related requirements in utility accommodation policies. Results show it achieves a 98.2% precision and a 94.7% recall in information extraction, a 94.4% precision and a 90.1% recall in semantic formalization, and an 83% accuracy in logical formalization.     

基于地理本体的空间数据库概念建模

针对用E-R模型建立空间数据库概念模型存在的不足之处,将本体论的思想和方法引入到地理信息领域。讨论了地理本体的意义及其表达语言。阐述了空间E-R模型的特点,分析了地理本体和空间E-R模型之间的关系。提出了以地理本体为语义基础设计空间ER模型的思想,并用扩展OWL表示的灌溉本体为例,介绍了从地理本体出发,设计空间E-R模型来建立空间数据库概念模型的方法。     

基于光流法的不良视频检测算法

针对用E-R模型建立空间数据库概念模型存在的不足之处,将本体论的思想和方法引入到地理信息领域.讨论了地理本体的意义及其表达语言.阐述了空间E-R模型的特点,分析了地理本体和空间E-R模型之间的关系.提出了以地理本体为语义基础设计空间ER模型的思想,并用扩展OWL表示的灌溉本体为例,介绍了从地理本体出发,设计空间E-R模型来建立空间数据库概念模型的方法.     

Algebraic semantics for natural language: some philosophy, some applications

Information processing, when performed by an intelligent agent, draws on a wide array of knowledge sources. Among them are world knowledge, situation knowledge, conceptual knowledge and linguistic knowledge. The focus in this paper will be on the semantic knowledge which is part of the general linguistic competence of any speaker of a natural language (NL).In particular, this knowledge contains ways of organizing the linguistic ontology, i.e. the collection of heterogeneous entities that make up the domain of discourse. The representation language that is proposed here to model this knowledge stresses the structural properties of the ontology. This approach has been persued under the name of algebraic semantics.The paper starts out by explaining the term "algebraic semantics" as it is used in logic. Two senses of "algebraic" are distinguished that are called here "conceptual" and "structural". These two senses of the algebraic method are then applied to NL semantics. The conceptual part is realized by the method of structuring the domains of linguistic ontology in various ways. Thus plural entities are recognized along with mass entities and events. The common outlook here is mereological or lattice-theoretical. Some applications to the study of plurals are given that are to show the usefulness of the algebraic approach. Finally, the ontology of plurals is addressed, and comments are made on some relevant discussion of mereology in recent philosophical work. In sum, it is contended that the algebraic perspective while being of interest in semantics and philosophy proper, also fits both the spirit and the practice of much work that has been done in the Artificial Intelligence (AI) field of knowledge representation.     

A formally specified ontology management API as a registry for ubiquitous computing systems

Recently, several standards have emerged for ontology markup languages that can be used to formalize all kinds of knowledge. However, there are no widely accepted standards yet that define APIs to manage ontological data. Processing ontological information still suffers from the heterogeneity imposed by the plethora of available ontology management systems. Moreover, ubiquitous computing environments usually comprise software components written in a variety of different programming languages, which makes it particularly difficult to establish a common ontology management API with programming language agnostic semantics. We implemented an ontological Knowledge Base Server, which can expose the functionality of arbitrary off-the-shelf ontology management systems via a formally specified and well defined API. A case study was carried out in order to demonstrate the feasibility of our approach to use a formally specified ontology management API to implement a registry for ubiquitous computing systems.     

短语结构制导的范畴表达式演算

对于语言表达式的组成成分及它们间的关系的刻画,目前大多数语法研究都着重在句法层面,而本文的范畴表达式演算理论则着重在语义层面。我们首先考察了完全表达式与不完全表达式、句法类型与语义类型、继承、顺序、提取、并列等若干重要的语言现象以及各种语法理论对这些现象的解释,然后提出范畴表达式的形式化定义,分析了句法层面的形式约束对语义层面的内容组织的制导作用,并且用典型的语言例子直观的说明了如何利用短语结构制导,进行范畴表达式的演算。这种机制可形式化、可验证,能很好的捕捉语言的组成成分及它们间的相互关系,揭示一个句子所说的内容。     

Algebraic tools for language processing

A language space provides a unified framework to deal with the properties of language constructs by associating them with their specification rules. The concrete syntax is represented by segments of the language space. The semantics is given by derived operations of the algebras where these constructs are interpreted by the processing tools operating on the language space. We examine in this paper only processing tools that collect syntactic information over the language space. Tools involved in semantics processing such as translators and interpreters are also integrated in the language space but are not discussed here.     

A framework for linguistic logic programming

Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real‐world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD‐style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc.     

计算语义合成性综述

随着自然语言处理技术的飞速发展,单纯在语法层上的研究已经不能解决目前的问题,语义层的研究逐渐成为热点。计算语义合成性作为语义学的关键部分,受到了诸多研究人员的关注。计算语义合成性的研究方法可以分为两大类: 语言学方法和分布式方法。该文详细介绍了它们各自具有代表性的工作,着重阐述了近年来使用广泛的深度学习方法在计算语义合成性研究中的应用,并对这两种方法进行了比较;然后对计算语义合成性在情感分析以及机器翻译中的应用做了细致分析;最后,展望了计算语义合成性未来的研究趋势。     

基于WordNet和自然语言处理技术的半自动领域本体构建

现有的大多数本体都是通过手工构建的,然而,本体的构建是一项非常费时费力的过程,近年来有关如何半自动地构建领域本体的研究越来越多。本文提出了一种基于WordNet和自然语言处理技术的领域本体半自动构建方法,该方法能够大大提高本体的构建效率,并且一定程度上能够保证结果本体的质量。实验表明,本文的方法在一定程度上令本体的生成过程实现自动化。     

Natural language understanding and Montague grammar1, 2

This paper reevaluates some of the contributions of Montague grammar in view of the increasing importance of computational considerations in linguistic theory and the demand for linguistic theories that can provide support in the design of natural language systems. It also considers Montague grammar in relation to work on lexical semantics and semantic nets. In this perspective the techniques of Montague grammar for systematically linking syntactic form and a model-theoretic semantics emerge as the most significant feature of the theory, while a number of the specific semantic assumptions recede in importance. Yet, with different ways of thinking about the structure mapping between levels of linguistic form and interpretations (e.g., constraint systems), we can also implement this connection using different techniques from what Montague had at his disposal.     

Ontology-based computational intelligent multi-agent and its application to CMMI assessment

This study presents an ontology-based computational intelligent multi-agent system for Capability Maturity Model Integration (CMMI) assessment. An ontology model is developed to represent the CMMI domain knowledge that will be adopted by the computational intelligent multi-agent. The CMMI ontology is predefined by domain experts, and created by the ontology generating system. The computational intelligent multi-agent comprises a natural language processing agent, an ontological reasoning agent and a summary agent. The multi-agent deals with the evaluation reports from the natural language processing agent, infers the term relation strength between the ontology and the evaluation report, and then summarizes the main sentences of the evaluation report. The summary reports are meanwhile transmitted back to the domain expert, which makes the domain expert further adjust the CMMI ontology. Experimental results indicate that the ontology-based computational intelligent multi-agent can effectively summarize the evaluation reports for the CMMI assessment.     

Incorporating linguistic structure into maximum entropy language models

In statistical language models,how to integrate diverse linguistic knowledge in a general framework for long-distance dependencies is a challenging issue,In this paper,an improved language model incorporating linguistic structure into maximum entropy framework is presented.The poposed model combines trigram with the structure knowledge of base phrase in which trigram is used to capture the local relation between words.while the structure knowledge of base phrase is considered to represent the long-distance relations between syntactical structures.The knowledge of syntax,semantics and vocabulary is is integrated into the maximum entropy framework,Experimental results show that the proposed model improves by 24% for language model perplexity and increases about3% for sign language recognition rate compared with the trigram model.     

本体论研究综述

起源于哲学的本体论(ontology)在信息科学领域受到广泛关注，其重要性已在许多方面表现出来，如知识工程、数据库设计和集成、信息检索与获取、软件工程、自然语言处理等．尤其是本体论在Web上的应用导致了语义Web的诞生，有望解决Web信息共享时的语义问题，实现世界范围的知识级信息集成．综述计算机科学中本体论的研究和应用现状，主要内容包括：本体论的起源和发展，本体论的定义，本体论的描述语言以及构建方法论，本体论与语义Web，以及本体论的应用等．     

一种提高本体映射精确度的方法

针对本体映射精确度不高的问题,提出一种基于自然语言处理的本体映射结果校验方法。对复合词进行启发式处理,分析WordNet词库中词汇所对应注释的语法树,提取与参考本体和目标本体相关的词汇,对已有的本体映射结果进行校验。实验结果表明,该方法能有效提高本体映射的精确度。