Classical negation in logic programs and disjunctive databases

An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic programs by including classical negation, in addition to negation-as-failure. The semantics of such extended programs is based on the method of stable models. The concept of a disjunctive database can be extended in a similar way. We show that some facts of commonsense knowledge can be represented by logic programs and disjunctive databases more easily when classical negation is available. Computationally, classical negation can be eliminated from extended programs by a simple preprocessor. Extended programs are identical to a special case of default theories in the sense of Reiter.     

User profiles and fuzzy logic for web retrieval issues

 We present a study of the role of user profiles using fuzzy logic in web retrieval processes. Flexibility for user interaction and for adaptation in profile construction becomes an important issue. We focus our study on user profiles, including creation, modification, storage, clustering and interpretation. We also consider the role of fuzzy logic and other soft computing techniques to improve user profiles. Extended profiles contain additional information related to the user that can be used to personalize and customize the retrieval process as well as the web site. Web mining processes can be carried out by means of fuzzy clustering of these extended profiles and fuzzy rule construction. Fuzzy inference can be used in order to modify queries and extract knowledge from profiles with marketing purposes within a web framework. An architecture of a portal that could support web mining technology is also presented.     

概率逻辑程序

1 引言最近几十年来,不确定性的管理在知识描述和推理中扮演着越来越重要的角色。为了处理不确定知识,人们提出了各种不同的形式化和方法论,其中大部分是直接或间接地基于概率论的。     

An XML-enabled data extraction toolkit for web sources

The amount of useful semi-structured data on the web continues to grow at a stunning pace. Often interesting web data are not in database systems but in HTML pages, XML pages, or text files. Data in these formats are not directly usable by standard SQL-like query processing engines that support sophisticated querying and reporting beyond keyword-based retrieval. Hence, the web users or applications need a smart way of extracting data from these web sources. One of the popular approaches is to write wrappers around the sources, either manually or with software assistance, to bring the web data within the reach of more sophisticated query tools and general mediator-based information integration systems. In this paper, we describe the methodology and the software development of an XML-enabled wrapper construction system—XWRAP for semi-automatic generation of wrapper programs. By XML-enabled we mean that the metadata about information content that are implicit in the original web pages will be extracted and encoded explicitly as XML tags in the wrapped documents. In addition, the query-based content filtering process is performed against the XML documents. The XWRAP wrapper generation framework has three distinct features. First, it explicitly separates tasks of building wrappers that are specific to a web source from the tasks that are repetitive for any source, and uses a component library to provide basic building blocks for wrapper programs. Second, it provides inductive learning algorithms that derive or discover wrapper patterns by reasoning about sample pages or sample specifications. Third and most importantly, we introduce and develop a two-phase code generation framework. The first phase utilizes an interactive interface facility to encode the source-specific metadata knowledge identified by individual wrapper developers as declarative information extraction rules. The second phase combines the information extraction rules generated at the first phase with the XWRAP component library to construct an executable wrapper program for the given web source.     

逻辑程序的事实维护

事实是逻辑程序的重要组成部分,事实维护影响着整个逻辑程序的一致性和完整性,并能够促进和完善规则维护。论文在分析了人工进行维护操作的弊端后,对事实维护中可能出现的情况进行分类分析,提出了事实维护系统的框架,重点描述了预警检测子系统所扮演的核心作用。     

Symmetric structure in logic programming

It is argued that some symmetric structure in logic programs could be taken into account when implementing semantics in logic programming. This may enhance the declarative ability or expressive power of the semantics. The work presented here may be seen as representative examples along this line. The focus is on the derivation of negative information and some other classic semantic issues. We first define a permutation group associated with a given logic program. Since usually the canonical models used to reflect the common sense or intended meaning are minimal or completed models of the program, we expose the relationships between minimal models and completed models of the original program and its so-called G-reduced form newly-derived via the permutation group defined. By means of this G-reduced form, we introduce a rule to assume negative information termed G-CWA, which is actually a generalization of the GCWA. We also develop the notions of G-definite, G-hierarchical and G-stratified logic programs,     

使用ILP学习Web信息提取规则

归纳逻辑编程(ILP)可以用于学习各种形式的逻辑规则,但在尝试用于学习Web页面的信息提取规则时存在格式不匹配问题.给出了系统结构的数据流图,重点分析了格式不匹配问题,提出了一种解决方案,主要包括规则的语法定义和动态生长方法.生成的规则结构清晰,可以用于从Web页面提取信息.     

处理指针相等关系不确定的指针逻辑

为类C小语言PointerC设计的指针逻辑是Hoare逻辑的一种扩展,可用来对指针程序进行精确的指针分析,以支持指针相等关系确定的程序的安全性验证.通过增加相等关系不确定的指针类型访问路径集合,可扩展这种指针逻辑,使得扩展后的指针逻辑可以应用于有向图等指针相等关系不确定的抽象数据结构上的指针程序性质　证明.     

一种关于Agent的模糊认知逻辑

由于经典逻辑不能表示模糊事实,而且Agent也不能利用经典逻辑的方法从模糊事实里获取知识,为了克服经典逻辑方面的不足,提出了一种关于Agent的模糊认知逻辑.首先,介绍了模糊认知逻辑和规则,该方法用数字来表示模糊事实,用模糊逻辑来获取知识.其次,引入了一种反向推理逻辑,利用该方法研究了条件和结论的相关性.最后,主要介绍Agent采用模糊认知逻辑获取知识的过程.     

一种用于指针程序安全性证明的指针逻辑

在高可信软件的各种性质中,安全性是被关注的重点,其中软件满足安全策略的证明方法是研究的热点之一.文中根据作者所设想的安全程序的设计和证明框架,为类C语言的一个子集设计了一个指针逻辑系统.该逻辑系统是Hoare逻辑系统的一种扩展,它用推理规则来表达每一种语句引起指针信息的变化情况.它可用来对指针程序进行精确的指针分析,所获得的信息用来证明指针程序是否满足定型规则的附加条件,以支持程序的安全性验证.该逻辑系统也可用来证明指针程序的其它性质.     

Declarative paradigm of test coverage

Two facts about declarative programming prevent the application of conventional testing methods. First, the classical test coverage measures such as statement, branch or path coverage, cannot be used, since in declarative programs no control flow notion exists. Second, there is no widely accepted language available for formal specification, since predicate logic, which is the most common formalism for declarative programming, is already a very high-level abstract language. This paper presents a new approach exending previous work by the authors on test input generation for declarative programs. For this purpose, the existing program instrumentation notion is extended and a new logic coverage measure is introduced. The approach is mathematically formalized and the goal of achieving 100% program logic coverage controls the automatic test input generation. The method is depicted by means of logic programming; the results are, however, generally applicable. Finally, the concepts introduced have been used practically within a test environment. © 1998 John Wiley & Sons, Ltd.     

基于扩展DOM树的Web页面信息抽取

随着Internet的发展,Web页面提供的信息量日益增长,信息的密集程度也不断增强.多数Web页面包含多个信息块,它们布局紧凑,在HTML语法上具有类似的模式.针对含有多信息块的Web页面,提出一种信息抽取的方法:首先创建扩展的DOM(Document Object Model)树,将页面抽取成离散的信息条;然后根据扩展DOM树的层次结构,并结合必要的视觉特性和语义信息对离散化的信息条重新整合;最后确定包含信息块的子树,深度遍历DOM树实现信息抽取.该算法能对多信息块的Web页面进行信息抽取.     

Exploiting link structure for web page genre identification

As the World Wide Web develops at an unprecedented pace, identifying web page genre has recently attracted increasing attention because of its importance in web search. A common approach for identifying genre is to use textual features that can be extracted directly from a web page, that is, On-Page features. The extracted features are subsequently inputted into a machine learning algorithm that will perform classification. However, these approaches may be ineffective when the web page contains limited textual information (e.g., the page is full of images). In this study, we address genre identification of web pages under the aforementioned situation. We propose a framework that uses On-Page features while simultaneously considering information in neighboring pages, that is, the pages that are connected to the original page by backward and forward links. We first introduce a graph-based model called GenreSim, which selects an appropriate set of neighboring pages. We then construct a multiple classifier combination module that utilizes information from the selected neighboring pages and On-Page features to improve performance in genre identification. Experiments are conducted on well-known corpora, and favorable results indicate that our proposed framework is effective, particularly in identifying web pages with limited textual information.     

Towards a contingency approach with whitelist- and blacklist-based anti-phishing applications: what do usability tests indicate?

In web browsers, a variety of anti-phishing tools and technologies are available to assist users to identify phishing attempts and potentially harmful pages. Such anti-phishing tools and technologies provide Internet users with essential information, such as warnings of spoofed pages. To determine how well users are able to recognise and identify phishing web pages with anti-phishing tools, we designed and conducted usability tests for two types of phishing-detection applications: blacklist-based and whitelist-based anti-phishing toolbars. The research results mainly indicate no significant performance differences between the application types. We also observed that, in many web browsing cases, a significant amount of useful and practical information for users is absent, such as information explaining professional web page security certificates. Such certificates are crucial in ensuring user privacy and protection. We also found other deficiencies in web identities in web pages and web browsers that present challenges to the design of anti-phishing toolbars. These challenges will require more professional, illustrative, instructional, and reliable information for users to facilitate user verification of the authenticity of web pages and their content.     

On Finding Templates on Web Collections

Templates are pieces of HTML code common to a set of web pages usually adopted by content providers to enhance the uniformity of layout and navigation of theirs Web sites. They are usually generated using authoring/publishing tools or by programs that build HTML pages to publish content from a database. In spite of their usefulness, the content of templates can negatively affect the quality of results produced by systems that automatically process information available in web sites, such as search engines, clustering and automatic categorization programs. Further, the information available in templates is redundant and thus processing and storing such information just once for a set of pages may save computational resources. In this paper, we present and evaluate methods for detecting templates considering a scenario where multiple templates can be found in a collection of Web pages. Most of previous work have studied template detection algorithms in a scenario where the collection has just a single template. The scenario with multiple templates is more realistic and, as it is discussed here, it raises important questions that may require extensions and adjustments in previously proposed template detection algorithms. We show how to apply and evaluate two template detection algorithms in this scenario, creating solutions for detecting multiple templates. The methods studied partitions the input collection into clusters that contain common HTML paths and share a high number of HTML nodes and then apply a single-template detection procedure over each cluster. We also propose a new algorithm for single template detection based on a restricted form of bottom-up tree-mapping that requires only small set of pages to correctly identify a template and which has a worst-case linear complexity. Our experimental results over a representative set of Web pages show that our approach is efficient and scalable while obtaining accurate results.     

基于主题的智能Web信息采集系统的研究与实现

研究并实现了一个基于主题的智能信息采集系统IFWC,该系统以全信息理论为支撑,吸收传统向量空间模型的思想,采用基于概念的向量空间模型,从词的语义层次对文本进行主题相关性分析;使用扩展元数据的语义相关性判定算法,对页面内的URL进行主题相关性预测。实验证明,该系统采集速度快,采集下来的页面精度高。     

线性递归Da taL og 程序优化算法

提出了线性齐次ＤａｔａＬｏｇ逻辑程序的概念,并为该类程序设计了一个优化的求解算法。在此基础上提出了求解一般线性ＤａｔａＬｏｇ程序的优化算法,该算法利用带有的约束条件的递归调用方法,将线性ＤａｔａＬｏｇ程序求解问题变换成齐次程序的求解问题。算法简单,易于实现,可应用于任何线性ＤａｔａＬｏｇ程序的求解。     

具有两种否定的描述逻辑系统MALC

否定信息在知识表示和推理中具有非常重要的作用。随着信息科学的发展,大量的事实表明：信息科学的许多领域需要区分概念的矛盾否定和对立否定。描述逻辑作为一阶谓词逻辑的可判定子集,并没有区分概念的矛盾否定与对立否定。本文将模糊否定词～和对立否定词 引入描述逻辑ALC,建立了一个扩展的描述逻辑系统MALC,使其具有处理模模糊知识的能力。同时,文章给出了基于中介无穷值语义模型的语义解释;在推理机制上,给出了可满足性的定义和可满足性的Tableau算法。