基于后控技术的中小型竞争情报系统自动标引研究

为企业设计构建竞争情报系统对支持企业做出适时恰当的决策起着重要作用.基于此.为中小企业设计了一种基于Internet的竞争情报系统,为企业提供智能检索、个性化的服务等;为了提高系统的检索效率,改善系统功能,通过分析后控词表与本体之间的关系,提出一种利用本体编制后控词表的方法.对竞争情报系统中的文献进行检索效果比较,表明采用后控制的文献检索其查全率有显著的提高.     

基于PMI-IR的联想词表构造方法研究

通过对大规模查询日志进行挖掘分析进而提高检索的准确率一直是信息检索领域的热点问题。文章提出一种基于PMI-IR（逐点互信息方法）的联想词表构造方法。该方法利用序列模式挖掘算法扫描大规模用户查询日志,获取共现频次超过某一阈值的词组合,进行聚类获取候选同义词集,然后依次计算词wordA与每个候选词的相似度,选择相似度高于某一阈值的词作为词wordA的联想词集,最后形成联想词表。实验表明,借助该方法得到的联想词表进行扩展查询提高了检索的准确率。     

基于相似性叙词表的模糊集合模型

传统的模糊集合模型基于词词关联矩阵来实现模糊检索,词词关联矩阵只考虑语词在文献内部的同时出现.本文提出了一个基于相似性叙词表的模糊集合模型,考虑语词与查询之间的相似性,并将查询扩展包含在此模型中,从而在一定程度上提高了检索性能.     

模糊描述逻辑知识库查询蕴涵的判定方法

大规模领域本体的快速发展对语义Web领域的数据访问提出了更高的要求,而基本的本体推理服务已不能满足数据密集型应用中处理复杂查询(主要是合取查询)的迫切需要.为此,大量的研究工作集中在本体和描述逻辑知识库合取查询算法的设计实现上,并开发出了很多知识库存储和查询的实用工具.近来模糊本体和模糊描述逻辑的研究,特别是它们在处理语义Web中模糊信息方面,得到了广泛关注.文中重点研究了模糊SH这一族极富表达能力的描述逻辑知识库的合取查询问题,提出了相应的基于推演表的算法,证明了算法对于f-SHOIQ的真子逻辑的可靠性、完备性和可终止性.证明了算法对于f-SHOIQ是可靠的,并分析了导致算法不可终止的原因.对于该问题的数据复杂度,证明了当查询中不存在传递角色时其严格的CONP上限.对于联合复杂度,汪明了算法关于知识库和查询大小的CO3NEXPTIME时间复杂度上限.     

基于多领域本体的智能查询系统模型

提出了一种基于多领域本体的智能查询系统的形式化模型,并且对系统及其特点进行了详细分析。该模型引入本体层来对知识库系统中的语义和信息内容进行描述,充分体现了用户查询中的语义信息,既方便用户进行查询,又增加了查询结果的相关性。同时,系统能够及时反映知识库的动态变化,简化了单一的全局本体所导致的一致性及效率问题。     

智能装配机器人机械零件知识库的自动建立

为了实现智能装配机器人能够模拟人装配机械零件,系统应包含有关装配所必需的知识.利用这些知识,机器人自动编制装配工艺规程.并自动安排机器人的一系列控制命令.机械零件知识库是基于知识的智能装配机器人规划系统中不可缺少的知识.本文介绍了由机器人的视觉系统摄入机械零件图纸后,如何由摄入的二值化图形自动建立机械零件知识库.     

知识库查询方法研究

随着现代信息技术的发展,网络知识库已成为人们进行知识共享和交流的平台。随着Wiki技术的出现,使人们对知识的需求量逐步提高,传统知识库出现了成本高、更新慢、查询效率低的现象。本文通过分析Wiki知识库、提出Wiki知识库模型搭建的方法,分析了Wiki知识库查询方法及应用内容,进一步对Wiki知识库进行了深入研究。     

知识库查询方法研究

随着现代信息技术的发展,网络知识库已成为人们进行知识共享和交流的平台。随着Wiki技术的出现,使人们对知识的需求量逐步提高,传统知识库出现了成本高、更新慢、查询效率低的现象。本文通过分析Wiki知识库、提出Wiki知识库模型搭建的方法,分析了Wiki知识库查询方法及应用内容,进一步对Wiki知识库进行了深入研究。     

基于网络知识库与通用搜索引擎的查询词扩展方法

对查询词进行扩展是为了进一步理解用户的搜索意图,使得搜索引擎返回更加准确的信息。已有的方法主要研究如何寻找与查询词相似的词,然而相似的户的词并一定能真正反映用意图。从网络知识库中抽取查询词的待扩展词,并利用通用搜索引擎对待扩展词进行排序,这样的查询词扩展方法充分利用了网络群体智慧,使得扩展词更加贴近用户的搜索期望。通过进行实验对比发现,该方法有较好的结果。     

扩展知识图谱上的实体关系检索

现有文本数据集上的实体搜索和自然语言查询方法无法处理需要将分散在不同文档中的信息碎片链接起来以满足有复杂实体关系的查询,而知识库上的查询虽然可以表示实体间的复杂关系,但由于知识库的异构性和不完全性,通常查全率较低。针对这些问题,提出使用文本数据集对知识库进行扩展,并设计相应的含文本短语的三元组模式查询以支持对知识库和文本数据的统一查询。在此基础上,设计并实现了查询放松机制和对结果元组的评分模型,并给出了高效的查询处理方法。使用YAGO、ClueWeb09和其上的FACC1数据集,在三个不同的查询测试集(实体检索、实体关系检索和复杂的实体关系查询)上与两个典型相关工作作了比较。实验结果显示,扩展知识图谱上使用查询放松规则的实体关系检索系统的检索效果大大超出了其他系统,具体地在三个查询测试集上,其平均正确率均值(MAP)比其他系统分别提升了27%、37%和64%以上。     

A fuzzy knowledge-based system for intelligent retrieval

For many knowledge-intensive applications, it is important to develop an environment that permits flexible modeling and fuzzy querying of complex data and knowledge including uncertainty. With such an environment, one can have intelligent retrieval of information and knowledge, which has become a critical requirement for those applications. In this paper, we introduce a fuzzy knowledge-based (FKB) system along with the model and the inference mechanism. The inference mechanism is based on the extension of the Rete algorithm to handle fuzziness using a similarity-based approach. The proposed FKB system is used in the intelligent fuzzy object-oriented database (IFOOD) environment, in which a fuzzy object-oriented database is used to handle large scale of complex data while the FKB system is used to handle knowledge of the application domain. Both the fuzzy object-oriented database system and the fuzzy knowledge-based system are based on the object-oriented concepts to eliminate data type mismatches. The aim of this paper is mainly to introduce the FKB system of the IFOOD environment.     

Intelligent query answering by knowledge discovery techniques

Knowledge discovery facilitates querying database knowledge and intelligent query answering in database systems. We investigate the application of discovered knowledge, concept hierarchies, and knowledge discovery tools for intelligent query answering in database systems. A knowledge-rich data model is constructed to incorporate discovered knowledge and knowledge discovery tools. Queries are classified into data queries and knowledge queries. Both types of queries can be answered directly by simple retrieval or intelligently by analyzing the intent of query and providing generalized, neighborhood or associated information using stored or discovered knowledge. Techniques have been developed for intelligent query answering using discovered knowledge and/or knowledge discovery tools, which includes generalization, data summarization, concept clustering, rule discovery, query rewriting, deduction, lazy evaluation, application of multiple-layered databases, etc. Our study shows that knowledge discovery substantially broadens the spectrum of intelligent query answering and may have deep implications on query answering in data- and knowledge-base systems     

Summarizing Vocabularies in the Global Semantic Web

In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage. With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies. Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipa...     

Improving interoperability using vocabulary linked data

The concept of Linked Data has been an emerging theme within the computing and digital heritage areas in recent years. The growth and scale of Linked Data has underlined the need for greater commonality in concept referencing, to avoid local redefinition and duplication of reference resources. Achieving domain-wide agreement on common vocabularies would be an unreasonable expectation; however, datasets often already have local vocabulary resources defined, and so the prospects for large-scale interoperability can be substantially improved by creating alignment links from these local vocabularies out to common external reference resources. The ARIADNE project is undertaking large-scale integration of archaeology dataset metadata records, to create a cross-searchable research repository resource. Key to enabling this cross search will be the ‘subject’ metadata originating from multiple data providers, containing terms from multiple multilingual controlled vocabularies. This paper discusses various aspects of vocabulary mapping. Experience from the previous SENESCHAL project in the publication of controlled vocabularies as Linked Open Data is discussed, emphasizing the importance of unique URI identifiers for vocabulary concepts. There is a need to align legacy indexing data to the uniquely defined concepts and examples are discussed of SENESCHAL data alignment work. A case study for the ARIADNE project presents work on mapping between vocabularies, based on the Getty Art and Architecture Thesaurus as a central hub and employing an interactive vocabulary mapping tool developed for the project, which generates SKOS mapping relationships in JSON and other formats. The potential use of such vocabulary mappings to assist cross search over archaeological datasets from different countries is illustrated in a pilot experiment. The results demonstrate the enhanced opportunities for interoperability and cross searching that the approach offers.     

An interlingua for electronic interchange of medical information: Using frames to map between clinical vocabularies

The proliferation of medical knowledge has led to the development of extensive dictionaries for electronically accessing information resources. The task of standardizing terminology used for electronic hospital records and for knowledge bases for medical expert systems and indexing the medical literature cannot easily be met by developing a single, monolithic “official” medical vocabulary. Developing a monolithic vocabulary would require a massive effort, and its existence would not guarantee its use by third-party payors, by practicing clinicians, or by developers of electronic medical information systems. Recognizing this, the National Library of Medicine (NLM) has begun to develop the Unified Medical Language System (UMLS) as a means of promoting electronic information exchange among systems with controlled vocabularies. The authors describe a frame-based system developed as an experimental approach to mapping between controlled clinical vocabularies.     

FILIP: A fuzzy intelligent information system with learning capabilities

FILIP (fuzzy intelligent learning information processing) system is designed with the goal to model human information processing. The issues addressed are uncertain knowledge representation and approximate reasoning based on fuzzy set theory, and knowledge acquisition by “being told” or by “learning from examples”. Concepts that can be “learned” by the system can be imprecise (fuzzy), or the knowledge can be incomplete. In the latter case, FILIP uses the concept of similarity to extrapolate the knowledge to cases that were not covered by examples provided by the user. Concepts are stored in the Knowledge Base and employed in intelligent query processing, based on flexible inference that supports approximate matches between the data in the database and the query.

The architecture of FILIP is discussed, the learning algorithm is described, and examples of the system's performance in the knowledge acquisition and querying modes, together with its explanatory capabilities are shown.     

智能楼宇中MS SQL数据库研究及设计

智能楼宇系统是建筑系统与现代的计算机技术和信息技术相结合产生的。智能楼宇系统给日常生活和企业带来了便捷的管理方式。本文主要研究了智能楼宇系统中基于MS SQL数据库的信息系统的设计和实现。首先介绍了智能楼宇系统和MSSQL的一些知识,然后研究设计了数据库系统的实现和数据库的一些优化措施。     

IFOOD: an intelligent fuzzy object-oriented database architecture

Next generation information system applications require powerful and intelligent information management that necessitates an efficient interaction between database and knowledge base technologies. It is also important for these applications to incorporate uncertainty in data objects, in integrity constraints, and/or in application. In this study, we propose an intelligent object-oriented database architecture, FOOD, which permits the flexible modeling and querying of complex data and knowledge including uncertainty with powerful retrieval capability.     

远程教学中面向对象的知识模型及其MAS实现

研究分析了远程教学发展现状，指出了第一代远程教育模式的不足之处，并提出了新一代远程教学模式：提供个性化服务的智能化远程教学。深入研究了智能化教学平台的组织结构；详细阐述了面向对象知识模型的实现机理和提供个性化服务的智能化控制策略。