Data summarization ontology-based query processing

Data summarization has recently received considerable attention in the knowledge systems community. This paper discusses the design of data summarization query system. Based on an initial analysis of requirement representations in data summarization, the study develops a generic organization of ontology for data summarization query system. Furthermore, this paper proposes a framework of ontology-based query language of data summarization based on the proposed ontology structure. A prototype project of data summarization ontology-based Query by Examples (QBE) for summarizing the data incompleteness demonstrates the effectiveness of the proposed framework.     

一种基于本体的P2P网络搜索方法

现有P2P网络规模大、动态性高、异构性强.有效的搜索技术一直是P2P系统研究中的核心问题.本文针对无结构P2P网络泛洪搜索机制的盲目性所导致的查询开销大、效率低的问题,提出了一种基于本体的P2P网络搜索方法OA.该方法给出了一个基于本体的P2P网络搜索模型,并设计了一个全局共享的节点本体来表示和组织节点知识,以提高检索质量.同时,设计了一个节点聚类算法PCA来改善消息路由.实验结果表明,OA算法比Gnutella算法实现了更高的查准率和查全率.     

A query refinement framework for xml keyword search

Existing work of XML keyword search focus on how to find relevant and meaningful data fragments for a query, assuming each keyword is intended as part of it. However, in XML keyword search, user queries usually contain irrelevant or mismatched terms, typos etc, which may easily lead to empty or meaningless results. In this paper, we introduce the problem of content-aware XML keyword query refinement, where the search engine should judiciously decide whether a user query Q needs to be refined during the processing of Q, and find a list of promising refined query candidates which guarantee to have meaningful matching results over the XML data, without any user interaction or a second try. To achieve this goal, we build a novel content-aware XML keyword query refinement framework consisting of two core parts: (1) we build a query ranking model to evaluate the quality of a refined query RQ, which captures the morphological/semantical similarity between Q and RQ and the dependency of keywords of RQ over the XML data; (2) we integrate the exploration of RQ candidates and the generation of their matching results as a single problem, which is fulfilled within a one-time scan of the related keyword inverted lists optimally. Finally, an extensive empirical study verifies the efficiency and effectiveness of our framework.     

Layered ontology-based multi-sourced information integration for situation awareness

The Journal of Supercomputing - Data and information produced in network-centric environments are large and heterogeneous. As a solution to this challenge, ontology-based situation awareness (SA)...     

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

Data access in an enterprise setting is a determining factor for value creation processes, such as sense-making, decision-making, and intelligence analysis. Particularly, in an enterprise setting, intuitive data access tools that directly engage domain experts with data could substantially increase competitiveness and profitability. In this respect, the use of ontologies as a natural communication medium between end users and computers has emerged as a prominent approach. To this end, this article introduces a novel ontology-based visual query system, named OptiqueVQS, for end users. OptiqueVQS is built on a powerful and scalable data access platform and has a user-centric design supported by a widget-based flexible and extensible architecture allowing multiple coordinated representation and interaction paradigms to be employed. The results of a usability experiment performed with non-expert users suggest that OptiqueVQS provides a decent level of expressivity and high usability and hence is quite promising.     

MQSS: multimodal query suggestion and searching for video search

In this paper, we propose a multimodal query suggestion method for video search which can leverage multimodal processing to improve the quality of search results. When users type general or ambiguous textual queries, our system MQSS provides keyword suggestions and representative image examples in an easy-to-use dropdown manner which can help users specify their search intent more precisely and effortlessly. It is a powerful complement to initial queries. After the queries are formulated as multimodal query (i.e., text, image), the new queries are input to individual search models, such as text-based, concept-based and visual example-based search model. Then we apply multimodal fusion method to aggregate the above-mentioned several search results. The effectiveness of MQSS is demonstrated by evaluations over a web video data set.     

Retrieval effectiveness of an ontology-based model for information selection

Technology in the field of digital media generates huge amounts of nontextual information, audio, video, and images, along with more familiar textual information. The potential for exchange and retrieval of information is vast and daunting. The key problem in achieving efficient and user-friendly retrieval is the development of a search mechanism to guarantee delivery of minimal irrelevant information (high precision) while insuring relevant information is not overlooked (high recall). The traditional solution employs keyword-based search. The only documents retrieved are those containing user-specified keywords. But many documents convey desired semantic information without containing these keywords. This limitation is frequently addressed through query expansion mechanisms based on the statistical co-occurrence of terms. Recall is increased, but at the expense of deteriorating precision. One can overcome this problem by indexing documents according to context and meaning rather than keywords, although this requires a method of converting words to meanings and the creation of a meaning-based index structure. We have solved the problem of an index structure through the design and implementation of a concept-based model using domain-dependent ontologies. An ontology is a collection of concepts and their interrelationships that provide an abstract view of an application domain. With regard to converting words to meaning, the key issue is to identify appropriate concepts that both describe and identify documents as well as language employed in user requests. This paper describes an automatic mechanism for selecting these concepts. An important novelty is a scalable disambiguation algorithm that prunes irrelevant concepts and allows relevant ones to associate with documents and participate in query generation. We also propose an automatic query expansion mechanism that deals with user requests expressed in natural language. This mechanism generates database queries with appropriate and relevant expansion through knowledge encoded in ontology form. Focusing on audio data, we have constructed a demonstration prototype. We have experimentally and analytically shown that our model, compared to keyword search, achieves a significantly higher degree of precision and recall. The techniques employed can be applied to the problem of information selection in all media types.Received: 7 October 2002, Accepted: 20 May 2003, Published online: 30 September 2003Edited by: E. LochovskyThis research has been funded [or funded in part] by the Integrated Media Systems Center, a National Science Foundation Engineering Research Center, Cooperative Agreement No. EEC-9529152.     

User-centric query refinement and processing using granularity-based strategies

Under the context of large-scale scientific literatures, this paper provides a user-centric approach for refining and processing incomplete or vague query based on cognitive- and granularity-based strategies. From the viewpoints of user interests retention and granular information processing, we examine various strategies for user-centric unification of search and reasoning. Inspired by the basic level for human problem-solving in cognitive science, we refine a query based on retained user interests. We bring the multi-level, multi-perspective strategies from human problem-solving to large-scale search and reasoning. The power/exponential law-based interests retention modeling, network statistics–based data selection, and ontology-supervised hierarchical reasoning are developed to implement these strategies. As an illustration, we investigate some case studies based on a large-scale scientific literature dataset, DBLP. The experimental results show that the proposed strategies are potentially effective.     

Analysis and searching for information in full-text databases

Features of the accumulation, processing, storage, and usage of mass media sources, including newspapers, radio, and TV are described. The technology of processing and usage includes several levels, that is, full-text, abstract, key words, meta-information, and codes. The search can be polyareal, typical, or nonstandard.     

An empirical analysis of ontology-based query expansion for learning resource searches using MERLOT and the Gene ontology

This paper proposes an expansion of queries based on formal domain ontologies in the context of the search for learning resources in repositories. The expansion process uses the relation types that are represented in these models; common ontological relations, and ontological relations specific to domain and traditional terminology relations, typical of thesauri. The tests were conducted using Gene ontology as the knowledge base and MERLOT is used as the test repository. The results of this study case indicate that, at similar levels of precision, expanded queries improve levels of novelty and coverage compared to the original query (without expansion), i.e. expanded queries allow the user to retrieve relevant objects, which might not be obtained without expansion.     

基于移动Agent的信息搜索系统的研究

对传统客户/服务器模式的网络信息搜索系统的缺点进行了分析,将移动Agent技术引入信息搜索领域,阐述了Agent和移动Agent的概念,特点、开发工具,分析了其适合信息搜索的技术特点.提出了一个基于移动Agent的网络信息搜索原型系统(MAISS)来处理网络信息搜索,以实现搜索的高效率,低开销以及智能化,并时其结构及功能,实现机制和关键技术进行了深入的分析和讨论.     

网格环境下基于本体的信息检索体系研究

为了优化基于本体的信息检索的处理过程、提高应用系统的可靠性,提出了一种网格环境中基于本体的信息检索体系模型.利用Globus和OGSA-DAI工具进行计算资源和数据资源的管理,整合了闲置资源,提高了资源利用率,同时,将数据访问服务化,统一了接口访问类型.利用工作流模型管理业务流程的执行,实现了对数据的分布式部署,对业务服务的并行执行,能够在一定程度上解决因为信息量庞大、流程算法复杂带来的检索低效问题,提高系统的客错能力.     

Controlled query evaluation for enforcing confidentiality in complete information systems

An important goal of security in information systems is confidentiality. A confidentiality policy specifies which users should be forbidden to acquire what kind of information. A controlled query evaluation should enforce such a policy even if users are able to reason about a priori knowledge and the answers to previous queries. The following aspects are considered: formal models of confidentiality policies based on potential secrets or secrecies, user awareness of the policy instance, and enforcement methods applying either lying or refusal, or a combination thereof. Reconsidering previous work and filling the gaps, we comprehensively treat and compare the resulting 12 cases. Thereby, the assumed completeness of the information system is essentially used.     

An ontology-based analysis of the industry foundation class schema for building information model exchanges

Robust knowledge sharing frameworks between different stakeholders in a building project is of high priority. Industry Foundation Classes (IFC) provides a rich schema for interoperability through object-based transactions. However, IFC lacks semantic clarity in mapping entities and relationships, resulting in multiple definitions to map the same information between different federated models. The objective of this research is to examine IFC from a perspective of an ontological framework, which can make the IFC definitions more formal, consistent and unambiguous. Different methods of ontological approaches to engineering knowledge are reviewed. Various issues such as the need for a logical framework, the current semantic approaches in the AEC/FM industry, and advantages of building an ontology structure are addressed. A comparative study of the ontology and segments of the existing IFC schema definition are performed. This exercise reveals the ambiguous nature of current IFC definitions and proposes reforms such that data exchanges would be more semantically robust. An ontology would structure the overall interoperability of BIM tools by providing a formal and consistent taxonomy and classification structure for extending IFC and for defining subsets as model view definitions (MVD).     

Evolutionary approach for semantic-based query sampling in large-scale information sources

Metadata about information sources (e.g., databases and repositories) can be collected by Query Sampling (QS). Such metadata can include topics and statistics (e.g., term frequencies) about the information sources. This provides important evidence for determining which sources in the distributed information space should be selected for a given user query. The aim of this paper is to find out the semantic relationships between the information sources in order to distribute user queries to a large number of sources. Thereby, we propose an evolutionary approach for automatically conducting QS using multiple crawlers and obtaining the optimized semantic network from the sources. The aim of combining QS and evolutionary methods is to collaboratively extract metadata about target sources and optimally integrate the metadata, respectively. For evaluating the performance of contextualized QS on 122 information sources, we have compared the ranking lists recommended by the proposed method with user feedback (i.e., ideal ranks), and also computed the precision of the discovered subsumptions in terms of the semantic relationships between the target sources.     

A self-adaptable query allocation framework for distributed information systems

In large-scale distributed information systems, where participants are autonomous and have special interests for some queries, query allocation is a challenge. Much work in this context has focused on distributing queries among providers in a way that maximizes overall performance (typically throughput and response time). However, preserving the participants’ interests is also important. In this paper, we make the following contributions. First, we provide a model to define the participants’ perception of the system regarding their interests and propose measures to evaluate the quality of query allocation methods. Then, we propose a framework for query allocation called Satisfaction-based Query Load Balancing (SQLB, for short), which dynamically trades consumers’ interests for providers’ interests based on their satisfaction. Finally, we compare SQLB, through experimentation, with two important baseline query allocation methods, namely Capacity based and Mariposa-like. The results demonstrate that SQLB yields high efficiency while satisfying the participants’ interests and significantly outperforms the baseline methods. Work partially funded by ARA “Massive Data” of the French ministry of research (Respire project) and the European Strep Grid4All project.     

信息系统数据智能查询功能的设计

信息系统的智能查询功能对大数据显得特别重要,可以更快捷、更有效地在数据库中查询到与用户需求相吻合的数据.系统设计利用WCF技术实现跨平台技术,具有单表查询、条件查询、多表查询、生成视图等功能模块,界面设计友好.系统构架分为公共层、服务端、客户端.系统能够做到用户点击界面便可查询所需数据,还可以把用户觉得重要的查询方式保存为视图,以便下次查看.     

How students evaluate information and sources when searching the World Wide Web for information

The World Wide Web (WWW) has become the biggest information source for students while solving information problems for school projects. Since anyone can post anything on the WWW, information is often unreliable or incomplete, and it is important to evaluate sources and information before using them. Earlier research has shown that students have difficulties with evaluating sources and information. This study investigates the criteria secondary educational students use while searching the Web for information. 23 students solved two information problems while thinking aloud. After completing the tasks they were interviewed in groups on their use of criteria. Results show that students do not evaluate results, source and information very often. The criteria students mention when asked which criteria are important for evaluating information are not always the same criteria they mention while solving the information problems. They mentioned more criteria but also admitted not always using these criteria while searching the Web.     

A model for designing query images in distributed internet information systems

In this article we examined a model for designing query images in distributed Internet information systems. The research data on the boundaries of subject areas is also presented. The model can be used in preliminary assessment in document search processes in distributed Internet information systems. As well, an algorithm for compiling a frequency dictionary in the process of designing a query search image is given.