An efficient query optimization strategy for spatio-temporal queries in video databases

The interest for multimedia database management systems has grown rapidly due to the need for the storage of huge volumes of multimedia data in computer systems. An important building block of a multimedia database system is the query processor, and a query optimizer embedded to the query processor is needed to answer user queries efficiently. Query optimization problem has been widely studied for conventional database systems; however it is a new research area for multimedia database systems. Due to the differences in query processing strategies, query optimization techniques used in multimedia database systems are different from those used in traditional databases. In this paper, a query optimization strategy is proposed for processing spatio-temporal queries in video database systems. The proposed strategy includes reordering algorithms to be applied on query execution tree. The performance results obtained by testing the reordering algorithms on different query sets are also presented.     

On research issues regarding uncertain query processing in an office document retrieval system

TEXPROS (TEXT PROcessing System) is an intelligent document processing, system; it supports storing, extracting, classifying, categorizing, retrieving, and browsing information from a variety of office documents [76]. This article presents a retrieval subsystem for TEXPROS, which is capable of processing incomplete, imprecise, and vague queries, and providing semantically meaningful responses to the user. The design of the retrieval subsystem is highly integrated with various mechanisms for achieving these goals. First, a system catalog including a thesaurus is used to store the knowledge about the database. Second, there is a query transformation mechanism composed of context construction and algebraic query formulation modules. Given an incomplete or imprecise query, the context construction module searches the system for the required terms and constructs a query that has a complete and precise representation: The resulting query is then formulated into an algebraic expression. Third, in practice, the user may not have a clear idea of what he is searching for. A browing mechanism is employed for such situations to assist the user in the retrieval process. With the browser, vague queries can be entered into the system until sufficient information, is obtained to the extent that the user is able to construct a query for his request. Finally, when processing of queries fails by responding with a null answer to the user, a generalizer mechanism is used to give the user cooperative explanation for the null answer. The presented techniques will contribute to our research toward development of highly intelligent data processing facilities beyond the present scope of database technology.This work was supported, in part, by the New Jersey Institute of Technology under grant No. 421280 and by a grant from the AT&T Foundation.     

基于本体推理的终端用户数据查询构造方法

基于数据分析的智能决策对提升企业竞争力具有重要意义.根据待分析的问题，从内部信息系统的数据库中查询并获取与问题密切相关且信息完整的数据，是企业数据分析过程中的关键环节.基于本体的可视化数据查询系统为不掌握计算机专业技能的终端用户提供了高效获取数据的手段，近年来成为研究热点.然而现有工作仅采用简单的映射规则，将数据库中的表、字段、外键关系等元素直接映射为本体中的概念、属性和关系，向终端用户暴露了过多数据库设计的技术细节，增加了用户理解的难度，降低了系统的可用性.而通过人工编写映射规则来屏蔽数据库细节，既低效又缺乏通用性.针对这一问题，提出了一种基于推理的终端用户本体查询构造方法.该方法利用本体模型的语义表达能力和推理能力，在原有基于数据库简单映射所生成的本体模型基础上注入领域知识，从而优化查询构造流程，使终端用户得以从其更为熟悉的业务知识的视角，而非数据库设计的视角来看待和操纵数据，提高系统可用性；同时，增加了对分组统计的支持，扩展了方法的适用范围.最后，通过对"餐饮前台信息管理"领域真实案例的分析，验证了该方法相对于已有方法，其可用性提高了53.44%，表达能力提高了20.43%.     

The design and implementation of an intelligent query tool for relational databases

Abstract: Retrieving ad hoc data from information systems is difficult for non-expert users. Despite the efforts made in improving query tools (e.g. visual query construction, Query By Example, query templates), empirical research shows that constructing a request is still difficult (Reisner 1988). The core of the problem seems to be in the difference between the way the user perceives the application domain and the way the system requires the user to see it (Carroll & Olsen 1988).
In this paper we describe the design and implementation of an ad hoc query tool developed by RCC for a personnel information system, and how AI techniques contributed to this module. The main novel idea incorporated in the query tool is to present the user with a means to question the conceptual model of the system instead of the technical model. To support this, a blackboard architecture has been designed and implemented with knowledge sources that translate the user's questions to database queries. The query tool is used in daily practice by over 100 users.     

Query rewriting for SWIFT (First) answers

Traditionally, the answer to a database query is construed as the set of all tuples that meet the criteria stated. Strict adherence to this notion in query evaluation is, however, increasingly unsatisfactory because decision makers are more prone to adopting an exploratory strategy for information search which we call “getting some answers quickly, and perhaps more later”. From a decision-maker's perspective, such a strategy is optimal for coping with information overload and makes economic sense (when used in conjunction with a micropayment mechanism). These new requirements present new opportunities for database query optimization. In this paper, we propose a progressive query processing strategy that exploits this behavior to conserve system resources and to minimize query response time and user waiting time. This is accomplished by the heuristic decomposition of user queries into subqueries that can be evaluated on demand. To illustrate the practicality of the proposed methods, we describe the architecture of a prototype system that provides a nonintrusive implementation of our approach. Finally, we present experimental results obtained from an empirical study conducted using an Oracle server that demonstrate the benefits of the progressive query processing strategy     

Polymorphic queries for P2P systems

When a query is posed on a centralized database, if it refers to attributes that are not defined in the database, the user is warranted to get either an error or an empty set. In contrast, when a query is posed on a peer in a P2P system and refers to attributes not found in the local database, the query should not be simply rejected if the relevant information is available at other peers. This paper proposes a query model for unstructured P2P systems to answer such queries. (a) We introduce a class of polymorphic queries, a revision of conjunctive queries by incorporating type variables to accommodate attributes not defined in the local database. (b) We define the semantics of polymorphic queries in terms of horizontal and vertical object expansions, to find attributes and tuples, respectively, missing from the local database. We show that both expansions can be conducted in a uniform framework. (c) We develop a top-K algorithm to approximately answer polymorphic queries. (d) We also provide a method to merge tuples collected from various peers, based on matching keys specified in polymorphic queries. Our experimental study verifies that polymorphic queries are able to find more sensible information than traditional queries supported by P2P systems, and that these queries can be evaluated efficiently.     

An overview of cooperative answering

Databases and information systems are often hard to use because they do not explicitly attempt to cooperate with their users. Direct answers to database and knowledge base queries may not always be the best answers. Instead, an answer with extra or alternative information may be more useful and less misleading to a user. This paper surveys foundational work that has been done toward endowing intelligent information systems with the ability to exhibit cooperative behavior. Grice's maxims of cooperative conversation, which provided a starting point for the field of cooperative answering, are presented along with relevant work in natural language dialogue systems, database query answering systems, and logic programming and deductive databases. The paper gives a detailed account of cooperative techniques that have been developed for considering users' beliefs and expectations, presuppositions, and misconceptions. Also, work in intensional answering and generalizing queries and answers is covered. Finally, the Cooperative Answering System at Maryland, which is intended to be a general, portable platform for supporting a wide spectrum of cooperative answering techniques, is described.     

HyperFile: A data and query model for documents

Non-quantitative information such as documents and pictures pose interesting new problems in the database world. Traditional data models and query languages do not provide appropriate support for this information. Such data are typically stored in file systems, which do not provide the security, integrity, or query features of database management systems. The hypertext model has emerged as a good interface to this information; however,finding information using hypertext browsing does not scale well. We developed a query interface that serves as an extension of the browsing model of hypertext systems. These queries minimize the repeated user interactions required to locate data in a standard hypertext system. HyperFile is a prototype data server interface. In this article, we describe HyperFile, including a number of issues such as query generation, query processing, and indexing.     

Query language approach based on the deductive object-oriented database paradigm

The integration of data-oriented (structural), behavioral and deductive aspects is necessary in next generation information systems. The deductive object-oriented database paradigm offers a very promising starting point for the implementation of these kinds of information systems. So far in the context of this paradigm a big problem has been the lack of a query language suitable to an ordinary end user. Typically in existing proposals for deductive object-oriented databases the user has to master well both logic-based rule formulation and object-oriented programming. In this paper we introduce a set of high-level querying primitives which increases the degree of declarativeness compared to the deductive object-oriented query languages proposed so far. In terms of these primitives it is possible to offer for end users such application-specific concepts and structures whose interpretation is obvious to users but whose specification is too demanding for them. By combining these primitives in queries the user can integrate data-oriented, behavioral and deductive aspects with each other in a concept-oriented way. Our query language approach is based on the incorporation of deductive aspects to object-orientation. Among others this means that deductive aspects of objects are inherited in the specialization/generalization hierarchy like any other properties of objects.     

A multi-agent conversational system with heterogeneous data sources access

In many of the problems that can be found nowadays, information is scattered across different heterogeneous data sources. Most of the natural language interfaces just focus on a very specific part of the problem (e.g. an interface to a relational database, or an interface to an ontology). However, from the point of view of users, it does not matter where the information is stored, they just want to get the knowledge in an integrated, transparent, efficient, effective, and pleasant way. To solve this problem, this article proposes a generic multi-agent conversational architecture that follows the divide and conquer philosophy and considers two different types of agents. Expert agents are specialized in accessing different knowledge sources, and decision agents coordinate them to provide a coherent final answer to the user. This architecture has been used to design and implement SmartSeller, a specific system which includes a Virtual Assistant to answer general questions and a Bookseller to query a book database. A deep analysis regarding other relevant systems has demonstrated that our proposal provides several improvements at some key features presented along the paper.     

A Methodology for Structured Database Decomposition

We present a methodology for structured database decomposition based on the relational data model. It is argued that in the distributed database environment, structured database decomposition is attractive both for efficiency and for database security considerations. Techniques for parallel processing and hashed access of structurally decomposed database are presented. Techniques for structured database decomposition to support multiple user views are also described. Structured database decomposition is most advantageous in a query only database environment with stable user views, although dynamic updates can also be handled using techniques described in this paper.     

Automatic localization and annotation of facial features using machine learning techniques

Content-based image retrieval (CBIR) systems traditionally find images within a database that are similar to query image using low level features, such as colour histograms. However, this requires a user to provide an image to the system. It is easier for a user to query the CBIR system using search terms which requires the image content to be described by semantic labels. However, finding a relationship between the image features and semantic labels is a challenging problem to solve. This paper aims to discover semantic labels for facial features for use in a face image retrieval system. Face image retrieval traditionally uses global face-image information to determine similarity between images. However little has been done in the field of face image retrieval to use local face-features and semantic labelling. Our work aims to develop a clustering method for the discovery of semantic labels of face-features. We also present a machine learning based face-feature localization mechanism which we show has promise in providing accurate localization.     

Reliability of answers to queries in relational databases

The author studies the problem of determining the reliability of answers to queries in a relational database system, where the information in the database comes from various sources with varying degrees of reliability. An extended relational model is proposed in which each tuple in a relation is associated with an information source vector which identifies the information source(s) that contributed to that tuple. The author shows how relational algebra operations can be extended, and implemented using information source vectors, to calculate the vector corresponding to each tuple in the answer to a query, and hence, to identify information source(s) contributing to each tuple in the answer. This also enables the database system to calculate the reliability of each tuple in the answer to a query as a function of the reliability of information sources     

基于用户兴趣的查询扩展语义模型

自然语言中词的同义现象和歧义现象一直是降低信息检索查全率和查准率的关键,在Web搜索引擎上显得更加突出。提出了一种基于用户兴趣的查询扩展语义模型,通过构建基于Yahoo的语义ontology知识库消除同义现象,设计客户端的用户兴趣挖掘模型消除歧义现象。实验结果显示该方法能有效提高Web信息检索的查全率与查准率。     

Growing certainty with null values

Non-availability of part of the data is a problem common to many database systems. We study here some aspects relating to incomplete information. Obviously, when the information in a database is not complete the answer to any query is only an approximation to the true result. The aim is to get a precise approximation. We regard databases as many-sorted algebras. Based on the concept of extended algebra we define what it means for an algebra to approximate another algebra. We then give the following simple principle for extending query languages to handle missing data: “Whenever information is added to an incomplete database subsequent answers to queries must not be contradictory or less informative than previously.” We then apply this principle to extend the functional query language Varqa. Finally, we compare the previously proposed many-valued logic systems with the system devised based on our principles.     

Controlled query evaluation with open queries for a decidable relational submodel

Controlled query evaluation for logic-oriented information systems provides a model for the dynamic enforcement of confidentiality policies in scenarios where users are able to reason about a priori knowledge and the answers to previous queries. Previous foundational work assumes that the control mechanism can solve the arising implication problems and deals only with closed queries. In this paper, we overcome these limitations by refining the abstract model for appropriately represented relational databases. We identify a relational submodel where all instances share a fixed infinite Herbrand domain but have finite base relations, and we require finite and domain-independent query results. Then, via suitable syntactic restrictions on the policy and query languages, each occurring implication problem can be equivalently expressed as a universal validity problem within the Bernays-Schönfinkel class, whose (known) decidability in the classical setting is extended to our framework. For refusal and lying, we design and verify evaluation methods for open queries, exploiting controlled query evaluation of appropriate sequences of closed queries, which include answer completeness tests. Additionally, we present alternative evaluation methods that work for lying and the combined approach but at the price of potentially reduced cooperativeness.     

Dynamic Query Optimization Approach for Semantic Database Grid

Fundamentally, semantic grid database is about bringing globally distributed databases together in order to coordinate resource sharing and problem solving in which information is given well-defined meaning, and DartGrid II is the implemented database gird system whose goal is to provide a semantic solution for integrating database resources on the Web. Although many algorithms have been proposed for optimizing query-processing in order to minimize costs and/or response time, associated with obtaining the answer to query in a distributed database system, database grid query optimization problem is fundamentally different from traditional distributed query optimization. These differences are shown to be the consequences of autonomy and heterogeneity of database nodes in database grid. Therefore, more challenges have arisen for query optimization in database grid than traditional distributed database. Following this observation, the design of a query optimizer in DartGrid II is presented, and a heuristic, dynamic and parallel query optimization approach to processing query in database grid is proposed. A set of semantic tools supporting relational database integration and semantic-based information browsing has also been implemented to realize the above vision.