Answering constraint-based mining queries on itemsets using previous materialized results

In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user interacts with the DBMS using advanced, constraint-based languages for data mining where constraints have been specifically introduced to increase the relevance of the results and, at the same time, to reduce its volume. In this paper we study the problem of mining frequent itemsets using an inductive database. We propose a technique for query answering which consists in rewriting the query in terms of union and intersection of the result sets of other queries, previously executed and materialized. Unfortunately, the exploitation of past queries is not always applicable. We then present sufficient conditions for the optimization to apply and show that these conditions are strictly connected with the presence of functional dependencies between the attributes involved in the queries. We show some experiments on an initial prototype of an optimizer which demonstrates that this approach to query answering is viable and in many practical cases it drastically reduces the query execution time.     

Efficient query expansion with auxiliary data structures

Query expansion is a well-known method for improving average effectiveness in information retrieval. The most effective query expansion methods rely on retrieving documents which are used as a source of expansion terms. Retrieving those documents is costly. We examine the bottlenecks of a conventional approach and investigate alternative methods aimed at reducing query evaluation time. We propose a new method that draws candidate terms from brief document summaries that are held in memory for each document. While approximately maintaining the effectiveness of the conventional approach, this method significantly reduces the time required for query expansion by a factor of 5–10.     

关系数据库中的多表联接查询

联接查询是关系数据库中最主要的查询,本文通过实例说明关系数据库中进行多表联接查询时联接的顺序性。     

Preprocessing of Spatial Query in Distributed GIS

This paper focuses on spatial query optimization in distributed GIS. A new qualitative spatial relation model and its consistency problem solution which is composed of topology, direction, distance and size, are proposed. Research integrating the four aspects has not appeared before. A new method to deduce the constraints of spatial query is given, so it saves the query process time in distributed GIS. Finally, the methods and theories are applied to a distributed GIS project, and the experiment result is satisfactory.     

Query by image and video content: a colored-based stochastic model approach

For efficient image retrieval, the image database should be processed to extract a representing feature vector for each member image in the database. A reliable and robust statistical image indexing technique based on a stochastic model of an image color content has been developed. Based on the developed stochastic model, a compact 12-dimensional feature vector was defined to tag images in the database system. The entries of the defined feature vector are the mean, variance, and skewness of the image color histogram distributions as well as correlation factors between color components of the RGB color space. It was shown using statistical analysis that the feature vector provides sufficient knowledge about the histogram distribution. The reliability and robustness of the proposed technique against common intensity artifacts and noise was validated through several experiments conducted for that purpose. The proposed technique outperforms traditional and other histogram based techniques in terms of feature vector size and properties, as well as performance.     

Building Minority Language Corpora by Learning to Generate Web Search Queries

The Web is a source of valuable information, but the process of collecting, organizing, and effectively utilizing the resources it contains is difficult. We describe CorpusBuilder, an approach for automatically generating Web search queries for collecting documents matching a minority concept. The concept used for this paper is that of text documents belonging to a minority natural language on the Web. Individual documents are automatically labeled as relevant or nonrelevant using a language filter, and the feedback is used to learn what query lengths and inclusion/exclusion term-selection methods are helpful for finding previously unseen documents in the target language. Our system learns to select good query terms using a variety of term scoring methods. Using odds ratio scores calculated over the documents acquired was one of the most consistently accurate query-generation methods. To reduce the number of estimated parameters, we parameterize the query length using a Gamma distribution and present empirical results with learning methods that vary the time horizon used when learning from the results of past queries. We find that our system performs well whether we initialize it with a whole document or with a handful of words elicited from a user. Experiments applying the same approach to multiple languages are also presented showing that our approach generalizes well across several languages regardless of the initial conditions.     

硬件组合技术在数据库查询优化中的应用

查询优化技术是关系数据库成功运作的关键技术之一。随着现代数据库规模不断扩大到以十亿字节(GB)计量,对能够处理如此巨大的数据信息的系统的需求也随之而来。找到一种高效的信息提取方法对于使研发过程更快、更容易地进行是十分必要的。文章介绍了一种将与或图和数字逻辑电路技术应用于SQL查询优化,得到数据库中有效信息的技术方法。该方法中把与或图作为一种中间数据结构,用来描述布尔值域上的查询集合的子集;数字逻辑电路则用来表示二进制数集合上的各项逻辑运算功能的一种实现方式。该文同时给出了相关实验结果,实验表明这是一个十分有效的方法。     

B~+-Tree的改进算法在可复用软构件库中的应用

文章通过对B+-Tree索引算法的改进,将其应用到可复用软构件库中。该改进算法继承了B+-Tree的优点,结合可复用软构件库的特点,将构件库多维数据索引转化为B+-Tree一维数据索引进行存储、查询。通过对比分析,证明了该构件库索引算法大大改进了构件库中构件的查找效率。     

经济地理信息系统

经济地理信息系统是基于地理信息系统开发平台，实现对大量资源数据信息进行计算机管理与辅助决策的大型软件系统。它利用计算机技术、地理信息系统(GIS)技术，在现有的基础信息库的基础上，联系相关部门的业务需要，实现经济信息管理的科学化和自动化。