Safety, domain independence and translation of complex value database queries

This paper considers the theory of database queries on the complex value data model with external functions. Motivated by concerns regarding query evaluation, we first identify recursive sets of formulas, called embedded allowed, which is a class with desirable properties of “reasonable” queries.We then show that all embedded allowed calculus (or fix-point) queries are domain independent and continuous. An algorithm for translating embedded allowed queries into equivalent algebraic expressions as a basis for evaluating safe queries in all calculus-based query classes has been developed.Finally we discuss the topic of “domain independent query programs”, compare the expressive power of the various complex value query languages and their embedded allowed versions, and discuss the relationship between safety, embedded allowed, and domain independence in the various calculus-based queries.     

Querying business processes with BP-QL

We present in this paper BP-QL, a novel query language for querying business processes. The BP-QL language is based on an intuitive model of business processes, an abstraction of the emerging BPEL (business process execution language) standard. It allows users to query business processes visually, in a manner very analogous to how such processes are typically specified, and can be employed in a distributed setting, where process components may be provided by distinct providers.     

Continuous query processing over music streams based on approximate matching mechanisms

It is foreseen that more and more music objects in symbolic format and multimedia objects, such as audio, video, or lyrics, integrated with symbolic music representation (SMR) will be published and broadcasted via the Internet. The SMRs of the flowing songs or multimedia objects will form a music stream. Many interesting applications based on music streams, such as interactive music tutorials, distance music education, and similar theme searching, make the research of content-based retrieval over music streams much important. We consider multiple queries with error tolerances over music streams and address the issue of approximate matching in this environment. We propose a novel approach to continuously process multiple queries over the music streams for finding all the music segments that are similar to the queries. Our approach is based on the concept of n-grams, and two mechanisms are designed to reduce the heavy computation of approximate matching. One mechanism uses the clustering of query n-grams to prune the query n-grams that are irrelevant to the incoming data n-gram. The other mechanism records the data n-gram that matches a query n-gram as a partial answer and incrementally merges the partial answers of the same query. We implement a prototype system for experiments in which songs in the MIDI format are continuously broadcasted, and the user can specify musical segments as queries to monitor the music streams. Experiment results show the effectiveness and efficiency of the proposed approach.     

垫片标准查询系统开发中的关键技术

鉴于国内外密封垫片标准众多、数据量庞大,设计了基于VisualBasic与MSAccess的垫片标准查询系统,实现了垫片标准的自动化查询。扩展了部分VB控件的功能,通过捕捉鼠标事件,实现了Picturebox控件的滚轮缩放以及MSHFlexGrid控件的滚轮翻页功能。可对查询结果进行二次筛选并输出至word文档,操作便捷。     

基于数据库查询的自然语言接口研究

语音识别技术是近年来信息领域重要的科技发展技术之一.作为一门交叉学科,语音识别正逐步成为信息技术中人机接口的关键技术.探讨了为数据库查询提供自然语言接口的可能性,介绍了图书资料查询系统中语音识别的基本框架,并详细描述了采用微软Speech SDK技术实现图书资料查询的详细过程.给出了查询流程,基于状态转换图的词法分析和语法分析方法,将疑问句转换成SQL查询语句的方法,以及由查询结果生成答句的方法.     

基于能量和频繁模式的数据流预测查询算法

设计了数据流预测查询的新模型,包括局域流能量预测、能量分布模式挖掘及预测序列的重构和数据流能量的度量方法;设计了融合数据流能量回归与基于频繁模式的小波分解预测新方法,并将新算法推广到强偶合多数据流的预测查询;提出了最近最频繁序列模式的新概念,并应用于局域流能量分解;在真实数据上的模拟实验,验证了算法的有效性.     

基于文档与搜索结果上下文的查询扩展方法

在查询扩展方法中,如果通过查询结果中关键词的上下文来计算候选关键词的权重,将权重大的词作为查询扩展词,其候选关键词来源于文档中关键词的上下文,这种方法存在主题漂移的问题。为了解决这个问题,提出一种将初始查询结果过滤,只选择与源文档语境相似的搜索结果,来帮助选择查询扩展词的方法。实验结果表明该方法能获得更合适的查询扩展词。     

Pattern discovery and change detection of online music query streams

Mining of music data is one of the most important problems in multimedia data mining. In this paper, two research issues of mining music data, i.e., online mining of music query streams and change detection of music query streams, are discussed. First, we proposed an efficient online algorithm, FTP-stream (Frequent Temporal Pattern mining of streams), to mine all frequent melody structures over sliding windows of music melody sequence streams. An effective bit-sequence representation is used in the proposed algorithm to reduce the time and memory needed to slide the windows. An effective list structure is developed in the FTP-stream algorithm to overcome the performance bottleneck of 2-candidate generation. Experiments show that the proposed algorithm FTP-stream only needs a half of memory requirement of original melody sequence data, and just scans the music query stream once. After mining frequent melody structures, we developed a simple online algorithm, MQS-change (changes of Music Query Streams), to detect the changes of frequent melody structures in current user-centered music query streams. Two music melody structures (set of chord-sets and string of chord-sets) are maintained and four melody structure changes (positive burst, negative burst, increasing change and decreasing change) are monitored in a new summary data structure, MSC-list (a list of Music Structure Changes). Experiments show that the MQS-change algorithm is an effective online method to detect the changes of music melody structures over continuous music query streams.

Semplore: A scalable IR approach to search the Web of Data

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.     

多维数据的复杂查询聚集算法研究

对空间多维数据的复杂查询是多维数据研究的重点和难点,目前研究的结论相对较少。在传统算法的基础上,进行了几个方面的改进：按分组属性值进行数据分块;对分组数据进行有效的排序;在聚集函数的应用上进行优化。模拟数据的试验表明：改进算法较大地提高了查询效率。