个人数据管理技术研究

信息技术的发展使个人数据量迅速增长,个人数据管理问题日益突出。对个人数据管理相关概念进行了阐述,从技术方面对个人数据管理与企业数据管理进行了比较,提出了以主体为中心的个人数据管理系统框架。从数据模型、数据集成、数据存储、数据查询、安全与隐私保护、评价技术、系统实现几个方面,综述分析了已有研究工作,提出了基于图的个人数据空间模型、自适应的个人数据集成方法、多级的数据存储策略和基于用户记忆规律的数据查询处理策略,并对该领域未来研究工作进行了展望。     

一种基于预测建模的WSN数据管理方案

能效、满足用户多样化需求的传感器网络数据管理是当前传感器网络应用的一个重大挑战,本文在基于Proxy/Sensor分层传感器网络数据管理方式基础上,提出了一种新的传感器数据管理方案,利用用户的历史查询建立时间序列预测模型以推断用户的未来数据需求,基于预测结果从Sensor层节点获取感知数据并存储在Proxy层节点,同时Sensor层节点实时监测自身的负载状态,当负载达到阈值后主动上报历史感知数据,以提供对历史数据查询与分析的支持.实验结果表明该方案在满足用户数据需求的基础上,以较低的能耗和较小的查询时延获得了较为全面的性能.     

Web使用挖掘在远程开放教育网站建设的应用

通过广东电大成绩查询网站的开发运行,应用Web使用挖掘技术,对成绩查询网站服务器日志数据及扩展的用户日志数据进行数据挖掘,分析了解学生的访问行为,从而可以为学生提供个性化、针对性的服务;同时基于Web使用挖掘的研究可以使网站结构曼合理、更安全.     

面向混合数据源的企业数据库私有云设计

针对混合数据源的采集、集成和应用问题,提出一种面向混合数据源的数据库私有云设计,针对混合数据源的不同结构化程度,将数据源分成结构化、半结构化和非结构化;针对混合数据源不同的不同时序特点,数据库私有云设计定时采集和实时采集两种采集方式;为了提高混合数据源的存取效率,数据库私有云将非结构化和半结构化数据存储在分布式文件系统,将结构化数据存储在分布式数据库;针对混合数据源的大数据应用需求,数据库私有云的计算层由数据仓库、实时数据处理、机器学习和数据查询服务组成;数据库私有云通过服务使能系统辅助用户开发具体应用程序,通过服务管理系统管理和监控这些具体应用程序。数据库私有云设计可以有效提供企业采集、集成和应用混合数据源的效率和效益。     

基于查询语言转换的多源数据统一访问框架

大数据时代,需要集成多样化数据管理分析工具完成业务需求,然而不同工具的数据访问接口标准不一,需要借助适配器进行接口转换以实现数据管理分析工具协作.因此,如何快速集成不同工具成为学术界与工业界亟待解决的问题.本文提出了一种基于查询语言转换的多源数据统一访问框架BAF4DUA(Bi-Adapter Framework for Data Unified Access),该框架采用双端接口适配方式,在数据提供者工具端和数据消费者工具端分别引入适配器对系统数据与查询语义进行适配,将查询语言与数据存储模型相分离,从而实现了数据提供者与数据消费者之间多对多、即插即用的数据访问,提高了应用的灵活性与扩展性.     

面向多模态数据的新型数据库技术专题前言

<正>以数字技术为标志的新一轮科技革命方兴未艾,将人类带入数字经济时代.全球各行各业数据量呈现爆炸式增长,数据类型和数据格式也呈现多种形式,例如结构化关系表、半结构化JSON/XML、非结构化文本/图像/视频,以及图数据、流数据和时序数据等.这要求数据库系统能够同时高效地管理多种不同类型的数据.多模态数据管理与分析成为亟需解决的问题.目前的方法主要通过拓展现有的数据库或通过集成各种不同模态数据管理引擎来支持多模态数据管理与分析,缺少新颖的理论、方法与技术的支撑.本专题围绕多模态数据管理与分析的整个生命周期,通过结合大数据技术和人工智能方法探讨新型数据库系统理论、方法和技术,包括多模态数据统一建模、存储与索引、查询与挖掘、并发控制、多模态数据库系统构建及其典型应用等主题,赋予数据库系统新的管理能力,形成多模态数据管理与分析在各行各业的最新应用成果.     

关系数据库管理系统RXDB的设计与实现

RXDB是一个通用的关系数据库管理系统,它以简单实用,功能完备,执行效率高为目标。RXDB支持统一的关系用户语言RQL。本文是对RXDB的全面介绍,RXDB主要由查询决策和数据管理两个子系统组成,查询决策子系统(QDS)主要完成RQL的编译与查询优化,数据管理子系统(DMS)主要完成存取路径的维护与并发控制。     

一种支持Top-k空间关键词检索的高效压缩索引

基于位置的服务可以指引用户找到在特定位置或区域内能够提供所需要服务的对象(比如找某个高校附近(经纬度标识)的咖啡店).向这类服务提交一个查询位置和多个关键词,该类服务返回k个最相关的对象,对象和查询的相关性同时考虑空间相近性和文本相似性.为了支持高效的top-k空间关键词查询,出现了多种混合索引,然而现有的这些索引为了提供实时响应均耗费大量存储空间.提出一种基于压缩技术的索引CSTI,该索引显著减少了存储开销(至少减少80%甚至到两个数据量级),同时保持高效的查询性能.大量基于真实和仿真数据集的实验结果表明,CSTI在空间开销和响应时间上均优于已有方法.     

利用反馈的时序模式挖掘算法研究

针对时序数据相似性挖掘方法进行研究，提出一种利用反馈的时序数据相似性挖掘算法，由用户赋予各初始范围查询得到的相似序列相应的权值，通过反馈与给定序列叠加产生新的查询序列，再次进行范围查询，获得相似序列，将该算法用于某钢铁企业的电力负荷时序数据，计算结果表明了算法的有效性。     

LBS中外包空间数据的kNN安全查询方法

云计算服务允许数据拥有者将数据库外包出去,从而避免高昂的存储和计算资源,该方法的关键在于既要对第三方服务提供商保持数据的机密性,又要为认证用户提供实时查询结果。对此,提出一种转换和加密方法,应用到服务提供商在空间数据集上执行用户查询和响应过程中。采用空间填充Hilbert曲线将多维空间的每一个空间点映射到单维空间;基于顺序保留加密技术处理转换的空间数据;用户向服务提供商发起基于Hilbert值的空间kNN查询,并应用加密密钥对查询响应进行解密。实验证明该加密方法能减少认证用户与服务提供商之间的通信开销。     

A Movie Recommendation System – An Application of Voting Theory in User Modeling

Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to model and reason with user preferences for items in the application domain. Our primary concern is to develop a reasoning procedure that can meaningfully and systematically tradeoff between user preferences. We have adapted mechanisms from voting theory that have desirable guarantees regarding the recommendations generated from stored preferences. To demonstrate the applicability of our technique, we have developed a movie recommender system that caters to the interests of users. We present issues and initial results based on experimental data of our research that employs voting theory for user modeling, focusing on issues that are especially important in the context of user modeling. We provide multiple query modalities by which the user can pose unconstrained, constrained, or instance-based queries. Our interactive agent learns a user model by gaining feedback aboutits recommended movies from the user. We also provide pro-active information gathering to make user interaction more rewarding. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide robust and effective recommendations.     

HyDB:集成MapReduce和数据库的高效SaaS架构

随着数据的快速增长和云计算的兴起,软件作为服务(SaaS)标志着计算机系统按需服务的应用的兴起.高效经济SaaS使得许多企业将大规模数据分析服务从部署在并行数据库的高端服务器转移至更便宜的无共享体系结构的低端服务器集群上.论文提出了集成MapReduce和数据库的高效经济SaaS架构—HyDB系统,解决海量结构化,半结构化与非结构化数据的高效查询服务,通过对数据的存储模型和查询模型进行研究,提出了完整的数据存储和查询服务方案,给出基于队列的作业调度算法,并支持针对简约数据查询的快速响应模式.最后通过可扩展实验,证明了该系统架构具有良好的加载性能、查询性能和容错能力,可以为用户提供优质的数据服务.     

Personal Data Management Systems: The security and functionality standpoint

Riding the wave of smart disclosure initiatives and new privacy-protection regulations, the Personal Cloud paradigm is emerging through a myriad of solutions offered to users to let them gather and manage their whole digital life. On the bright side, this opens the way to novel value-added services when crossing multiple sources of data of a given person or crossing the data of multiple people. Yet this paradigm shift towards user empowerment raises fundamental questions with regards to the appropriateness of the functionalities and the data management and protection techniques which are offered by existing solutions to laymen users. These questions must be answered in order to limit the risk of seeing such solutions adopted only by a handful of users and thus leaving the Personal Cloud paradigm to become no more than one of the latest missed attempts to achieve a better regulation of the management of personal data. To this end, we review, compare and analyze personal cloud alternatives in terms of the functionalities they provide and the threat models they target. From this analysis, we derive a general set of functionality and security requirements that any Personal Data Management System (PDMS) should consider. We then identify the challenges of implementing such a PDMS and propose a preliminary design for an extensive and secure PDMS reference architecture satisfying the considered requirements. Finally, we discuss several important research challenges remaining to be addressed to achieve a mature PDMS ecosystem.     

基于移动设备的个人云服务及资源Mashup

个人用户家庭或工作环境中的智能手机、个人电脑、智能相册等通过网络形成个人云,为个人的数据处理和共享带来了便利。然而,如何面向具体应用需求为用户提供方便、高效的个人云服务及资源整合仍然是一个亟待解决的问题。为此,提出了一种基于移动设备的个人云服务及资源Mashup框架来统一管理设备和描述服务及资源,并阐述了如何通过框架合理构建Mashup应用;此外,开发了基于Agent的框架实现以及Android客户端。基于该框架及客户端,用户可以通过整合个人云服务及资源方便、快捷地构造个人化应用。通过一个用户案例研究对所提出的Mashup框架及其实现的有效性和易用性进行了评估。     

Personalized Service Discovery in Ubiquitous Computing Environments

In ubiquitous computing environments, users want to discover the most appropriate service to support their tasks. Because the most appropriate service depends on user preferences and context, service discovery protocols should personalize results. A service discovery framework based on the virtual personal space (VPS)-that is, a virtual administrative domain of services managed for the user-aims to provide this personalization. In this framework, personal operating middleware embedded in a personal device manages a set of contextually close services in the user's VPS. An inference module supports this management. Laboratory evaluations show that the VPS framework helps users find high-quality, appropriate services.     

ECMail:基于实体发现、查找和管理的中文邮件管理系统

随着个人用户的数据和信息级数增长,个人信息管理的研究成为热点.电子邮件作为个人信息的重要载体在个人信息业务中占据着重要的地位.随着个人信息的增加,用户在对邮件进行查询时经常遇到遗忘关键字的困扰,对此普通的邮件工具很难为用户组织和管理个人信息提供帮助.提出了一个基于实体发现、查找和管理的中文邮件管理系统--ECMail,有效改善了以上问题,同时对关键技术-中文分词、实体挖掘和实体关联管理的实现提出了自己的想法和处理机制,最终达到了提高用户邮件管理效率的目的.     

Towards practical private processing of database queries over public data

Privacy is a major concern when users query public online data services. The privacy of millions of people has been jeopardized in numerous user data leakage incidents in many popular online applications. To address the critical problem of personal data leakage through queries, we enable private querying on public data services so that the contents of user queries and any user data are hidden and therefore not revealed to the online service providers. We propose two protocols for private processing of database queries, namely BHE and HHE. The two protocols provide strong query privacy by using Paillier’s homomorphic encryption, and support common database queries such as range and join queries by relying on the bucketization of public data. In contrast to traditional Private Information Retrieval proposals, BHE and HHE only incur one round of client server communication for processing a single query. BHE is a basic private query processing protocol that provides complete query privacy but still incurs expensive computation and communication costs. Built upon BHE, HHE is a hybrid protocol that applies ciphertext computation and communication on a subset of the data, such that this subset not only covers the actual requested data but also resembles some frequent query patterns of common users, thus achieving practical query performance while ensuring adequate privacy levels. By using frequent query patterns and data specific privacy protection, HHE is not vulnerable to the traditional attacks on k-Anonymity that exploit data similarity and skewness. Moreover, HHE consistently protects user query privacy for a sequence of queries in a single query session.     

Designing a personal informatics system for users without experience in self-tracking: a case study

Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics (PI) systems can now reach a larger audience of users. However, it is not still clear whether this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific barriers that may prevent the widespread adoption of PI and finding solutions to overcome them. We requested users without competence in self-tracking to use different PI instruments during their daily practices, identifying five user requirements by which to design novel PI tools. On such requirements, we developed a new system that can stimulate the use of these technologies, by enhancing the perceived benefits of collecting personal data. Then, we explored how naïve and experienced users differently explore their personal data in our system through a user trial. Results showed that the system was successful at helping individuals manage and interpret their own data, validated the usefulness of the requirements found and inspired three further design opportunities that could orient the design of future PI systems.     

An Operable Email Based Intelligent Personal Assistant

The recent phenomena of email-function-overloading and email-centricness in daily life and business have created new problems to users. There is a practical need for developing a software assistant to facilitate the management of personal and organizational emails, and to enable users to complete their email-centric jobs or tasks smoothly. This paper presents the status, goals, and key technical elements of an Email-Centric Intelligent Personal Assistant, called ECIPA. ECIPA provides various assisting functions, including automated and cost-sensitive spam filtering based on corresponding analysis, ontology-mediated email classification, query and archiving. ECIPA can learn from dynamic user behaviors to effectively sort and automatically respond email. Techniques developed in Web Intelligence (WI) are adopted to implement ECIPA. In order to facilitate cooperation of ECIPAs of different users, the concept of operable email, an extension of traditional email with an operable form, is introduced. ECIPA can in fact be viewed as a family of collaborative agents working together on the operable email.     

A polymorphic service management scheme based on virtual object for ubiquitous computing environment

For the ubiquitous computing environment, an important assumption is that all the components in any specific environment are connected with each other. With this assumption, we introduce an effective scheme to provide a personalized service based on Virtual Personal World (VPW). Virtual Personal World (VPW) which is a model focused on service continuity with specially designed components. Previous ubiquitous frameworks have been concerned with the location where a user is provided any specific service. However those questions above are not the most important problems anymore in VPW. It concentrates on the point whether the services are successive or not, wherever a user goes to any place. Services are not regarded as a sum of functions which is embedded on any objects in any certain place. We conceptually define a resource management scheme based on a unified form of the object which participates in service provision, so called virtual object (VO). Thus the service can be described as the sum of functions of VOs. With our resource management scheme, users can utilize their required object as VO wherever it is located. And also, for better utilization of VPW service, we introduce a novel form of profiles and service provision scheme based on the polymorphism. Our simulation result shows that the Ratio of VPW pure service time is 0.15 % higher than conventional location based service. And also the possibility that users can meet adequate service he wants raised 29 % in our proposed VPW environment.