SCWCD教程：Java Web组件开发认证第二版

需积分: 8 52 浏览量更新于2024-07-26 收藏 5.27MB PDF 举报

《SCWCD考试学习套件：Java Web组件开发人员认证第二版》是一本专注于Java Web开发的专业教材，针对的是Sun Microsystems（现已被Oracle收购）推出的Sun Certified Web Component Developer (SCWCD) 考试的学习资料。该书于2005年5月出版，旨在帮助考生准备并掌握Java Web组件开发的相关知识和技能。本书是LectureNotes in Artificial Intelligence (LNAI)系列的一部分，由J.G. Carbonell和J. Siekmann编辑，它强调了在Web开发中智能信息集成和语义Web的重要性。书中深入探讨了如何处理数据在语义层面的整合，以及如何有效地处理时空关系的表示和管理。SCWCD考试主要考察Java开发者在构建可重用、模块化的Web组件时所需具备的知识，这些组件通常包括JavaServer Faces (JSF)、Enterprise JavaBeans (EJB)和Servlets等技术。在内容上，本书可能包含章节涵盖了以下关键知识点： 1. **Java Web框架基础**：介绍Java Web开发的核心框架，如Java Servlets、JSF和EJB，以及它们在Web组件开发中的角色。 2. **语义Web技术**：讲解RDF（Resource Description Framework）、OWL（Web Ontology Language）和SPARQL（SPARQL Protocol and RDF Query Language），这些都是构建语义Web应用的基础。 3. **数据集成与API设计**：讨论如何设计和实现能够跨多个源集成数据的API，以支持高效的信息共享和查询。 4. **Spatio-temporal数据处理**：涉及地理信息系统（GIS）技术在Web应用中的应用，以及如何处理空间和时间相关的数据模型。 5. **用户体验与UI设计**：关注如何通过Java Web组件提供一致性和易用性，确保用户界面的友好性和性能。 6. **安全与性能优化**：涵盖身份验证、授权、数据加密以及如何优化Web应用程序的性能，如缓存策略和负载均衡。 7. **最佳实践和案例研究**：书中可能包含实战项目和案例分析，以帮助读者理解和应用所学知识。 8. **SCWCD考试指南**：针对SCWCD考试的结构、题型和考试策略进行详细介绍，帮助考生制定有效的复习计划。《SCWCD Exam Study Kit Java Web Component Developer Certification 2nd Edition》是一本实用且深入的参考书籍，适合希望在Java Web开发领域取得SCWCD认证的程序员，或是对Web组件和语义Web感兴趣的开发者阅读。通过这本书，读者可以提升自己的专业技能，并为实际工作中的复杂Web应用开发打下坚实的基础。

Part I

Introduction and Related Work

TEAM LinG

Introduction

The Internet has provided us with a new dimension in terms of seeking and

retrieving information for our various needs. Who would have thought about

the vast amount of data that is currently available electronically ten years

ago? When we look back and think about what made the Internet a success

we think about physical networks, fast servers, and comfortable browsers,

just to name a few. What one might not think about, a simple but important

issue is the first version of HTML. This language allowed people to share their

information in a simple but effective way. All of a sudden, people were able

to define a HTML document and put their information piece on the Web.

The given language was sloppy and almost anybody with a small amount of

knowledge about syntax or simple programming use could define a web page.

Even when language items such as end-tags or closing brackets were forgotten,

the browser did the work and delivered the content without returning syntax

errors. We believe this to be a crucial point when considering the success story

of the Internet: give the people a simple but effective tool with the freedom

to provide their information.

Providing information is one thing, searching and retrieving information is

at least as important. Early browsers or search engines offered the opportunity

to search for specific keywords, mostly searching for strings. The user was

prompted with results in a rather simple way and had to choose the required

information manually. The more data were added to the Web, the harder the

search for information became. The latest versions of search engines such as

Google provide a far more advanced search based on statistical evidences or

smart context comparisons and rank the results accordingly. However, the

users still have to choose the information they are interested in more or less

manually.

Being able to provide data in a rather unstructured or semi-structured

way is part of the problems with automatic information retrieval. This is the

situation behind the activities of the W3C concerning the Semantic Web. The

W3C defines the Semantic Web on their Web page as:

TEAM LinG

Introduction

“The Semantic Web is the abstract representation of data on the World

Wide Web, based on the RDF standards and other standards to be

defined. It is being developed by the W3C, in collaboration with a

large number of researchers and industrial partners.” [136]

The same page contains a definition of the Semantic Web that is of similar

importance. This definition has been created by [8] and states

“The Semantic Web is an extension of the current web in which infor-

mation is given well-defined meaning, better enabling computers and

people to work in cooperation.” [136]

These definitions indicate the Web of tomorrow. If data have a well-defined

meaning, engines will be able to intelligently seek, retrieve, and integrate

information and generate new knowledge to answer complex queries.

The retrieval and integration of information is the focus of this paper.

Before going into detail we would like to share some creative ideas, which can

be a vision of what we can expect from the Semantic Web.

1.1

Semantic Web Vision

Bernes-Lee et al. [8] already gave us an insight of what we should be able to

do with the help of data and engines working in the Web. In addition, the

following can help to see where researchers want to arrive in the future. These

ideas can be distinguished into four groups:

Short-term: The following tasks are not far away from being solved or,

are already solved to a certain extent.

Being able to reply on an email via telephone call: This requires com-

munication abilities between a phone and an email client. Nowadays,

the first solutions are available, however, vendors offer a complete so-

lution with a phone and an email client that come in one package with

more or less the same software. An example is the VoiceXML pack-

age from RoadNews

. The beauty of this point is that an arbitrary

email client and an arbitrary phone can be used. The main subject is

interoperability between address databases.

Meaningful browsing support: The idea behind this is that the browser

is smart enough to detect the subject the user is looking for. If for

instance, the user is looking for the program on television for a certain

day on a web page, the browser could support the user by offering

similar links to other web sites offering the same content.

http://www.w3.org/2001/sw/, no pagination, verified on Oct 17, 2002.

http://www.w3.org/2001/sw/

no pagination, verified on July 1st, 2003.

http://www.roadnews.com, verified on July, 1st, 2003.

TEAM LinG

1.1

Semantic Web Vision

Mid-term: These tasks are harder to solve and we believe that solutions

will be available in the next few years.

Planning appointments with colleagues by integrating diaries: This is

a problem already tackled by some researchers (e.g. [90]) and the

first solutions are available. Pages can be parsed to elicit relevant

information and through reference to published ontologies reasoning

support, it is possible to provide user assistance. However, this task

is not simple and many problems still have to be addressed. This

task serves as one example of the ongoing Semantic Web Challenge

(http://challenge.semanticweb.org).

Context-aware applications: Ubiquitous computing might serve as an-

other keyword in this direction. Context-awareness (cf. [49]) has to deal

with mobile computing, reduction of data, and useful abstraction (e.g.,

digital maps in an unknown city on a PDA).

Giving restrictions for a trip and getting the schedule and the booking:

The scenario behind this is giving a computer the constraints for a

vacation/trip. An agent is then supposed to check all the information

available on the Web, including the local travel agencies and make the

booking accordingly. Besides some severe technical problems, such as

technical interoperability between agencies, we also have to deal with

digital signatures and trust for the actual booking at this point. First

approaches include modern travel portals such as DanCenter

where

restrictions for a trip can be made and booking is also possible. This

issue will be postponed for now.

Long-term: Tasks in this group are again more difficult and the solutions

might emerge only in the next decade.

Information exchange between different devices: Suppose, we are surf-

ing the Web and see some movies we are interested in which will be

shown on television during the next few days. Theoretically, we are able

to directly take this information and program our VCR (e.g., WebTV

Oral communication with the Semantic Web: So far, plain commands

can be given via speech software to a computer. This tasks goes even

further: here, we think about the discussions of issues rather than plain

commands. We also anticipate inferences and interaction.

Lawn assistant: Use satellite and weather information from the Web,

background garden knowledge issued to program your personal lawn

assistant.

Never: Automatic fusion of large databases.

We can identify a number of difficult tasks that will most likely be difficult

to solve. The automatic fusion of large databases is an example for this. On

the other hand, we have already seen some solutions (or partly solutions) for

http://www.dancenter.com, verified on July, 1st, 2003.

http://about-the-web.com/shtml/WebTV.shtml, verified on June, 1st, 2003.

TEAM LinG

剩余164页未读，继续阅读

longzhu28

粉丝: 0
资源: 3

SCWCD教程：Java Web组件开发认证第二版

scwcd英语教材

SCWCD Exam Study Kit Java Web Component Develop及笔记

Java程序员哪些证书权威？

Oasys是一个使用Maven进行项目管理的OA办公自动化系统。该项目基于Spring B

peewee-3.15.0-cp310-cp310-win_amd64.whl

Delphi 12控件之FR安装工具24.7z

基于树莓派使用sht20采集温湿度信息，以JSON格式上传至MQTT，MQTT发布开关灯指令，树莓派执行指令操作

数据可视化面板-ECharts.zip

机器人上下楼梯控制系统的设计与实现

nlopt-2.7.1-cp38-cp38-win_amd64.whl

最新资源