Over the last several years, computing systems based on adaptive learning with fine-grained parallel architectures have moved from obscurity to front-page prominence. These systems derive some of their novel architecture from ideas gleaned from biology, hence the name “neural network”. Although many of the ideas behind this field are not new, improved computing hardware, better understanding of learning algorithms, and limitations of traditional approaches have combined to renew interest in neural nets.
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The paper presents a new approach to source code exploration, which is the result of integrating the Google Desktop Search (GDS) engine into the Eclipse development environment. The resulting search engine, named Google Eclipse Search (GES), provides improved searching in Eclipse software projects.
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Traditionally, Microsoft’s core business has been focused on the Windows platform and the Office suite. Windows and Office, by all means, continue to be the heart of Microsoft. The latest versions of the flagship products, Windows Vista and the Office 2007 System, made available to the public at the end of January 2007, have fueled the vast majority of the company’s most recent fiscal second quarter record financial results of $16.37 billion in revenue, and $6.48 billion in operating income. With Office SP1 out of the way at the end of 2007, Microsoft is currently building Windows Vista Service Pack 1, Windows XP Service Pack 3 and Windows 7 client platforms, as well as putting the finishing touches on Windows Server 2008.
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Newspapers are struggling with harsh economic realities, and are seeking creative new revenue sources while transitioning from their traditional print-centric business model, to where their audience has migrated – the Internet.

A major part of this transition involves newspaper companies producing greater amounts of video content online. Some are hoping the proven high engagement rates of video will generate to their websites greater traffic levels, longer time spent, and more follow-through actions from visitors – all with the ultimate goal of more revenue from advertisers, and overall monetization.
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To those of us whose passion for the growth of the World Wide Web is exceeded only by the marketing possibilities that emerge from that growth, the Internet has become a playground for the imagination. There is a large number of marketers, however, who are fascinated by the Web but approach its marketing capabilities more out of necessity than lifestyle. The Internet’s capacity has advanced in so many areas in the past few years that marketers playing catch-up are at a significant disadvantage. Marketing directors and account managers with traditional media backgrounds need to expand their breadth of knowledge in order to make informed decisions in today’s e-commerce.
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Current search engines such as Google and Yahoo! are prevalent for searching the Web. Search in dynamic pages, however, is either inexistent or far from perfect. AJAX and Rich Internet Application are such applications. They are increasingly frequent on the Web (in YouTube, Amazon, GMail, Yahoo!Mail) or mobile devices and are offering a high degree of interactivity to the user, by seamlessly loading content from the server without the need to refresh the page. Current search engines cannot correctly index AJAX applications. This produces false positives and false negatives, because search engines do not understand the application logic that loads content dynamically. Crawling an AJAX application is a difficult problem. Since the user invokes events on the page, crawling must identify the different application states generated by the client-side logic.
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Most of the current methodologies for building ontologies rely on specialized knowledge engineers. This is in contrast to real-world settings, where the need for maintenance of domain specific ontologies emerges in the daily work of users. But in order to allow for participatory ontology engineering, we need to have a more realistic conceptual model of how ontologies develop in the real world. We introduce the ontology maturing processes which is based on the insight that ontology engineering is a collaborative informal learning process and for which we analyze characteristic evolution steps and triggers that have users engage in ontology engineering within their everyday work processes.
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Web 2.0 is the term used for web based applications that allow more interaction and collaboration between users. Examples of Web 2.0 technology are blogs, wikis, podcasts, RSS feeders and interactive websites, such as YouTube and SecondLife. These resources can be searched for information that you can use for papers and projects.
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