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"The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Readers will find that the second edition includes significant changes that bring the text up to date on current information retrieval methods. For example, the authors have added a completely new chapter on link-structure algorithms used in search engines such as Google, and the chapter on user interface has been rewritten to specifically focus on search engine usability. To reflect updates in the literature on information retrieval, the authors have added new recommendations for further reading and expanded the bibliography. In addition, the index has been updated and streamlined to make it more reader friendly."

"Keeping up with the ever-growing Web, along with professional resources and information for customers, can be an overwhelming challenge for busy librarians. Combine that with the fact that up to 60 percent of web data is "invisible" to search engines, and suddenly staying current seems like a losing battle, without enough hours in the day. What if you could keep current in one hour per day or less? What if you didn't have to surf? What if the information you selected proactively arrived in your inbox? What if you had effective sorting and saving tools to capture your preferred portion of this flood of data? Illustrating ways to overcome the daunting deluge of information, author and librarian Steven Cohen shows you how to use all the new cool tools. An early adapter and passionate proponent of cutting-edge technology to access and organize information, Cohen is the librarian's very own web guy search engine."

"Academic search e ngines, intends to run through the current panorama of the academic search engines through a quantitative approach that analyses the reliability and consistence of these services. The objective is to describe the main characteristics of these engines, to highlight their advantages and drawbacks, and to discuss the implications of these new products in the future of scientific communication and their impact on the research measurement and evaluation. In short, Academic search engines presents a summary view of the new challenges that the Web set to the scientific activity through the most novel and innovative searching services available on the web."