“The title tag is critical. It’s important not to overcomplicate your design and technical approach with things such as Flash, Java, frames and dynamically built websites.” (Gerry McGovern)

“(…) in 10 years, we will look back on todays search interfaces and recognize them as a simple and limited way to interact with information. After all, she explains, a 5-inch-long rectangle with a long list of text results beneath it doesnt do much to help people make sense of the billions upon billions of unorganized bits of data in the world.” (Susan Dumais – Microsoft Research) – courtesy of usability in the news

“Search optimization is about getting links. The more links you get to your website, the more likely you are to get into the first page of search engine results.” (Gerry McGovern)

“Search optimization focuses on how people search. Search engine optimization focuses on how search engines work. Search optimization sees quality web content as its foundation stone.” (Gerry McGovern)

“We propose a new method to extract semantic knowledge from the World Wide Web for both supervised and unsupervised learning using the Google search engine in an unconventional manner.” (Rudi Cilibrasi and Paul M. B. Vitanyi – CWI, University of Amsterdam)

“Deluged with superfluous responses to online queries, users will soon benefit from improved search engines that deliver customized results.” (Scientific American) – courtesy of ui designer

“For many years researchers in library and information science have borrowed theory from other fields to provide insight into our research findings. We are moving from this borrowed theory approach to creating a conceptual framework that has been tested, refined and adapted specifically for application in our field. The conceptual framework has developed rapidly during the past ten years with early signs of application in other fields.” – Papers presented at the 5th Information Seeking in Context Conference, Dublin, Ireland, 1-3 September, 2004 (Carol C. Kuhlthau – Information Research, January 2005)

“The paper addresses the issue of how online natural language question answering, based on deep semantic analysis, may compete with currently popular keyword search, open domain information retrieval systems, covering a horizontal domain. We suggest the multiagent question answering approach, where each domain is represented by an agent which tries to answer questions taking into account its specific knowledge. The meta–agent controls the cooperation between question answering agents and chooses the most relevant answer(s). We argue that multiagent question answering is optimal in terms of access to business and financial knowledge, flexibility in query phrasing, and efficiency and usability of advice. The knowledge and advice encoded in the system are initially prepared by domain experts.” (Boris Galitsky – First Monday January 2005)

“This is perhaps the Holy Grail of search, understanding what it is you are looking for and providing it quickly. The problem is that no one yet knows how to get there.” (BBC News)

“Why is this huge? Because the biggest problem with search as it exists today is that users can’t know what lies on the other side of that Submit button. It could be nothing, it could be just what they are looking for – how to know ahead of time?” (Brett Lider – every breath death defying)

“Search for videos across the web.” (Yahoo!) – courtesy of searchblog

“It is increasingly recognised in the modern enterprise that getting the processes of searching for and retrieving information right in a business can deliver a vital competitive edge. In a knowledge based economy employees who can’t find vital internal information about their jobs are less productive, and with the advent of the web, potential customers who can’t get straight to the information they need are only a click away from a competitor’s site.” (Martin Belam – currybetdotnet)

“This paper discusses the research into information seeking and its directions at a general level. We approach this topic by analysis and argumentation based on past research in the domain. We begin by presenting a general model of information seeking and retrieval which is used to derive nine broad dimensions that are needed to analyze information seeking and retrieval. Past research is then contrasted with the dimensions and shown not to cover the dimensions sufficiently. Based on an analysis of the goals of information seeking research, and a view on human task performance augmentation, it is then shown that information seeking is intimately associated with, and dependent on, other aspects of work; tasks and technology included. This leads to a discussion on design and evaluation frameworks for information seeking and retrieval, based on which two action lines are proposed: information retrieval research needs extension toward more context and information seeking research needs extension towards tasks and technology.” (Kalervo Järvelin and Peter Ingwersen – Information Research, Vol. 10 No. 1, October 2004)

“With a theoretical limit on the amount of information we can possibly consume, finding the information both on the internet and on your own computers can be a daunting task. Recently, there’s been a lot of attention on search.” (Kevin Cheng – OK/Cancel)

“In the work reported here, we present a new way of performing fault-tolerant fulltext retrieval on large text corpora, such as scientific encyclopedias.” (Wolfram M. Esser – Journal of Digital Information 6.1)

“Search is not restricted to entering a text field and getting back a collection of links” (Daniel H. Steinberg – Web 2.0)

“The vast amount of information on the Internet is growing every day – it’s enough to gag a Google search. Researcher Ramesh Jain offers up new strategies for information retrieval.” (ACM Ubiquity)

“Search engines are unreliable tools for data collection for research that aims to reconstruct the historical record. This unreliability is not caused by sudden instabilities of search engines. On the contrary, their operational stability in systematically updating the Internet is the cause. We show how both Google and Altavista systematically relocate the time stamp of Web documents in their databases from the more distant past into the present and the very recent past. They also delete documents. We show how this erodes the quality of information. The search engines continuously reconstruct competing presents that also extend to their perspectives on the past. This has major consequences for the use of search engine results in scholarly research, but gives us a view on the various presents and pasts living side by side in the Internet.” (Paul Wouters et al. – First Monday 9.10)

“This article describes the journey from the conception of and vision for a modern search-engine-based search environment to its technological realisation. In doing so, it takes up the thread of an earlier article on this subject, this time from a technical viewpoint. As well as presenting the conceptual considerations of the initial stages, this article will principally elucidate the technological aspects of this journey.” (Friedrich Summann and Norbert Lossau – D-Lib Magazine) – courtesy of chris mcevoy

“The current emphasis on content management is not about content management at all but rather about content publishing – and there is a difference. Organizations are aware of the problems in getting current, reliable information into an intranet but feel that their responsibility stops with building the repository and providing some templates for page display. Far too little attention is paid to the fact that unless people can find the information, the effort to add it to the repository and to make the look consistent is wasted.” (Martin White – EContent) – courtesy of uidesigner