How Does the Search Process Support Inquiry Learning?

Total Page:16

File Type:pdf, Size:1020Kb

How Does the Search Process Support Inquiry Learning? 2 ESSENTIAL QUESTIONS How does the search process support inquiry learning? What are the best instructional strategies to teach the search process? Which search engines best support students' searching and exploration? Searching the Web 23 Alisha slips off her iPod earbuds and sits down at the computer; she has about 15 minutes before she meets with her team. She's thinking about their last meeting when they brainstormed questions and discussed what they each knew about the topic. She pulls up the Research Wiki set up by Mr. Rodriquez, her teacher-librarian. He always uses a wiki so kids can work collaboratively in identifying the best search tools. A few of the search engines peak her interest as she scans the annotated list; she clicks on Quintura to see how the tag cloud is used. As she watches the screencast, she opens another window and follows along experimenting with different keywords. Satisfied that she has mastered the new search engine, she returns to Google remem­ bering a strategy Mr. Rodriquez recommended at the class research session- "type define: search term" to get definitions. She uses Google all the time but did not realize that it had advanced searching strategies. Cool, it worked! She scans the list of 20 or more definitions of global warming, looking at the URLs. She tags the Web page in her shared del.icio. us account to share with her teammates. She moves to another search tool, Ask.com. When the class was comparing search engines, she noticed that Ask.com had a great results page-it gave listings of videos and up-to-date news on the search term and offered suggestions to narrow and broaden the search. She clicks on "Ways to Stop Global Warming" and "News" and gets an annotated list of world news stories. Her eyes go to the lower side of the screen where she sees a listing of RSS news feeds for "Top Stories/' "World/' "United States/' "Science/' etc. Great, she thinks to herself ''I'm going to suggest that the team set up some news feeds on our global warming wiki. Why spend time searching for the information when it can come to you?" She makes a mental note to add that to the research wiki to alert other students to this feature. This will be a good start for her team. Before she leaves, she quickly reviews what she has gathered: definitions, videos, suggestions to narrow their search, related terms, and news feeds. Not bad for 20 minutes work, this will help her team focus their In addition to being the most popular search engine, Google topic and decide on the has a number of other great services that educators can use to essential questions they support student learning: Google Alert is an e-mail update service of the latest relevant want to investigate. With Google results (Web, news, etc.) based on your choice of query two minutes to spare, she or topic. checks her e-mail. Google Docs is a free Web-based word processor, spreadsheet, and presentations that allow you share and collaborate online. iGoogle is a start page tool where you can aggregate all the How Has Searching Google resources you use on your online desktop, e.g., Mail, Develop ed? Google Calendar.... Google Reader constantly checks your favorite news sites and The first Web site, created on blogs for new content and posts them to one easy page. August 6, 199 t by Tim Berners­ GMail is a free e-mail service that integrates with Google's other Lee, was also the fir t Web services. directory since he kept an ever­ Google Apps is a free communication, collaboration, and publish­ growing, categorized list of ing tools, including e-mail accounts on your school's domain (like [email protected]). Web sites that other peop le created. It became the WWW Virtual Library (http://vlib.org). Figure 2.2. Google: Not Just a Search Engine. 24 Choosing Web 2.0 Tools If Only Search engInes Could Understand What We Want In 1994, there were fewer than 10,000 Web sites, but by 1998, it had grown to approximately 3.5 million Web sites. Google, the search engin e with the goofy name and a new algo­ rithm that produced results that were more useful, was launched and took the largest sh,u:e of the search engine mar­ ket very quickly. Google now commands 60 percent of all searches worldwide. Yahoo! is a distant second with 14 per­ cen t and MSM Live is third Figure 2.3. YouTube Video "IfOnly Search Engines Could Understand with 4 percent of the market. What We Want" (http: //www.youtube.com/ w atch?v=qOBfp4URgWQ). Show this brief video to students as a conversation starter. Are their (You know a search engine is experiences using search engines similar? very popular when its name becomes a verb-Google it!) The idea of Web searching has been around for as long as the Internet itself, but only in the past several years did it catch on with the mainstream. Now, it is the sec­ ond most popular activity online, after e-mail (Pew In ternet). But things change quickly on the Web and if you think Google will always be leader of the pack, think again; history shows how quickly search engines users become fickle. Alta Vista was the favorite home page in 1995 due to its index that offered lightning fasts results, but it was quickly replaced by Google, who not only indexed Web pages but ranked pages by who linked to it. Luckily, there is always pressure to create the latest and the best search engine to capture the highest revenue. Using the latest and most innovative technologies, search engine companies are continuously competing to develop the best search engine. It's not surprising that many of the search engines being developed have unique features based on Web 2.0 characteristics. We don't often think of search engines as being Web 2.0 tools since they are not new technol­ ogies but recent changes and updates have brought about customization, social search capabilities, and expanded content. This aligns with Web 2.0' s characteristics that emphasize participation, publication, socialization, and sharing. Student Information Seeking Behavior Before we look at the search process, we need to look at our primary users, students. The ubiquitous nature of the Web and Google gives students an inflated sense of their abil­ ities when it comes to conducting online research. Just ask any student if they need help and they will say, "No, I'm fine" or "I'll just Google." Kathleen Tyner in her book Literacy in a Digital World categorizes literacies into two groups- toolliteracies which encompass computer, network, and technology; and literacies of representation that include informa­ tion, visual, and media. Kids often fool their teachers and sometimes themselves into think­ ing they are digitally literate because they have strong "tool" or computer skills; however, Searching the Web 25 they often lack "literacies of representation"-information literacy (Tyner 1998,94). The two are very distinct and different skills. Students expect a search engine to deliver accurate, analyzed answers, but it rarely, if ever, does. But even though students overrate their searching abilities and expect too much from the search engines, they are usually satisfied with their results; what they find is usually "good enough." Research shows that 93 percent of young people are sat­ isfied or very satisfied with their overall experience of using a search engine. However, research also tells us 72.3 percent of search engines users experience"search engine fatigue" either "always," "usually," or "sometimes" when researching a topic on the Internet (Sterling 2007). The report discusses user frustration with clutter and the content of search results: "When asked to name their #1 complaint about the process, 25 percent cited a deluge of results, 24 percent cited a predominance of commercial (paid) listings, 18.8 percent blamed the search engine's inability to understand their keywords (forcing them to try again), and 18.6 percent were most frustrated by disorganized/random results." There was also a desire among many users that search engines be able to read their minds. "The survey respondents were asked whether they wished that search engines like Google could, in effect, read their minds, delivering the results they were actually looking for .... That capability is something that 78 percent of all survey-takers 'wished' for, including 86.2 percent of 18-34 year-olds and 85 percent of those under 18." Although search engines can't read our minds, yet, innovation in the search industry is picking up. What we think of as "search" has expanded substantially in the last few years largely due to the new type of services offered and content that is ( available. Because of all the 5 recent advancemen ts in search ;, engine development, it's diffi­ d cult to categorize search engines ti into neat group s with specific it features and cap abilities since o most overlap in differen t ways. s Instead, what w have done in t this chapter is to group them into strategies that highbght their capability to help students be successful searchers and to make sense of the information they are finding. How D oes the Search Process Support Inquiry Learning? All of you, unfortunately, are faced with students doing topic research, such as a fi ve-p age Investigate paper on China or a PowerPoint presentation on the state bird. Figure 2.4. Stripling Inquiry Model. 26 Choosing Web 2.0 Tools The emphasis is on finding facts and cutting and pasting bits of information into some type of report with little real learning taking place.
Recommended publications
  • Rpa Demystified
    RPA in Action for Healthcare A Challenging Council Merger DECEMBER-JANUARY 2018 RPA DEMYSTIFIED OPEN EMAIL COPY PASTE REPEAT Print Post Approved: 100002740 Ensuring the Failure of Your Knowledge Management Efforts A records manager’s job is never done..with EzeScan! Ready To Help: 1300 EZESCAN (1300 393 722 ) www.ezescan.com.au Finance looks to a new path to digital According the new Finance Discussion Paper, “In early 2018, Finance undertook a 12-week Demonstration of Concept (the record-keeping nirvana Demonstration) to test the concept of automating records capture and categorisation via machine learning and semantic data technologies. Through the Demonstration, it was concluded that while the Government is best placed to describe its functions, industry is working towards automation and would be best placed to provide digital records management systems that would be compatible with the government developed Australian Government Records Interoperability Framework (AGRIF). One industry vendor responded, “I think this means they have decided it is all too hard and could one or more of you vendors do it for us at your cost but to our theoretical and incomplete design? “I guess it will be one of those government projects that goes on More than three years into its multi-million dollar quest to for years and years costing a fortune and then is finally cancelled revolutionise digital record-keeping practices across Federal because technology has passed it by.” government, Australia’s Department of Finance has announced There is also industry concern that the co-design approach another shift in direction and a “review” of the current (and this whole project overall) puts a disproportionately heavy moratorium on new investment in records management burden on SMEs.
    [Show full text]
  • Open Source Intelligence (OSINT) Link Directory Targeting Tomorrow’S Terrorist Today (T4) Through OSINT By: Mr
    Creative Commons Copyright © Ben Benavides—no commercial exploitation without contract June 2011 Country Studies Public Places Open Source Intelligence (OSINT) Link Directory Targeting Tomorrow’s Terrorist Today (T4) through OSINT by: Mr. E. Ben Benavides CounterTerrorism Infrastructure Money Laundering Gang Warfare Open Source Intelligence is the non-cloak- and-dagger aspect of fact collecting. (Alan D. Tompkins) Human Smuggling Weapon Smuggling IEDs/EFPs Creative Commons Copyright © Ben Benavides—no commercial exploitation without contract Table of Contents Table of Contents ........................................................................................................................ 2 Comments ................................................................................................................................... 7 Open Source Intelligence (OSINT): What It Is and What It Isn’t ................................................... 8 How To Use Open Source Intelligence ........................................................................................ 9 Key Army Access Sites .............................................................................................................. 17 Must Haves References ............................................................................................................ 18 Core Open Source Intelligence Documents & Guides ........................................................... 18 MI Officer Students ...............................................................................................................
    [Show full text]
  • OSINT) Analyst Overtly Passive / Covertly Active Surveillance / Reconnaissance Observation / Exploration Eye / Spy
    Open Source Intelligence (OSINT) Analyst Overtly Passive / Covertly Active Surveillance / Reconnaissance Observation / Exploration Eye / Spy PREFACE This deskside/pocket smartbook contains information to assist you, the open source intelligence analyst, in carrying out your research responsibilities in a Intelligence Oversightmanner that first of all adhere to intelligence oversight and follow the guide lines of AR 381-10, Executive Order 12333, and unit standard operating procedures (SOP). The second is to practice and implement effective operational security (OPSEC) measures during data and information collection activities online. A fine line exists between collection and acquisition, and examples will be pointed out throughout the handbook. This handout is not written specifically for the military active or passive OSINT Analyst but rather as an all-purpose guide for anyone doing research. The one big advantage for the passive OSINT Analyst is that it does not require interaction with the mark. Therefore, it poses little risk since it does not alert the target to the presence of the analyst. If a technique violates Intelligence Oversight and OPSEC, then common sense must take center stage. For those in the civilian community (law enforcement, journalists, researchers, etc.), you are bound by a different set of rules and have more latitude. One important thing to keep in mind is that when threats are mentioned the majority tend to think they are military in nature. We think of Iran, North Korea, and other countries with a military capability. That is not the case. Threats can be the lone wolf types, a disgruntled worker, someone calling in a bomb threat to a hospital, etc.
    [Show full text]
  • List Created By: Jonathan Kidder (Wizardsourcer.Com) Contact
    List created by: Jonathan Kidder (WizardSourcer.com) Contact Finding Extensions: Adorito: Email Lookup for LinkedIn. ​ Aeroleads Prospect Finder: Find Prospects and Send them to AeroLeads. ​ AmazingHiring: Search for social media profiles across the web. This tool helps ​ find personal contact information and so much more. Clearbit Connect: Find contact information on social media profiles. ​ Connectifier: Search for social media profiles and contact information across the ​ web. (Recently acquired by LinkedIn). Connectifier Social Links: Find social media profiles on individual LinkedIn ​ profiles. ContactOut: Find anyone's email and phone number on LinkedIn. ​ Evercontact: Is the highest-rated Contact Management App on Google Apps. ​ Hiretual: A sourcing tool that offers contact information and so much more. ​ Hunter: An extension that helps find corporate email addresses on LinkedIn ​ profiles. Improver: Find contact information from social media profiles. ​ Lead Generator: Get private emails of LinkedIn profiles and check their ​ willingness to change a job. Leadiq.io: Browse LinkedIn Profiles, AngelList Profiles, or grab LinkedIn search ​ results and import into Google Sheets. Lusha: Find contact information on individual LinkedIn profiles. ​ ManyContacts: Check any email address & discover Social Profiles. ​ MightySourcer: Helps find contact info. ​ People.Camp: Social Media Sourcing and Application/Lead Tracking Software. ​ People Finder: Find leads, get emails, phone numbers and other contact data. ​ Save and share your LinkedIn connections. People Search: Find contact information and resumes on social media profiles. ​ Prophet II: Find contact information from social media profiles. ​ SeekOut: Find contact information from social media profiles. ​ Sellhack: Sales Helper - Social profiles add on to gather additional info about ​ leads. SignalHire: Find contact information on individual social media profiles.
    [Show full text]
  • Comparison of Web Search Engines Using User-Based Metrics in Survey Statistics *Ogunyinka, P
    Futo Journal Series (FUTOJNLS) e-ISSN : 2476-8456 p-ISSN : 2467-8325 Volume-6, Issue-2, pp- 190 - 200 www.futojnls.org Research Paper December 2020 Comparison of web search engines using user-based metrics in survey statistics *Ogunyinka, P. I.1, Aigbogun, L. I.1, Iheanyichukwu, B. F.2, Ekundayo, O. M.3, Banjo, O.1, Olubanwo, O. O.1 and Dehinsilu, O. A.1 1Department of Mathematical Sciences, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria. 2Olabisi Onabanjo University Library, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria. 3Department of Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria. *Corresponding Author’s Email: [email protected] Abstract Different web search engines had been rated based on different metrics. However, almost none had considered the search query length, the retrieved quantity and retrieval time for evaluation of web search engines. This study had rated five web search engines (Google, Yahoo, WOW, AOL and Bing) using non-parametric Kruskal-Wallis test for significant mean difference and single-phase sampling for regression estimation and examination of internal error. The retrieval time was used as the study variable while the retrieved quantity of the organic search results and the search query length were used as the auxiliary variables. The correlation coefficient, mean square error, percentage coefficient of variation and percentage relative efficiency were used for the evaluation and comparison of the estimated population mean of the retrieval time. Results revealed that Google was the most rated web search engine with the highest significant retrieved quantity and significant retrieval time while Bing was the least rated web search engine.
    [Show full text]
  • List of Search Engines
    A blog network is a group of blogs that are connected to each other in a network. A blog network can either be a group of loosely connected blogs, or a group of blogs that are owned by the same company. The purpose of such a network is usually to promote the other blogs in the same network and therefore increase the advertising revenue generated from online advertising on the blogs.[1] List of search engines From Wikipedia, the free encyclopedia For knowing popular web search engines see, see Most popular Internet search engines. This is a list of search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites that have a search facility for online databases. Contents 1 By content/topic o 1.1 General o 1.2 P2P search engines o 1.3 Metasearch engines o 1.4 Geographically limited scope o 1.5 Semantic o 1.6 Accountancy o 1.7 Business o 1.8 Computers o 1.9 Enterprise o 1.10 Fashion o 1.11 Food/Recipes o 1.12 Genealogy o 1.13 Mobile/Handheld o 1.14 Job o 1.15 Legal o 1.16 Medical o 1.17 News o 1.18 People o 1.19 Real estate / property o 1.20 Television o 1.21 Video Games 2 By information type o 2.1 Forum o 2.2 Blog o 2.3 Multimedia o 2.4 Source code o 2.5 BitTorrent o 2.6 Email o 2.7 Maps o 2.8 Price o 2.9 Question and answer .
    [Show full text]
  • Optimizing Click-Through in Online Rankings for Partially Anonymous Consumers∗
    Optimizing Click-through in Online Rankings for Partially Anonymous Consumers∗ Babur De los Santosy Sergei Koulayevz November 15, 2014 First Version: December 21, 2011 Abstract Consumers incur costly search to evaluate the increasing number of product options avail- able from online retailers. Presenting the best alternatives first reduces search costs associated with a consumer finding the right product. We use rich data on consumer click-stream behavior from a major web-based hotel comparison platform to estimate a model of search and click. We propose a method of determining the hotel ordering that maximizes consumers' click-through rates (CTRs) based on partial information available to the platform at that time of the con- sumer request, its assessment of consumers' preferences, and the expected consumer type based on request parameters from the current visit. Our method has two distinct advantages. First, rankings are targeted to anonymous consumers by relating price sensitivity to request param- eters, such as the length of stay, number of guests, and day of the week of the stay. Second, we take into account consumer response to new product ordering through the use of search refinement tools, such as sorting and filtering of product options. Product ranking and search actions together shape the consideration set from which clicks are made. We find that predicted CTR under our proposed ranking are almost double those under the online platform's default ranking. Keywords: consumer search, hotel industry, popularity rankings, platform,
    [Show full text]
  • Download Download
    International Journal of Management & Information Systems – Fourth Quarter 2011 Volume 15, Number 4 History Of Search Engines Tom Seymour, Minot State University, USA Dean Frantsvog, Minot State University, USA Satheesh Kumar, Minot State University, USA ABSTRACT As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google Ad Words program. By 2007, pay-per-click programs proved to be primary money-makers for search engines. In a market dominated by Google, in 2009 Yahoo! and Microsoft announced the intention to forge an alliance. The Yahoo! & Microsoft Search Alliance eventually received approval from regulators in the US and Europe in February 2010. Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunities offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals.
    [Show full text]
  • Inclusiva-Net Nuevas Dinámicas Artísticas En Modo Web 2
    Inclusiva-net Nuevas dinámicas artísticas en modo web 2 Primer encuentro Inclusiva-net Dirigido por Juan Martín Prada Julio, 2007. MEDIALAB-PRADO · Madrid www.medialab-prado.es ISBN: 978-84-96102-35-4 Edita: Área de las Artes. Dirección General de Promoción y Proyectos Culturales. Madrid. 2007 © de esta edición electrónica 2007: Ayuntamiento de Madrid © Textos e imágenes: los autores ÍNDICE Prefacio Juan Martín Prada 5 La “Web 2.0” como nuevo contexto para las prácticas artísticas Juan Martín Prada 6 Isubmit, Youprofile, WeRank La deconstrucción del mito de la Web 2.0 Geert Lovink 23 Telepatía colectiva 2.0 (Teoría de las multitudes interconectadas) José Luis Brea 39 Deslices de un avatar: prestidigitación y praxis artística en Second Life Mario-Paul Martínez Fabre y Tatiana Sentamans 55 Escenarios emergentes en las prácticas sociales y artísticas con tecnologías móviles Efraín Foglia 82 El artista como generador de swarmings. Cuestionando la sociedad red Carlos Seda 93 Procesos culturales en red Perspectivas para una política cultural digital Ptqk (Maria Perez) 110 Fósiles y monstruos: comunidades y redes sociales artísticas en el Estado Español Lourdes Cilleruelo 126 Tempus Fugit Cuando arte y tecnología encuentran a la persona equivocada Raquel Herrera 138 Impacto de las tecnologías web 2.0 En la comunicación cultural Javier Celaya 149 “No List Available” Web 2.0 para rescatar a los museos libios del olvido institucional. Prototipo para el Museo Jamahiriya de Trípoli lamusediffuse 158 “Arquitecturapública”: El concurso de arquitectura
    [Show full text]
  • Web Search Engine
    Web Search Engine Bosubabu Sambana, MCA, M.Tech Assistant Professor, Dept of Computer Science & Engineering, Simhadhri Engineering College, Visakhapatnam, AP-531001, India. Abstract: This hypertext pool is dynamically changing due to this reason it is more difficult to find useful The World Wide Web (WWW) allows people to share information.In 1995, when the number of “usefully information or data from the large database searchable” Web pages was a few tens of millions, it repositories globally. We need to search the was widely believed that “indexing the whole of the information with specialized tools known generically Web” was already impractical or would soon become as search engines. There are many search engines so due to its exponential growth. A little more than a available today, where retrieving meaningful decade later, the GYM search engines—Google, information is difficult. However to overcome this problem of retrieving meaningful information Yahoo!, and Microsoft—are indexing almost a intelligently in common search engines, semantic thousand times as much data and between them web technologies are playing a major role. In this providing reliable sub second responses to around a paper we present a different implementation of billion queries a day in a plethora of languages. If this semantic search engine and the role of semantic were not enough, the major engines now provide much relatedness to provide relevant results. The concept higher quality answers. of Semantic Relatedness is connected with Wordnet which is a lexical database of words. We also For most searchers, these engines do a better job of made use of TF-IDF algorithm to calculate word ranking and presenting results, respond more quickly frequency in each and every webpage and to changes in interesting content, and more effectively Keyword Extraction in order to extract only useful eliminate dead links, duplicate pages, and off-topic keywords from a huge set of words.
    [Show full text]
  • OSINT Handbook September 2020
    OPEN SOURCE INTELLIGENCE TOOLS AND RESOURCES HANDBOOK 2020 OPEN SOURCE INTELLIGENCE TOOLS AND RESOURCES HANDBOOK 2020 Aleksandra Bielska Noa Rebecca Kurz, Yves Baumgartner, Vytenis Benetis 2 Foreword I am delighted to share with you the 2020 edition of the OSINT Tools and Resources Handbook. Once again, the Handbook has been revised and updated to reflect the evolution of this discipline, and the many strategic, operational and technical challenges OSINT practitioners have to grapple with. Given the speed of change on the web, some might question the wisdom of pulling together such a resource. What’s wrong with the Top 10 tools, or the Top 100? There are only so many resources one can bookmark after all. Such arguments are not without merit. My fear, however, is that they are also shortsighted. I offer four reasons why. To begin, a shortlist betrays the widening spectrum of OSINT practice. Whereas OSINT was once the preserve of analysts working in national security, it now embraces a growing class of professionals in fields as diverse as journalism, cybersecurity, investment research, crisis management and human rights. A limited toolkit can never satisfy all of these constituencies. Second, a good OSINT practitioner is someone who is comfortable working with different tools, sources and collection strategies. The temptation toward narrow specialisation in OSINT is one that has to be resisted. Why? Because no research task is ever as tidy as the customer’s requirements are likely to suggest. Third, is the inevitable realisation that good tool awareness is equivalent to good source awareness. Indeed, the right tool can determine whether you harvest the right information.
    [Show full text]
  • Members' Library Finding Information Online January 2011
    Members' Library Finding information online January 2011 The National Assembly for Wales is the democratically elected body that represents the interests of Wales and its people, makes laws for Wales and holds the Welsh Government to account. Members' Library Finding information online January 2011 Finding information online This guide is intended to help Assembly Members, their support staff and Assembly officials find useful information quickly when searching the internet. Different types of search engines and online directories are included, followed by information on creating a strong search strategy and evaluating websites. Lastly, further sources of information and useful links are listed. The basics Search engines Search engines do not search the Search engines are useful when you know what you are looking for World Wide Web directly. Each one and can define it in a few keywords or phrases. searches a database of web pages Popular search engines include: that they have already collected and stored using spiders which “crawl” Altavista the internet looking for new web http://uk.altavista.com/ pages. Bing (Microsoft’s search engine) When a user clicks on the links http://www.bing.com/?mkt=en-gb provided in a search engine's search Exalead results, they retrieve the current http://www.exalead.com/search/ version of the page. Duckduckgo Many web pages are excluded from http://duckduckgo.com/ search engines, including most Google library catalogues and article http://www.google.co.uk/ databases, because search engine Google: Welsh language interface: spiders cannot access them. This http://www.google.co.uk/webhp?hl=cy material is referred to as the invisible web as it cannot be “seen” by search Yahoo engines.
    [Show full text]