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Internet Training: the Basics. INSTITUTION Temple Univ., Philadelphia, PA
DOCUMENT RESUME ED 424 360 CE 077 241 AUTHOR Gallo, Gail; Wechowski, Chester P. TITLE Internet Training: The Basics. INSTITUTION Temple Univ., Philadelphia, PA. Center for Vocational Education Professional Personnel Development. PUB DATE 1998-04-00 NOTE 27p. PUB TYPE Guides Non-Classroom (055) EDRS PRICE MF01/PCO2 Plus Postage. DESCRIPTORS Adult Education; Educational Needs; *Information Sources; *Online Systems; Postsecondary Education; Secondary Education; Teaching Methods; Vocational Education Teachers; *World Wide Web IDENTIFIERS Web Sites ABSTRACT This paper outlines the basic information teachers need to . know to use the World Wide Web for research and communication, using Netscape 3.04. Topics covered include the following: what is the World Wide Web?; what is a browser?; accessing the Web; moving around a web document; the Uniform Resource Locator (URL); Bookmarks; saving and printing a web page; Netscape's options preferences menu; searching the Web; and interesting places (websites of interest to vocational educators) .Two appendixes contain the following: "Infoseek: How Do I Search? 'Ruby Slippers'" and Guidelines for Completing Abstracts. (KC) ******************************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ***********************************************************************i******** t. The Center for Vocational Education \I/ Professional Personnel Development/ \ INTERNET TRAINING: THE BASICS Developed by Gail Gallo Project Director Chester P. Wichowski Temple University April, 1998 ./1.S. DEPARTMENT OFEDUCATION /ffice of Educational Research and Improvement PERMISSION TO REPRODUCE AND E UCATIONAL RESOURCES INFORMATION DISSEMINATE THIS MATERIAL HAS CENTER (ERIC) BEEN GRANTED BY This document has been reproduced as received from the person or organization originating it. 0 Minor changes have been made to improve reproduction quality. -
Market Research SD-5 Gathering Information About Commercial Products and Services
Market Research SD-5 Gathering Information About Commercial Products and Services DEFENSE STANDARDIZATION PROGRA M JANUARY 2008 Contents Foreword 1 The Market Research Other Considerations 32 Background 2 Process 13 Amount of Information Strategic Market Research to Gather 32 What Is Market Research? 2 (Market Surveillance) 14 Procurement Integrity Act 32 Why Do Market Research? 2 Identify the Market or Market Paperwork Reduction Act 33 Segment of Interest 14 When Is Market Research Cost of Market Research 34 Done? 5 Identify Sources of Market Information 16 Who Should Be Involved In Market Research? 7 Collect Relevant Market Other Information Information 17 Technical Specialist 8 Document the Results 18 on Market Research 35 User 9 Logistics Specialist 9 Tactical Market Research Appendix A 36 (Market Investigation) 19 Testing Specialist 9 Types of Information Summarize Strategic Market Available on the Internet Cost Analyst 10 Research 19 Legal Counsel 10 Formulate Requirements 20 Appendix B 39 Contracting Officer 10 Web-Based Information Identify Sources of Sources Information 21 Guiding Principles 11 Collect Product or Service Appendix C 47 Examples of Tactical Start Early 11 Information from Sources 22 Collect Information from Information Define and Document Product or Service Users 26 Requirements 11 Evaluate the Data 27 Refine as You Proceed 12 Document the Results 30 Tailor the Investigation 12 Repeat as Necessary 12 Communicate 12 Involve Users 12 Foreword The Department of Defense (DoD) relies extensively on the commercial market for the products and services it needs, whether those products and services are purely commercial, modified for DoD use from commercial products and services, or designed specifically for DoD. -
Evaluation of Web-Based Search Engines Using User-Effort Measures
Evaluation of Web-Based Search Engines Using User-Effort Measures Muh-Chyun Tang and Ying Sun 4 Huntington St. School of Information, Communication and Library Studies Rutgers University, New Brunswick, NJ 08901, U.S.A. [email protected] [email protected] Abstract This paper presents a study of the applicability of three user-effort-sensitive evaluation measures —“first 20 full precision,” “search length,” and “rank correlation”—on four Web-based search engines (Google, AltaVista, Excite and Metacrawler). The authors argue that these measures are better alternatives than precision and recall in Web search situations because of their emphasis on the quality of ranking. Eight sets of search topics were collected from four Ph.D. students in four different disciplines (biochemistry, industrial engineering, economics, and urban planning). Each participant was asked to provide two topics along with the corresponding query terms. Their relevance and credibility judgment of the Web pages were then used to compare the performance of the search engines using these three measures. The results show consistency among these three ranking evaluation measures, more so between “first 20 full precision” and search length than between rank correlation and the other two measures. Possible reasons for rank correlation’s disagreement with the other two measures are discussed. Possible future research to improve these measures is also addressed. Introduction The explosive growth of information on the World Wide Web poses a challenge to traditional information retrieval (IR) research. Other than the sheer amount of information, some structural factors make searching for relevant and quality information on the Web a formidable task. -
How to Choose a Search Engine Or Directory
How to Choose a Search Engine or Directory Fields & File Types If you want to search for... Choose... Audio/Music AllTheWeb | AltaVista | Dogpile | Fazzle | FindSounds.com | Lycos Music Downloads | Lycos Multimedia Search | Singingfish Date last modified AllTheWeb Advanced Search | AltaVista Advanced Web Search | Exalead Advanced Search | Google Advanced Search | HotBot Advanced Search | Teoma Advanced Search | Yahoo Advanced Web Search Domain/Site/URL AllTheWeb Advanced Search | AltaVista Advanced Web Search | AOL Advanced Search | Google Advanced Search | Lycos Advanced Search | MSN Search Search Builder | SearchEdu.com | Teoma Advanced Search | Yahoo Advanced Web Search File Format AllTheWeb Advanced Web Search | AltaVista Advanced Web Search | AOL Advanced Search | Exalead Advanced Search | Yahoo Advanced Web Search Geographic location Exalead Advanced Search | HotBot Advanced Search | Lycos Advanced Search | MSN Search Search Builder | Teoma Advanced Search | Yahoo Advanced Web Search Images AllTheWeb | AltaVista | The Amazing Picture Machine | Ditto | Dogpile | Fazzle | Google Image Search | IceRocket | Ixquick | Mamma | Picsearch Language AllTheWeb Advanced Web Search | AOL Advanced Search | Exalead Advanced Search | Google Language Tools | HotBot Advanced Search | iBoogie Advanced Web Search | Lycos Advanced Search | MSN Search Search Builder | Teoma Advanced Search | Yahoo Advanced Web Search Multimedia & video All TheWeb | AltaVista | Dogpile | Fazzle | IceRocket | Singingfish | Yahoo Video Search Page Title/URL AOL Advanced -
Multitasking Web Search on Alta Vista
1 Multitasking Web Search on Alta Vista Amanda Spink* & Bernard J. Jansen Minsoo Park School of Info Sciences and Jan Pedersen School of Information Technology Chief Scientist Sciences The Pennsylvania State Overture Web Search University of Pittsburgh University Division 610 IS Building, 135 N. 4P Thomas Building 1070 Arastradero Road Bellefield Avenue University Park PA 16802 Palo Alto, CA 94304 Pittsburgh PA 15260 Tel: (814) 865-6459 [email protected] Tel: (412) 624-9454 Fax: (814) 865-6424 Fax: (412) 648-7001 E-mail: [email protected] E-mail: [email protected],edu * To whom all correspondence should be addressed. Ozmutlu [8] show that IR searches often include Abstract multiple topics, during a single search session or A user’s single session with a Web search engine multitasking search. Spink, Batemen and Greisdorf may consist of seeking information on single or [9] found that eleven (3.8%) of the 287 Excite users multiple topics. Most Web search sessions consist of responding to a Web-based survey reported two queries of two words. We present findings from a multitasking searches. However, limited knowledge study of two-query search sessions on the Alta Vista exists on the characteristics and patterns of Web search engine to examine the degree of multitasking searches. Recent studies have examined multitasking search by typical web searchers. A multitasking searching on the Excite and sample of two-query length search sessions were AlltheWeb.com Web search engines [10, 11]. filtered from Alta Vista transaction logs from 2003. Ozmutlu, Ozmutlu and Spink [10] provide a Findings include: (1) 81% of two-query sessions detailed analysis of multitasking sessions on were multitasking searches, and (2) there are a broad AlltheWeb.com. -
The Deep Web: Surfacing Hidden Value
White Paper The Deep Web: Surfacing Hidden Value BrightPlanet.com LLC July 2000 The author of this study is Michael K. Bergman. Editorial assistance was provided by Mark Smither; analysis and retrieval assistance was provided by Will Bushee. This White Paper is the property of BrightPlanet.com LLC. Users are free to distribute and use it for personal use.. Some of the information in this document is preliminary. BrightPlanet plans future revisions as better information and documentation is obtained. We welcome submission of improved information and statistics from others involved with the “deep” Web. Mata Hari® is a registered trademark and BrightPlanet™, CompletePlanet™, LexiBot™, search filter™ and A Better Way to Search™ are pending trademarks of BrightPlanet.com LLC. All other trademarks are the respective property of their registered owners. © 2000 BrightPlanet.com LLC. All rights reserved. Summary BrightPlanet has uncovered the “deep” Web — a vast reservoir of Internet content that is 500 times larger than the known “surface” World Wide Web. What makes the discovery of the deep Web so significant is the quality of content found within. There are literally hundreds of billions of highly valuable documents hidden in searchable databases that cannot be retrieved by conventional search engines. This discovery is the result of groundbreaking search technology developed by BrightPlanet called a LexiBot™ — the first and only search technology capable of identifying, retrieving, qualifying, classifying and organizing “deep” and “surface” content from the World Wide Web. The LexiBot allows searchers to dive deep and explore hidden data from multiple sources simultaneously using directed queries. Businesses, researchers and consumers now have access to the most valuable and hard- to-find information on the Web and can retrieve it with pinpoint accuracy. -
Meta Search Engine with an Intelligent Interface for Information Retrieval on Multiple Domains
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.1, No.4, October 2011 META SEARCH ENGINE WITH AN INTELLIGENT INTERFACE FOR INFORMATION RETRIEVAL ON MULTIPLE DOMAINS D.Minnie1, S.Srinivasan2 1Department of Computer Science, Madras Christian College, Chennai, India [email protected] 2Department of Computer Science and Engineering, Anna University of Technology Madurai, Madurai, India [email protected] ABSTRACT This paper analyses the features of Web Search Engines, Vertical Search Engines, Meta Search Engines, and proposes a Meta Search Engine for searching and retrieving documents on Multiple Domains in the World Wide Web (WWW). A web search engine searches for information in WWW. A Vertical Search provides the user with results for queries on that domain. Meta Search Engines send the user’s search queries to various search engines and combine the search results. This paper introduces intelligent user interfaces for selecting domain, category and search engines for the proposed Multi-Domain Meta Search Engine. An intelligent User Interface is also designed to get the user query and to send it to appropriate search engines. Few algorithms are designed to combine results from various search engines and also to display the results. KEYWORDS Information Retrieval, Web Search Engine, Vertical Search Engine, Meta Search Engine. 1. INTRODUCTION AND RELATED WORK WWW is a huge repository of information. The complexity of accessing the web data has increased tremendously over the years. There is a need for efficient searching techniques to extract appropriate information from the web, as the users require correct and complex information from the web. A Web Search Engine is a search engine designed to search WWW for information about given search query and returns links to various documents in which the search query’s key words are found. -
Resources for Patrons
Part 1 Ready Reference on the Web: Resources for Patrons Quick! What is the best Web resource for finding a good vacuum cleaner? Getting information for a grade-school “state” report? Finding a life-saving clinical trial? People just walk up to our desks and ask us these questions every day. And we are expected to answer them in seconds, not minutes or hours. For heaven’s sake! How are we supposed to know? Well, as Robert W. Winter, Arthur G. Coons Professor of the History of Ideas, Emeritus at Occidental College in Los Angeles once told our class, “A liberal arts education will teach you what you don’t know.” In other words, as educated people, as librarians, we know that we don’t know everything, yet we are armed with tools to find out about anything. My hope is that the first section of this book can serve as one of those tools. I have tried to cover some of the most asked subject areas that I encounter every day on the job. I also point to directo- ries of high-quality sites that can quickly connect librarians and their patrons to the answers that they need. These listings may not answer every question. But I guarantee you, if you can learn to turn to them first, your patrons will hail your alacrity and brilliance. And isn’t this glory what we librarians live for? 7 Chapter 1 Searching and Meta-Searching the Internet The topic of searching the Web puts me in an elegiac mood. I think back to 1994 when I was first playing with the Web during my library school internship at the Getty Research Institute. -
Meta Search Engine Examples
Meta Search Engine Examples mottlesMarlon istemerariously unresolvable or and unhitches rice ichnographically left. Salted Verney while crowedanticipated no gawk Horst succors underfeeding whitherward and naphthalising. after Jeremy Chappedredetermines and acaudalfestively, Niels quite often sincipital. globed some Schema conflict can be taken the meta descriptions appear after which result, it later one or can support. Would result for updating systematic reviews from different business view all fields need to our generated usually negotiate the roi. What is hacking or hacked content? This meta engines! Search Engines allow us to filter the tons of information available put the internet and get the bid accurate results And got most people don't. Best Meta Search array List The Windows Club. Search engines have any category, google a great for a suggestion selection has been shown in executive search input from health. Search engine name of their booking on either class, the sites can select a search and generally, meaning they have past the systematisation of. Search Engines Corner Meta-search Engines Ariadne. Obsession of search engines such as expedia, it combines the example, like the answer about search engines out there were looking for. Test Embedded Software IC Design Intellectual Property. Using Research Tools Web Searching OCLS. The meta description for each browser settings to bing, boolean logic always prevent them the hierarchy does it displays the search engine examples osubject directories. Online travel agent Bookingcom has admitted that playing has trouble to compensate customers whose personal details have been stolen Guests booking hotel rooms have unwittingly handed over business to criminals Bookingcom is go of the biggest online travel agents. -
C:\Users\Boots\Dropbox\Research\Spring 2014\Rebuilt CCCENL
Using Metasearch Engines for Chemistry-II Part of The Alchemist's Lair Web Site Maintained by Harry E. Pence, Professor of Chemistry, SUNY Oneonta, for the use of his students. Any opinions are totally coincidental and have no official endorsement, including the people who sign my pay checks. Comments and suggestions are welcome ([email protected]). Last Revised Sept. 30, 2004 YOU ARE HERE> Alchemist's Lair > Web Tutorial > Meta Search Engines for the WWW. (This article appeared in the Fall 2004 issue of the Computers in Chemical Education Newsletter.) Meta Search Engines for the WWW, Harry E. Pence, SUNY Oneonta, Oneonta, NY, [email protected] Introduction The mergers and realignments of the past year are still churning the world of search engines. As if this were not enough, Amazon has recently announced that it is developing its own search engine that will make it much easier for an individual to manage his or her information resources. Until this situation becomes more stable, any attempt to compare the different engines is as fruitless as trying to nail plain jello on the wall. On the other hand, there have been some interesting developments in the world of metasearch engines, and it has been two years since this topic was discussed in these reviews (see Using Metasearch Engines for Chemistry-I). As noted in this previous article, the basic idea of a metasearch engine seems very attractive. If it is true that few search engines cover the entire searchable web (not to speak of the portions of the WWW that cannot be accessed by spiders), it seems like a very good strategy to combine the results from several different engines to obtain greater coverage and create a correspondingly greater chance of finding the best reference to the topic being searched. -
The Commercial Search Engine Industry and Alternatives to The
and Yahoo!), works successfully to hide an increasingly profitable information and advertising industry. Search engine companies, of which there are really only three, have morphed into advertising conglomerates and now serve advertisers, not users, in a mutual, rather delightful, relationship. The advertiser pays the search engine to be affiliated with certain key words; the search company The Commercial Search Engine Industry and provides the sponsored links, which users click on; and traffic is driven to the sites of advertisers. Indeed, users are now universally described as consumers in the Alternatives to the Oligopoly marketplace rhetoric of search engine enterprise; they are the pawns who the business world seeks to manipulate into clicking those links that will ultimately Bettina Fabos - Interactive Media Studies and Journalism, Miami lead to the most profits. University of Ohio In this arrangement, helping users find relevant information is a priority only in This essay details the search engine industry’s transformation into an that, like other commercial media systems (think radio or television), there has to advertising oligopoly. It discusses how librarians, educators, archivists, be some decent content to create a perception that Internet users matter. In fact, activists, and citizens, many of whom are the guardians of indispensable users only matter to the extent that they participate in the commercial system by noncommercial websites and portals, can band together against a sea of knowingly—or unknowingly—clicking on sponsored links.1 Keyword advertising advertising interests and powerful and increasingly overwhelming online generated an unprecedented $3.9 billion in 2004. By 2005 Google’s advertising marketing strategies. -
Library Trends 53(4) Spring 2005
Introduction Bettina Fabos The Global Brand of the Year in 2003 title did not go to Coca-Cola, Nike, or Starbucks, some of the most ubiquitous commercial names in our midst. Instead, it went to Google, a highly used but lightly promoted search en- gine, which beat Apple for the second year in a row. The leading brand consultancy, Interbrand, had surveyed about 4,000 “branding professionals” who determined that the Google brand had made the most impact inter- nationally (Google voted, 2004). To think of Google—the most popular searching tool on the Web—as a brand is important for this issue of Library Trends because it underscores how closely mainstream online information resources are tied to the commercial economy. The Web has been a commercial medium since 1995, when the govern- ment quietly sold the Internet’s backbone (previously controlled by the National Science Foundation) to private enterprise. Ten years ago we saw the beginning of a tremendous push—from the Clinton administration, Bill Gates, and the computer and telecommunication industries in general—to get schools and libraries wired. The push, it turns out, was not necessarily to bring the promised “universe of knowledge” (Clinton’s words) to all young and “lifelong” learners alike. Instead, the push was a careful public relations strategy to build up a user base so that the Web could become a viable commercial advertising medium (Fabos, 2004). Indeed, the rhetoric and accompanying media campaign of the mid-1990s was successful: in just five short years, the Web (as part of the larger Internet) became a mass medium—faster than any communication medium before it.