Advanced Internet Searching
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Russia Technology Internet Local Dominance Strengthens
12 December 2018 | 1:51AM MSK Russia Technology: Internet Local dominance strengthens; competition among ecosystems intensifies It’s been a year since we published Russia’s internet champions positioned to Vyacheslav Degtyarev +7(495)645-4010 | keep US giants at bay. We revisit our thesis, highlighting that the domestic internet [email protected] OOO Goldman Sachs Bank incumbents are successfully defending their home turf from international competition. We have seen only modest incremental efforts from global players, with some recognizing the importance of local expertise (Alibaba’s agreement to transfer control in AliExpress Russia to local partners) or conceding to domestic market leaders (Uber merged its Russian operations with Yandex.Taxi, citing Yandex’s strong technology and brand advantage). The two domestic market leaders, Yandex and Mail.ru, have solidified their dominant positions in search and social networks, respectively, and are leveraging these core businesses to exploit new sources of growth across their ecosystems (e.g. advertising, taxi, food tech, music). While their ever-expanding competitive overlap is worrying, we note this is not unique for global tech and is still relatively limited in scale. We expect the local dominance trend to continue and see significant untapped opportunities in e-commerce, messengers, local services, cloud and fintech. We re-iterate our Buy ratings on Yandex (on CEEMEA FL) and Mail.ru, and view them as the key beneficiaries of internet sector growth in Russia. We believe the market -
Dining Hall,” “Cafeteria,” and “Campus Food Service” • Be Specific As You Learn More – E.G
THE INTERNET Conducting Internet Research Computer Applications I Martin Santos Jorge Cab Objectives • After completing this section, students will be able to: • Understand the internet • Identify the different tools for research • Use and cite references from the internet Lecturers: Martin Santos/Jorge Cab (S.P.J.C.) 2 Vocabulary List • Internet (the Net): a global connection of millions of computer networks • Browser: software that helps a user access web sites (Internet Explorer and Netscape) • Server: a computer that runs special software and sends information over the Internet when requested • World Wide Web (the Web or www.): multimedia portion of the Internet consisting of text, graphics, audio and video • URL: stands for Uniform Resource Locator. It is the website's “address” or what the user types in to make the connection • Web site: a “virtual” place on the Internet with a unique URL • Virtual: “mental” replica of something - you can’t “touch” it – need a “tool” to get to it • Web page: a place on a web site where specific information is located • Home page: main page of a web site and first page to load when a site is accessed • Hyperlink: “clickable” text or graphics – takes you from one place to another – usually underlined and shows a hand shaped icon • Hypertext: capability to “link” or “jump” to other references or cross references by clicking • Cyberspace: “electronic” universe where information from one computer connects with another • Upload: process of transferring information to a page/site on the internet • Download: process of transferring information to a computer • Search engine: a site that scans the contents of other web sites to create a large index of information • Domain (top level): code located in the URL representing the type of organization (i.e., .gov (government), .edu (education), .mil (military), .org (organization – non-profit), .com (commercial – a business – for profit) • Internet Service Provider (ISP): a company with direct connection to the Internet that grants subscribers access to various Internet services. -
Comparative Analysis of Yandex and Google Search Engines
Anna Paananen Comparative Analysis of Yandex and Google Search Engines Helsinki Metropolia University of Applied Sciences Master’s Degree Information Technology Master’s Thesis 26 May 2012 PREFACE Working in NetBooster Finland as an International Project Manager specialized in Russian market I’ve been asked many times about differences between the search engines Yandex and Google. This Master’s Thesis is the outcome of my professional experience in the Search Engine Optimisation field in Russia and Finland. I would like to thank all the people from NetBooster Finland and Helsinki Metropolia University of Applied Sciences who has helped me in the development of the study. Special thanks to my instructors Timo-Pekka Jäntti and Ville Jääskeläinen for all the support, both in technical and non-technical matters. I would like to thank also my collegues from NetBooster Finland for their help and support while writing the thesis. Last but not least I would like to thank my mother Tamara Kapitonova, who always has been my prior motivator for the education, and of course to my lovely husband Jukka Paananen for his inconditional support and patience. Helsinki, May 26, 2012 Anna Paananen Author(s) Anna Paananen Title Comparative Analysis of Google and Yandex Search Engines Number of Pages 51 pages + 1 appendix Date 26 May 2012 Degree Master’s Degree Degree Programme Degree Programme in Information Technology Specialisation option Instructor Timo-Pekka Jäntti, Supervisor This thesis presents a comparative analysis of algorithms and information retrieval performance of two search engines: Yandex and Google in the Russian language. Comparing two search engines is usually done with user satisfaction studies and market share measures in addition to the basic comparison measures. -
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. -
Dogpile.Com First to Combine Search Results from MSN Search with Google, Yahoo and Ask Jeeves
Dogpile.com First to Combine Search Results From MSN Search with Google, Yahoo and Ask Jeeves With the Addition of MSN Search, Dogpile.com Users Can Efficiently Find More of the Web's Most Relevant Search Results in One Place BELLEVUE, Wash. – August 2, 2005 – Dogpile.com today announced that search results from MSN Search are now available on the Web's leading metasearch engine. By becoming the first to combine results from the four leading search sites—MSN Search, Google, Yahoo and Ask Jeeves—Dogpile.com gives consumers the most comprehensive view of the Web and helps them efficiently retrieve the most relevant results. The addition of MSN Search to Dogpile.com further extends Dogpile.com's differentiation from any single search engine. Most people believe search results across all four engines are the same, when, in fact, the vast majority of the results from each engine are different. According to a new study, researchers at the University of Pittsburgh and the Pennsylvania State University evaluated 12,570 random queries run on MSN Search, Google, Yahoo and Ask Jeeves. They found only 1.1 percent of the first page results are the same across all four engines. The full results of the study can be found at http://CompareSearchEngines.dogpile.com/whitepaper. "By bringing together the best results from the top engines on Dogpile.com, consumers can be confident they are receiving the most relevant results," said Brian Bowman, vice president of marketing and product management for InfoSpace Search & Directory. Dogpile.com has built a tool that allows consumers to compare the results of the leading engines for themselves. -
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 -
Web Search Tutoring for the Local Community
Web search for local communities in the Highlands of Scotland: A self-tutoring guide MODULE III Alternatives to Google: some other search tools worth a try © Copyright Hans Zell Publishing Consultants 2011 Glais Bheinn, Lochcarron, Ross-shire IV54 8YB, Scotland, UK Email: [email protected] Web: www.hanszell.co.uk Web search for local communities in the Highlands of Scotland: A self-tutoring guide MODULE I How to get the most out of Google Web search MODULE II A concise guide to Google products, services, applications, and other offerings MODULE III Alternatives to Google: some other search tools worth a try MODULE IV The best of the Web: a guide to some of the most information-rich resources on the Internet 2 Introduction Google is a marvellous Web search tool and is as good as they get at present, but it is certainly not the only one. Other top search engines include Ask.com (aka as Ask Jeeves), Bing (formerly called MSN Search), and Yahoo! (and see General purpose, product, and visual search engines below). According to data published by Experian Hitwise http://www.hitwise.com/us/datacenter/main/dashboard-23984.html in June 2011, Google still heavily dominates the market with a share of about 68%, while the market share of Yahoo and Microsoft’s Bing currently is something just under 14% for both; Ask.com is in fourth place with around 2.6%, and AOL Search in fifth place with about 1.4%. The picture is roughly the same if ranked by number of visits, although Bing does better than Yahoo in this category. -
Final Study Report on CEF Automated Translation Value Proposition in the Context of the European LT Market/Ecosystem
Final study report on CEF Automated Translation value proposition in the context of the European LT market/ecosystem FINAL REPORT A study prepared for the European Commission DG Communications Networks, Content & Technology by: Digital Single Market CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report This study was carried out for the European Commission by Luc MEERTENS 2 Khalid CHOUKRI Stefania AGUZZI Andrejs VASILJEVS Internal identification Contract number: 2017/S 108-216374 SMART number: 2016/0103 DISCLAIMER By the European Commission, Directorate-General of Communications Networks, Content & Technology. The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the Commission. The Commission does not guarantee the accuracy of the data included in this study. Neither the Commission nor any person acting on the Commission’s behalf may be held responsible for the use which may be made of the information contained therein. ISBN 978-92-76-00783-8 doi: 10.2759/142151 © European Union, 2019. All rights reserved. Certain parts are licensed under conditions to the EU. Reproduction is authorised provided the source is acknowledged. 2 CEF AT value proposition in the context of the European LT market/ecosystem Final Study Report CONTENTS Table of figures ................................................................................................................................................ 7 List of tables .................................................................................................................................................. -
Analysis of Query Keywords of Sports-Related Queries Using Visualization and Clustering
Analysis of Query Keywords of Sports-Related Queries Using Visualization and Clustering Jin Zhang and Dietmar Wolfram School of Information Studies, University of Wisconsin—Milwaukee, Milwaukee, WI 53201. E-mail: {jzhang, dwolfram}@uwm.edu Peiling Wang School of Information Sciences, College of Communication and Information, University of Tennessee at Knoxville, Knoxville, TN 37996–0341. E-mail: [email protected] The authors investigated 11 sports-related query key- the user’s request includes the client Internet Protocol (IP) words extracted from a public search engine query log address, request date/time, page requested, HTTP code, bytes to better understand sports-related information seeking served, user agent, referrer, and so on. The data are kept in on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related key- a standard format in a transaction log file (Hallam-Baker & words were identified, along with frequently co-occurring Behlendorf, 2008). query terms associated with the identified keywords. Although a transaction log comprises rich data, including Relationships among each sports-related focus keyword browsing times and traversal paths, it is the queries directly and its related keywords were characterized and grouped submitted by users that have attracted the most research using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two attention. Query data contain keywords that reflect users’ approaches were synthesized in a visual context by high- wide-ranging information needs. Query logs have been ana- lighting the results of the hierarchical clustering analysis lyzed from a variety of sources with different emphases and in the visual MDS configuration. -
A Survey of Collaborative Web Search Through Collaboration Among Search Engine Users to More Relevant Results
A Survey of Collaborative Web Search Through Collaboration among Search Engine Users to More Relevant Results Pavel Surynek Faculty of Mathematics and Physics, Charles University in Prague, Malostranské náměstí 25, Prague, Czech Republic Keywords: Collaborative Web Search, Social Search, Search Engine, Search Results, Collaborative Filtering, Recommender Systems, System Integration. Abstract: A survey on collaborative aspects of web search is presented in this paper. Current state in full-text web search engines with regards on users collaboration is given. The position of the paper is that it is becoming increasingly important to learn from other users searches in a collaborative way in order to provide more relevant results and increase benefit from web search sessions. Recommender systems represent a rich source of concepts that could be employed to enable collaboration in web search. A discussion of techniques used in recommender systems is followed by a suggestion of integration web search with recommender sys- tems. An initial experience with web search powering small academic site is reported finally. 1 INTRODUCTION AND assumption that a series of queries characterize the effort of what the user want to find better than the MOTIVATION single query. The typical search engine however does not help in this effort – users are put into isola- Web search is an area of the information technology tion typically which precludes any cooperation and industry where artificial intelligence and particularly recommendation from other users based on past knowledge engineering techniques can be applied queries. To be honest, for instance the Bing search with potentially significant impacts. Currently users engine (more correctly the decision engine) uses face a still increasing amount of data of many kinds certain technology that provide search results based that can be accessed through web (textual data, mul- on user’s search history and geographical location. -
Efficient Marketing Communications Towards Russian Customers. Case: Grande Orchidée Fashion Center
Saimaa University of Applied Sciences Faculty of Business Administration, Lappeenranta Degree Programme in International Business Specialisation in International Business Bachelor's Thesis 2014 Ekaterina Evtikhevich Efficient Marketing Communications towards Russian Customers. Case: Grande Orchidée Fashion Center Bachelor's Thesis 2014 ABSTRACT Ekaterina Evtikhevich Efficient Marketing Communications towards Russian Customers. Case: Grande Orchidée Fashion Center, 47 pages, 2 appendices Saimaa University of Applied Sciences Faculty of Business Administration, Lappeenranta Degree Programme in International Business Specialisation in International Business Bachelor’s Thesis 2014 Instructor: Principal Lecturer Minna Ikävalko, Saimaa University of Applied Sciences The objective of this thesis was to research what are the most efficient market- ing communications of Grande Orchidée Fashion Center towards Russian customers. The focus was kept on individual customers who come regularly to do shopping in Lappeenranta. The theory part of this research work includes an examination of conventional theories of marketing communication tools and analysis of modern marketing in Russia. The empirical part was implemented by studying the current marketing com- munications of the company. The data collection methods included a semi structured interview with the CEO's assistant at the company and a customer survey. The outcomes showed the most efficient communication channels that can be utilized and that can positively contribute to the company's marketing -
Accelerating Development Using the Web: Empowering Poor and Marginalized Populations George Sadowsky, Ed
Accelerating Development Using the Web: Empowering Poor and Marginalized Populations George Sadowsky, ed. George Sadowsky Najeeb Al-Shorbaji Richard Duncombe Torbjörn Fredriksson Alan Greenberg Nancy Hafkin Michael Jensen Shalini Kala Barbara J. Mack Nnenna Nwakanma Daniel Pimienta Tim Unwin Cynthia Waddell Raul Zambrano Cover image: Paul Butler http://paulbutler.org/archives/visualizing-facebook-friends/ Creative Commons License Attribution-ShareAlike 3.0 This work, with the exception of Chapter 7 (Health), is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA. Chapter 7 (Health) © World Health Organization [2012]. All rights reserved. The World Health Organization has granted the Publisher permission for the reproduction of this chapter. Accelerating Development Using the Web | Foreword from the Rockefeller Foundation i Foreword from the Rockefeller Foundation For almost 100 years, the Rockefeller Foundation has been at the forefront of new ideas and innovations related to emerging areas of technology. In its early years, the Foundation advanced new technologies to eradicate hookworm and develop a vaccine for yellow fever, creating a lasting legacy of strengthening the application of new technologies to improve the lives of the world’s poor and vulnerable. By the middle of the 20th century, this approach led the Foundation to the pre-cursor to the modern day comput- er. At the dawn of the digital era in 1956, the Foundation helped launch the field of artificial intelligence through its support for the work of John McCarthy, the computing visionary who coined the term.