Awareness Watch™ Newsletter by Marcus P
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Why We Need an Independent Index of the Web ¬ Dirk Lewandowski 50 Society of the Query Reader
Politics of Search Engines 49 René König and Miriam Rasch (eds), Society of the Query Reader: Reections on Web Search, Amsterdam: Institute of Network Cultures, 2014. ISBN: 978-90-818575-8-1. Why We Need an Independent Index of the Web ¬ Dirk Lewandowski 50 Society of the Query Reader Why We Need an Independent Index of the Web ¬ Dirk Lewandowski Search engine indexes function as a ‘local copy of the web’1, forming the foundation of every search engine. Search engines need to look for new documents constantly, detect changes made to existing documents, and remove documents from the index when they are no longer available on the web. When one considers that the web com- prises many billions of documents that are constantly changing, the challenge search engines face becomes clear. It is impossible to maintain a perfectly complete and current index.2 The pool of data changes thousands of times each second. No search engine can keep up with this rapid pace of change.3 The ‘local copy of the web’ can thus be viewed as the Holy Grail of web indexing at best – in practice, different search engines will always attain a varied degree of success in pursuing this goal.4 Search engines do not merely capture the text of the documents they find (as is of- ten falsely assumed). They also generate complex replicas of the documents. These representations include, for instance, information on the popularity of the document (measured by the number of times it is accessed or how many links to the document exist on the web), information extracted from the documents (for example the name of the author or the date the document was created), and an alternative text-based 1. -
HTTP Cookie - Wikipedia, the Free Encyclopedia 14/05/2014
HTTP cookie - Wikipedia, the free encyclopedia 14/05/2014 Create account Log in Article Talk Read Edit View history Search HTTP cookie From Wikipedia, the free encyclopedia Navigation A cookie, also known as an HTTP cookie, web cookie, or browser HTTP Main page cookie, is a small piece of data sent from a website and stored in a Persistence · Compression · HTTPS · Contents user's web browser while the user is browsing that website. Every time Request methods Featured content the user loads the website, the browser sends the cookie back to the OPTIONS · GET · HEAD · POST · PUT · Current events server to notify the website of the user's previous activity.[1] Cookies DELETE · TRACE · CONNECT · PATCH · Random article Donate to Wikipedia were designed to be a reliable mechanism for websites to remember Header fields Wikimedia Shop stateful information (such as items in a shopping cart) or to record the Cookie · ETag · Location · HTTP referer · DNT user's browsing activity (including clicking particular buttons, logging in, · X-Forwarded-For · Interaction or recording which pages were visited by the user as far back as months Status codes or years ago). 301 Moved Permanently · 302 Found · Help 303 See Other · 403 Forbidden · About Wikipedia Although cookies cannot carry viruses, and cannot install malware on 404 Not Found · [2] Community portal the host computer, tracking cookies and especially third-party v · t · e · Recent changes tracking cookies are commonly used as ways to compile long-term Contact page records of individuals' browsing histories—a potential privacy concern that prompted European[3] and U.S. -
Distributed Indexing/Searching Workshop Agenda, Attendee List, and Position Papers
Distributed Indexing/Searching Workshop Agenda, Attendee List, and Position Papers Held May 28-19, 1996 in Cambridge, Massachusetts Sponsored by the World Wide Web Consortium Workshop co-chairs: Michael Schwartz, @Home Network Mic Bowman, Transarc Corp. This workshop brings together a cross-section of people concerned with distributed indexing and searching, to explore areas of common concern where standards might be defined. The Call For Participation1 suggested particular focus on repository interfaces that support efficient and powerful distributed indexing and searching. There was a great deal of interest in this workshop. Because of our desire to limit attendance to a workable size group while maximizing breadth of attendee backgrounds, we limited attendance to one person per position paper, and furthermore we limited attendance to one person per institution. In some cases, attendees submitted multiple position papers, with the intention of discussing each of their projects or ideas that were relevant to the workshop. We had not anticipated this interpretation of the Call For Participation; our intention was to use the position papers to select participants, not to provide a forum for enumerating ideas and projects. As a compromise, we decided to choose among the submitted papers and allow multiple position papers per person and per institution, but to restrict attendance as noted above. Hence, in the paper list below there are some cases where one author or institution has multiple position papers. 1 http://www.w3.org/pub/WWW/Search/960528/cfp.html 1 Agenda The Distributed Indexing/Searching Workshop will span two days. The first day's goal is to identify areas for potential standardization through several directed discussion sessions. -
Discontinued Browsers List
Discontinued Browsers List Look back into history at the fallen windows of yesteryear. Welcome to the dead pool. We include both officially discontinued, as well as those that have not updated. If you are interested in browsers that still work, try our big browser list. All links open in new windows. 1. Abaco (discontinued) http://lab-fgb.com/abaco 2. Acoo (last updated 2009) http://www.acoobrowser.com 3. Amaya (discontinued 2013) https://www.w3.org/Amaya 4. AOL Explorer (discontinued 2006) https://www.aol.com 5. AMosaic (discontinued in 2006) No website 6. Arachne (last updated 2013) http://www.glennmcc.org 7. Arena (discontinued in 1998) https://www.w3.org/Arena 8. Ariadna (discontinued in 1998) http://www.ariadna.ru 9. Arora (discontinued in 2011) https://github.com/Arora/arora 10. AWeb (last updated 2001) http://www.amitrix.com/aweb.html 11. Baidu (discontinued 2019) https://liulanqi.baidu.com 12. Beamrise (last updated 2014) http://www.sien.com 13. Beonex Communicator (discontinued in 2004) https://www.beonex.com 14. BlackHawk (last updated 2015) http://www.netgate.sk/blackhawk 15. Bolt (discontinued 2011) No website 16. Browse3d (last updated 2005) http://www.browse3d.com 17. Browzar (last updated 2013) http://www.browzar.com 18. Camino (discontinued in 2013) http://caminobrowser.org 19. Classilla (last updated 2014) https://www.floodgap.com/software/classilla 20. CometBird (discontinued 2015) http://www.cometbird.com 21. Conkeror (last updated 2016) http://conkeror.org 22. Crazy Browser (last updated 2013) No website 23. Deepnet Explorer (discontinued in 2006) http://www.deepnetexplorer.com 24. Enigma (last updated 2012) No website 25. -
Web-Page Indexing Based on the Prioritize Ontology Terms
Web-page Indexing based on the Prioritize Ontology Terms Sukanta Sinha1, 4, Rana Dattagupta2, Debajyoti Mukhopadhyay3, 4 1Tata Consultancy Services Ltd., Victoria Park Building, Salt Lake, Kolkata 700091, India [email protected] 2Computer Science Dept., Jadavpur University, Kolkata 700032, India [email protected] 3Information Technology Dept., Maharashtra Institute of Technology, Pune 411038, India [email protected] 4WIDiCoReL Research Lab, Green Tower, C-9/1, Golf Green, Kolkata 700095, India Abstract. In this world, globalization has become a basic and most popular human trend. To globalize information, people are going to publish the docu- ments in the internet. As a result, information volume of internet has become huge. To handle that huge volume of information, Web searcher uses search engines. The Web-page indexing mechanism of a search engine plays a big role to retrieve Web search results in a faster way from the huge volume of Web re- sources. Web researchers have introduced various types of Web-page indexing mechanism to retrieve Web-pages from Web-page repository. In this paper, we have illustrated a new approach of design and development of Web-page index- ing. The proposed Web-page indexing mechanism has applied on domain spe- cific Web-pages and we have identified the Web-page domain based on an On- tology. In our approach, first we prioritize the Ontology terms that exist in the Web-page content then apply our own indexing mechanism to index that Web- page. The main advantage of storing an index is to optimize the speed and per- formance while finding relevant documents from the domain specific search engine storage area for a user given search query. -
Google Bing Facebook Findopen Foursquare
The Network Google Active Monthly Users: 1B+ Today's world of smartphones, mobile moments, and self-driving cars demands accurate location data more than ever. And no single search, maps, and apps provider is more important to your location marketing strategy than Google. With the Yext Location Manager, you can manage your location data on Google My Business—the tool through which Businesses can supply data to Google Search, Google Maps, and Google+. Bing Active Monthly Users: 150M+ With more than 20% of search market share in the US and rapidly increasing traction worldwide, Bing is an essential piece of the local ecosystem. More than 150 million users search for local Businesses and services on Bing every month. Beginning in 2016, Bing will also power search results across the AOL portfolio of sites, including Huffington Post, Engadget, and TechCrunch. Facebook Active Monthly Users: 1.35B Facebook is the world’s Biggest social network with more than 2 Billion users. Yext Sync for FaceBook makes it easy to manage accurate and up-to-date contact information, photos, messages and more. FindOpen FindOpen is one of the world’s leading online Business directories and helps consumers find the critical information they need to know aBout the Businesses they’d like to visit, like hours of operation, holiday hours, special hours, menus, product and service lists, and more. FindOpen — also known as FindeOffen, TrovaAperto, TrouverOuvert, VindOpen, nyitva.hu, EncuentreAbierto, AussieHours, FindAaben, TeraZOtwarte, HittaӦppna, and deschis.ro in the many countries it operates — provides a fully responsive experience, no matter where its gloBal users are searching from. -
The Google Search Engine
University of Business and Technology in Kosovo UBT Knowledge Center Theses and Dissertations Student Work Summer 6-2010 The Google search engine Ganimete Perçuku Follow this and additional works at: https://knowledgecenter.ubt-uni.net/etd Part of the Computer Sciences Commons Faculty of Computer Sciences and Engineering The Google search engine (Bachelor Degree) Ganimete Perçuku – Hasani June, 2010 Prishtinë Faculty of Computer Sciences and Engineering Bachelor Degree Academic Year 2008 – 2009 Student: Ganimete Perçuku – Hasani The Google search engine Supervisor: Dr. Bekim Gashi 09/06/2010 This thesis is submitted in partial fulfillment of the requirements for a Bachelor Degree Abstrakt Përgjithësisht makina kërkuese Google paraqitet si sistemi i kompjuterëve të projektuar për kërkimin e informatave në ueb. Google mundohet t’i kuptojë kërkesat e njerëzve në mënyrë “njerëzore”, dhe t’iu kthej atyre përgjigjen në formën të qartë. Por, ky synim nuk është as afër ideales dhe realizimi i tij sa vjen e vështirësohet me zgjerimin eksponencial që sot po përjeton ueb-i. Google, paraqitet duke ngërthyer në vetvete shqyrtimin e pjesëve që e përbëjnë, atyre në të cilat sistemi mbështetet, dhe rrethinave tjera që i mundësojnë sistemit të funksionojë pa probleme apo të përtërihet lehtë nga ndonjë dështim eventual. Procesi i grumbullimit të të dhënave ne Google dhe paraqitja e tyre në rezultatet e kërkimit ngërthen në vete regjistrimin e të dhënave nga ueb-faqe të ndryshme dhe vendosjen e tyre në rezervuarin e sistemit, përkatësisht në bazën e të dhënave ku edhe realizohen pyetësorët që kthejnë rezultatet e radhitura në mënyrën e caktuar nga algoritmi i Google. -
Context Based Web Indexing for Storage of Relevant Web Pages
International Journal of Computer Applications (0975 – 8887) Volume 40– No.3, February 2012 Context based Web Indexing for Storage of Relevant Web Pages Nidhi Tyagi Rahul Rishi R.P. Agarwal Asst. Prof. Prof. & Head Prof. & Head Shobhit University, Technical Institute of Textile & Shobhit University, Meerut Sciences, Bhiwani Meerut ABSTRACT or 1. This strategy makes the searching task faster and A focused crawler downloads web pages that are relevant to a optimized. user specified topic. The downloaded documents are indexed with a view to optimize speed and performance in finding 2. RELATED WORK relevant documents for a search query at the search engine In this section, a review of previous work on index side. However, the information will be more relevant if the organization is given. In this field of index organization and context of the topic is also made available to the retrieval maintenance, many algorithms and techniques have already system. This paper proposes a technique for indexing the been proposed but they seem to be less efficient in efficiently keyword extracted from the web documents along with their accessing the index. contexts wherein it uses a height balanced binary search F. Silvestri, R.Perego and Orlando [4] proposed the (AVL) tree, for indexing purpose to enhance the performance reordering algorithm which partitions the set of documents of the retrieval system. into k ordered clusters on the basis of similarity measure where the biggest document is selected as centroid of the first General Terms cluster and n/k1 most similar documents are assigned to this Algorithm, retrieval, indexer. cluster. Then the biggest document is selected and the same process repeats. -
Appendix I: Search Quality and Economies of Scale
Appendix I: search quality and economies of scale Introduction 1. This appendix presents some detailed evidence concerning how general search engines compete on quality. It also examines network effects, scale economies and other barriers to search engines competing effectively on quality and other dimensions of competition. 2. This appendix draws on academic literature, submissions and internal documents from market participants. Comparing quality across search engines 3. As set out in Chapter 3, the main way that search engines compete for consumers is through various dimensions of quality, including relevance of results, privacy and trust, and social purpose or rewards.1 Of these dimensions, the relevance of search results is generally considered to be the most important. 4. In this section, we present consumer research and other evidence regarding how search engines compare on the quality and relevance of search results. Evidence on quality from consumer research 5. We reviewed a range of consumer research produced or commissioned by Google or Bing, to understand how consumers perceive the quality of these and other search engines. The following evidence concerns consumers’ overall quality judgements and preferences for particular search engines: 6. Google submitted the results of its Information Satisfaction tests. Google’s Information Satisfaction tests are quality comparisons that it carries out in the normal course of its business. In these tests, human raters score unbranded search results from mobile devices for a random set of queries from Google’s search logs. • Google submitted the results of 98 tests from the US between 2017 and 2020. Google outscored Bing in each test; the gap stood at 8.1 percentage points in the most recent test and 7.3 percentage points on average over the period. -
The Indexing at the Internet
THE INDEXING AT THE INTERNET Isidoro Gil-Leiva Universidad de Murcia Murcia/Spain ABSTRACT It is presented an analysis of the presence of indexing at the Internet supported by the idea that good part of the basic pillars in the ones which this web of computers is based is impregnated in higher or lower measure by indexing. The pillars are the metadata, the searchers, the users and the web positioning. Each one of these elements is reviewed to prove the approach which is accomplished the one is denominated Universe of the Web Indexing. Keywords: Indexing; Internet; Metadata; Web Positioning; Users; Searchers; Search Engines; Universe of Web Indexing. INTRODUCTION Before the Internet appearance, most of the occasions, the data, the information and the steps were distant and decentralized. To accomplish an administrative step it was necessary to go the administration, to read or buy a book to go to the library or to a bookstore, to contemplate determined museum work go to one, or to buy a car move to the car dealer and, like that, successively. Along with the Internet generalization almost all the activity branches of the human being were blooming on the web and, consequently, the competence of the physical world in the services, trade or culture were translated to the digital scope. However, according to the improvements of the content at the web it was necessary the development of bridges, to connect the people to the information mass available at the web, with the purpose to access in a fast and efficient way this new environment. These footbridges are the denominated search or research engines. -
Apex Filters 17.2.3.0 User Guide 27 Jun 2017 Table of Contents
Apex Filters 17.2.3.0 User Guide 27 Jun 2017 Table of Contents Chapter 1: Apex filters.................................................................................................. 4 Boolean operators used in filter expressions...........................................................................5 app........................................................................................................................................................6 browser................................................................................................................................................7 browserPlatform...............................................................................................................................8 browserVersion..................................................................................................................................9 dataSource........................................................................................................................................10 ethertype........................................................................................................................................... 11 fixRequest......................................................................................................................................... 13 fixResponse.......................................................................................................................................15 flowIdx.............................................................................................................................................. -
Pembangunan Add-On Untuk Content Aware Web Browser (Studi Kasus: Mozilla Firefox)
Tugas Akhir - 2012 PEMBANGUNAN ADD-ON UNTUK CONTENT AWARE WEB BROWSER (STUDI KASUS: MOZILLA FIREFOX) Jessi Monika¹, Bayu Erfianto², Retno Novi Dayawati³ ¹Teknik Informatika, Fakultas Teknik Informatika, Universitas Telkom Abstrak Mozilla Firefox merupakan salah satu web browser yang paling banyak digunakan pada saat ini. Mozilla Firefox memiliki banyak features yang menarik para penggunanya. Salah satunya adalah add-ons, yaitu aplikasi tambahan untuk menambah fungsi-fungsi yang diperlukan oleh user dalam menggunakan browser. Terdapat tiga jenis add-ons pada Mozilla Firefox: Extension, Themes, dan Plugin. Sampai saat ini Mozilla Firefox adalah yang paling banyak memiliki add-ons dibanding browser yang lain. Selain kelebihan yang telah disebutkan terdapat juga kekurangan pada Mozilla Firefox. Salah satunya adalah fenomena dimana banyaknya plugins yang dimiliki oleh pengguna dan berada pada kondisi aktif (enable) dapat membuat penggunaan memori (memory usage) pada Mozilla Firefox tersebut menjadi lebih besar sehingga user merasakan bahwa browser bekerja lebih lambat bekerja dan sering terjadi crash. Pada tugas akhir ini membuat sebuah add-ons yang berupa extension pada Mozilla Firefox yang dapat menon-aktifkan (disable) dan mengaktifkan (enable) plugin yang hanya dibutuhkan saja berdasarkan content-type pada halaman web yang dibuka. Berdasarkan hasil analisis dan pengujian menunjukan bahwa penentuan besar dari memory usage tidak hanya berdasarkan dari firefox.exe saja tetapi ada beberapa aplikasi lain yang juga dapat mempengaruhi besar dari memory usage yaitu plugin-container.exe, java.exe, jp2launcher.exe, dan FlashPluginPlayer.exe. Hal ini terjadi berdasarkan kebutuhan dari sebuah plugin dalam bekerja. Plugin java membutuhkan kinerja dari aplikasi java.exe dan jp2launcher.exe, sedangkan FlashPluginPlayer.exe aktif karena pengaruh dari kinerja plugin Shockwave Flash.