Unit14 Overview of Web Indexing, Metadata, Interoperability and Ontologies
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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. -
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. -
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. -
Awareness Watch™ Newsletter by Marcus P
Awareness Watch™ Newsletter By Marcus P. Zillman, M.S., A.M.H.A. http://www.AwarenessWatch.com/ V9N4 April 2011 Welcome to the V9N4 April 2011 issue of the Awareness Watch™ Newsletter. This newsletter is available as a complimentary subscription and will be issued monthly. Each newsletter will feature the following: Awareness Watch™ Featured Report Awareness Watch™ Spotters Awareness Watch™ Book/Paper/Article Review Subject Tracer™ Information Blogs I am always open to feedback from readers so please feel free to email with all suggestions, reviews and new resources that you feel would be appropriate for inclusion in an upcoming issue of Awareness Watch™. This is an ongoing work of creativity and you will be observing constant changes, constant updates knowing that “change” is the only thing that will remain constant!! Awareness Watch™ Featured Report This month’s featured report covers Deep Web Research. This is a comprehensive miniguide of reference resources covering deep web research currently available on the Internet. The below list of sources is taken from my Subject Tracer™ Information Blog titled Deep Web Research and is constantly updated with Subject Tracer™ bots at the following URL: http://www.DeepWeb.us/ These resources and sources will help you to discover the many pathways available to you through the Internet to find the latest reference deep web resources and sites. 1 Awareness Watch V9N4 April 2011 Newsletter http://www.AwarenessWatch.com/ [email protected] eVoice: 800-858-1462 © 2011 Marcus P. Zillman, M.S., A.M.H.A. Deep Web Research Bots, Blogs and News Aggregators (http://www.BotsBlogs.com/) is a keynote presentation that I have been delivering over the last several years, and much of my information comes from the extensive research that I have completed over the years into the “invisible” or what I like to call the “deep” web. -
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. -
Automatic Indexing: an Approach Using an Index Term Corpus and Combining Linguistic and Statistical Methods
CORE Metadata, citation and similar papers at core.ac.uk Provided by Helsingin yliopiston digitaalinen arkisto Automatic indexing: an approach using an index term corpus and combining linguistic and statistical methods Timo Lahtinen Academic dissertation to be publicly discussed, by due permission of the Faculty of Arts at the University of Helsinki in lecture room Unioninkatu 35, on the 11th of December, 2000, at 11 o’clock. University of Helsinki PUBLICATIONS Department of General Linguistics NO. 34 P.O. Box 4 2000 FIN-00014 University of Helsinki Finland ISBN 951-45-9639-0 ISBN 951-45-9640-4 (PDF) ISSN 0355-7170 Helsinki 2000 Yliopistopaino Abstract This thesis discusses the problems and the methods of finding relevant information in large collections of documents. The contribution of this thesis to this problem is to develop better content analysis methods which can be used to describe document content with index terms. Index terms can be used as meta-information that describes documents, and that is used for seeking information. The main point of this thesis is to illustrate the process of developing an automatic indexer which analyses the content of documents by combining evidence from word frequencies and evidence from linguistic analysis provided by a syntactic parser. The indexer weights the expressions of a text according to their estimated importance for describing the content of a given document on the basis of the content analysis. The typical linguistic features of index terms were explored using a linguistically analysed text collection where the index terms are manually marked up. This text collection is referred to as an index term corpus. -
NEDLIB Glossary
NEDLIB Glossary Authors: José Luis Borbinha, National Library of Portugal Fernando Cardoso, National Library of Portugal Nuno Freire, INESC Date of Issue: 22 February 2000 Issue: 1.0web Total Number of Pages: 46 NEDLIB Glossary TABLE OF CONTENTS TABLE OF CONTENTS...............................................................................................................................................................................i Abstract ................................................................................................................................................................................................2 Keywords..............................................................................................................................................................................................2 1. Concepts ..................................................................................................................................................................................................2 1.1 Index of Terms ............................................................................................................................................................................2 1.2 Terms Relationship ....................................................................................................................................................................6 1.3 Glossary ....................................................................................................................................................................................13 -
A New Hidden Web Crawling Approach
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 10, 2015 A New Hidden Web Crawling Approach L.Saoudi A.Boukerram S.Mhamedi Computer science department Computer science department Computer science department Mohammed Boudiaf University Abderrahmane Mira University Mohammed Boudiaf University M‟sila, Algeria bejaia, algeria M‟sila, Algeria Abstract—Traditional search engines deal with the Surface V describes the experimental results that is done over book Web which is a set of Web pages directly accessible through domain which are discussed in section VI and finally, section hyperlinks and ignores a large part of the Web called hidden VII draws the conclusion and describes the future research. Web which is a great amount of valuable information of online database which is “hidden” behind the query forms. II. HIDDEN WEB CRAWLERS To access to those information the crawler have to fill the forms with a valid data, for this reason we propose a new A. Generality approach which use SQLI technique in order to find the most A web crawler (also known as a robot or a spider) is a promising keywords of a specific domain for automatic form system for the bulk downloading of web pages. Web crawlers submission. are used for a variety of purposes. Most prominently, they are The effectiveness of proposed framework has been evaluated one of the main components of web search engines, systems through experiments using real web sites and encouraging that assemble a corpus of web pages, index them, and allow preliminary results were obtained users to issue queries against the index and find the web pages that match the queries.