The Impact of Internet Technologies: Search
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Risk Management Resolutions Easier Than a Diet; Good for the Health of Your Nonprofit by Melanie L
A publication of the Nonprofit Risk Management Center Volume 14, No. 1, January/February 2005 Risk Management Resolutions Easier than a diet; good for the health of your nonprofit by Melanie L. Herman ere you one of thousands dilemma you’re facing and the of Americans who received a solution we recommend. To W gym membership gift tucked access this free service, visit neatly in a card from a loved one? www.nonprofitrisk.org and Across the country millions of click on the ADVICE tab. Or Americans are jotting down resolutions, give us a call at (202) 785-3891. most of which have something to do with the three Cs: calories, cardio- Resolution #1 workouts, or carcinogens. Blow the Dust off Resolutions about the three health- inducing Cs are awfully tough to keep, Your Policies as are risk management resolutions that Throughout the year the could change the health of your Nonprofit Risk Management nonprofit. Does the organization you Center receives phone calls from serve have a mission worth preserving? chief financial officers, Are there any risks lurking in your continued on page 2 nonprofit’s future that could spell significant set-back or disaster? Are you losing any sleep about risks related to HR, financial management, fundraising, NEW! Risk Management Essentials Series reputation, or staff/participant injuries? This article offers some simple but Visit www.nonprofitrisk.org to check out a important Risk Management special offer from the Nonprofit Risk Resolutions for 2005. The resolutions can be easily adapted to reflect the Management Center. The Risk Management circumstances and resources of your Essentials Series takes the guesswork out of nonprofit. -
NEXT GENERATION CATALOGUES: an ANALYSIS of USER SEARCH STRATEGIES and BEHAVIOR by FREDRICK KIWUWA LUGYA DISSERTATION Submitted I
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Illinois Digital Environment for Access to Learning and Scholarship Repository NEXT GENERATION CATALOGUES: AN ANALYSIS OF USER SEARCH STRATEGIES AND BEHAVIOR BY FREDRICK KIWUWA LUGYA DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Library and Information Science in the Graduate College of the University of Illinois at Urbana-Champaign, 2017 Urbana, Illinois Doctoral Committee: Associate Professor Kathryn La Barre, Chair and Director Assistant Professor Nicole A. Cooke Dr. Jennifer Emanuel Taylor, University of Illinois Chicago Associate Professor Carol Tilley ABSTRACT The movement from online catalogues to search and discovery systems has not addressed the goals of true resource discoverability. While catalogue user studies have focused on user search and discovery processes and experiences, and construction and manipulation of search queries, little insight is given to how searchers interact with search features of next generation catalogues. Better understanding of user experiences can help guide informed decisions when selecting and implementing new systems. In this study, fourteen graduate students completed a set of information seeking tasks using UIUC's VuFind installation. Observations of these interactions elicited insight into both search feature use and user understanding of the function of features. Participants used the basic search option for most searches. This is because users understand that basic search draws from a deep index that always gives results regardless of search terms; and because it is convenient, appearing at every level of the search, thus reducing effort and shortening search time. -
Uva-DARE (Digital Academic Repository)
UvA-DARE (Digital Academic Repository) Search engine freedom: on the implications of the right to freedom of expression for the legal governance of Web search engines van Hoboken, J.V.J. Publication date 2012 Link to publication Citation for published version (APA): van Hoboken, J. V. J. (2012). Search engine freedom: on the implications of the right to freedom of expression for the legal governance of Web search engines. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:29 Sep 2021 Chapter 2: A Short History of Search Engines and Related Market Developments 22 2.1 The Internet, the Web and the rise of navigational media 2.1.1. Early visions of navigation in digitized information environments The way in which digital computing would lead to a revolution in information and knowledge navigation was already being explored more than half a century ago, when computers were still a rarity and neither the Internet, nor the World Wide Web existed. -
A Framework for Evaluating the Retrieval Effectiveness of Search Engines Dirk Lewandowski Hamburg University of Applied Sciences, Germany
1 A Framework for Evaluating the Retrieval Effectiveness of Search Engines Dirk Lewandowski Hamburg University of Applied Sciences, Germany This is a preprint of a book chapter to be published in: Jouis, Christophe: Next Generation Search Engine: Advanced Models for Information Retrieval. Hershey, PA: IGI Global, 2012 http://www.igi-global.com/book/next-generation-search-engines/59723 ABSTRACT This chapter presents a theoretical framework for evaluating next generation search engines. We focus on search engines whose results presentation is enriched with additional information and does not merely present the usual list of “10 blue links”, that is, of ten links to results, accompanied by a short description. While Web search is used as an example here, the framework can easily be applied to search engines in any other area. The framework not only addresses the results presentation, but also takes into account an extension of the general design of retrieval effectiveness tests. The chapter examines the ways in which this design might influence the results of such studies and how a reliable test is best designed. INTRODUCTION Information retrieval systems in general and specific search engines need to be evaluated during the development process, as well as when the system is running. A main objective of the evaluations is to improve the quality of the search results, although other reasons for evaluating search engines do exist (see Lewandowski & Höchstötter, 2008). A variety of quality factors can be applied to search engines. These can be grouped into four major areas (Lewandowski & Höchstötter, 2008): • Index Quality: This area of quality measurement indicates the important role that search engines’ databases play in retrieving relevant and comprehensive results. -
E-Book: an Introduction to Custom Search Engines for Websites
E-book: An Introduction to Custom Search Engines for Websites What are you looking for? Search www.sitesearch360.com 1 Contents An introduction to search engines........................................ 4 Your visitor’s search journey: the key elements................ 23 What is site search?................................................................ 6 Presentation — how does it look?................................................ 24 Why is site search important?............................................... 6 Processing — how does it work?.................................................. 28 Navigation vs. search................................................................. 7 Results — how does it deliver?.................................................... 32 How are people using search?............................................... 9 Implementation challenges.................................................... 36 Why are custom search engines the perfect choice?........ 12 JavaScript................................................................................ 36 Semantic search........................................................................ 12 Security.................................................................................. 37 Natural search language............................................................ 13 WordPress............................................................................... 37 Actionable analytics.................................................................. 14 Cloudflare and -
Webcrawler: Finding What People Want
© Copyright 2000 Brian Pinkerton WebCrawler: Finding What People Want Brian Pinkerton A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2000 Program Authorized to Offer Degree: Department of Computer Science & Engineering University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Brian Pinkerton and have found that it is complete and satisfactory in all respects and that any and all revisions required by the final examining committee have been made. Co-chairs of the Supervisory Committee: _______________________________________________ Edward Lazowska _______________________________________________ John Zahorjan Reading Committee: _______________________________________________ Edward Lazowska _______________________________________________ John Zahorjan _______________________________________________ David Notkin Date: _____________________ In presenting this dissertation in partial fulfillment of the requirements for the Doctoral degree at the Univer- sity of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of the dissertation is allowable only for scholarly purposes, consistent with “fair use” as prescribed in the U.S. Copyright Law. Requests for copying or reproduction of this dissertation may be referred to Bell and Howell Information and Learning, 300 North Zeeb Road, Ann Arbor, MI 48106- 1346, to whom the author -
The Commodification of Search
San Jose State University SJSU ScholarWorks Master's Theses Master's Theses and Graduate Research 2008 The commodification of search Hsiao-Yin Chen San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_theses Recommended Citation Chen, Hsiao-Yin, "The commodification of search" (2008). Master's Theses. 3593. DOI: https://doi.org/10.31979/etd.wnaq-h6sz https://scholarworks.sjsu.edu/etd_theses/3593 This Thesis is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Theses by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. THE COMMODIFICATION OF SEARCH A Thesis Presented to The School of Journalism and Mass Communications San Jose State University In Partial Fulfillment of the Requirement for the Degree Master of Science by Hsiao-Yin Chen December 2008 UMI Number: 1463396 INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. ® UMI UMI Microform 1463396 Copyright 2009 by ProQuest LLC. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 E. -
Web Crawler for Mining Web Data
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072 WEB CRAWLER FOR MINING WEB DATA S.AMUDHA, B.SC., M.SC., M.PHIL., Assistant Professor, VLB Janakiammal College of Arts and Science, Tamilnadu, India [email protected] -----------------------------------------------------------------********--------------------------------------------------------------------- ABSTRACT Web crawler is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Web crawlers are full text search engines which assist users in navigating the web. Web crawling is an important method for collecting data on, and keeping up with, the rapidly expanding Internet. Users can find their resources by using different hypertext links. A vast number of web pages are continually being added every day, and information is constantly changing. Search engines are used to extract valuable Information from the internet. Web crawlers are the principal part of search engine, is a computer program or software that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. This Paper is an overview of various types of Web Crawlers and the policies like selection, revisit, politeness, and parallelization. Key Words: Web Crawler, World Wide Web, Search Engine, Hyperlink, Uniform Resource Locator. 1. INTRODUCTION A Web crawler starts with a list of URLs to visit, called the seeds. As the crawler visits these URLs, it identifies all the hyperlinks in the page and adds them to the list of URLs to visit, called the crawl frontier. URLs from the frontier are recursively visited according to a set of policies. -
Natural Language Processing for Online Applications Text Retrieval, Extraction and Categorization
Natural Language Processing for Online Applications Natural Language Processing Editor Prof. Ruslan Mitkov School of Humanities, Languages and Social Sciences University of Wolverhampton Stafford St. Wolverhampton WV1 1SB, United Kingdom Email: [email protected] Advisory Board Christian Boitet (University of Grenoble) Jn Carroll (University of Sussex, Brighton) Eugene Charniak (Brown University, Providence) Eduard Hovy (Information Sciences Institute, USC) Richard Kittredge (University of Montreal) Geoffrey Leech (Lancaster University) Carlos Martin-Vide (Rovira i Virgili Un., Tarragona) Andrei Mikheev (University of Edinburgh) Jn Nerbonne (University of Groningen) Nicolas Nicolov (IBM, T.J. Watson Research Center) Kemal Oflazer (Sabanci University) Allan Ramsey (UMIST, Manchester) Monique Rolbert (Université de Marseille) Richard Sproat (AT&T Labs Research, Florham Park) K-Y Su (Baviour Design Corp.) Isabelle Trancoso (INESC, Lisbon) Benjamin Tsou (City University of Hong Kong) Jun-ichi Tsujii (University of Tokyo) Evene Tzoukermann (Bell Laboratories, Murray Hill) Yorick Wilks (University of Sheffield) Volume 5 Natural Language Processing for Online Applications: Text Retrieval, Extraction and Categorization by Peter Jackson and Isabelle Moulinier Natural Language Processing for Online Applications Text Retrieval, Extraction and Categorization Peter Jackson Isabelle Moulinier omson Legal & Regulatory John Benjamins Publishing Company Amsterdam / iladelia TM The paper used in this publication meets the minimum requirements of American 8 National Standard for Information Sciences – Permanence of Paper for Printed Library Materials, ansi z39.48-1984. Library of Congress Cataloging-in-Publication Data Jackson, Peter, 1948- Natural language processing for online applications : text retrieval, extraction, and categorization / Peter Jackson, Isabelle Moulinier. p.cm.(Natural Language Processing, issn 1567–8202 ; v.5) Includes bibliographical references and index. -
Effective Performance of Information Retrieval on Web by Using Web Crawling
International Journal of Web & Semantic Technology (IJWesT) Vol.3, No.2, April 2012 EFFECTIVE PERFORMANCE OF INFORMATION RETRIEVAL ON WEB BY USING WEB CRAWLING Sk.AbdulNabi 1 and Dr. P. Premchand 2 1Department of CSE, AVN Inst. of Engg. & Tech, Hyderabad, A.P., India [email protected] 2Department of CSE, Osmania University, Hyderabad, A.P., India [email protected] ABSTRACT World Wide Web consists of more than 50 billion pages online. It is highly dynamic [6] i.e. the web continuously introduces new capabilities and attracts many people. Due to this explosion in size, the effective information retrieval system or search engine can be used to access the information. In this paper we have proposed the EPOW (Effective Performance of WebCrawler) architecture. It is a software agent whose main objective is to minimize the overload of a user locating needed information. We have designed the web crawler by considering the parallelization policy. Since our EPOW crawler has a highly optimized system it can download a large number of pages per second while being robust against crashes. We have also proposed to use the data structure concepts for implementation of scheduler & circular Queue to improve the performance of our web crawler. (Abstract) KEYWORDS EPOW, Effective Web Crawler, Circular Queue, Scheduler, Basic Crawler, Precision & Recall. 1. INTRODUCTION In world wide web, information retrieval system [1] acts a vital role to extract the useful information with minimum amount of time. It has the ability to store the information and retrieved the information from the repository and also manages the information. The general objective of any Information Retrieval Method is to minimize the overhead of a user locating needed information. -
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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. -
Indexing the World Wide Web: the Journey So Far Abhishek Das Google Inc., USA Ankit Jain Google Inc., USA
Indexing The World Wide Web: The Journey So Far Abhishek Das Google Inc., USA Ankit Jain Google Inc., USA ABSTRACT In this chapter, we describe the key indexing components of today’s web search engines. As the World Wide Web has grown, the systems and methods for indexing have changed significantly. We present the data structures used, the features extracted, the infrastructure needed, and the options available for designing a brand new search engine. We highlight techniques that improve relevance of results, discuss trade-offs to best utilize machine resources, and cover distributed processing concept in this context. In particular, we delve into the topics of indexing phrases instead of terms, storage in memory vs. on disk, and data partitioning. We will finish with some thoughts on information organization for the newly emerging data-forms. INTRODUCTION The World Wide Web is considered to be the greatest breakthrough in telecommunications after the telephone. Quoting the new media reader from MIT press [Wardrip-Fruin , 2003]: “The World-Wide Web (W3) was developed to be a pool of human knowledge, and human culture, which would allow collaborators in remote sites to share their ideas and all aspects of a common project.” The last two decades have witnessed many significant attempts to make this knowledge “discoverable”. These attempts broadly fall into two categories: (1) classification of webpages in hierarchical categories (directory structure), championed by the likes of Yahoo! and Open Directory Project; (2) full-text index search engines such as Excite, AltaVista, and Google. The former is an intuitive method of arranging web pages, where subject-matter experts collect and annotate pages for each category, much like books are classified in a library.