An Analysis of Web Documents Retrieved and Viewed
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March 21–25, 2016
FORTY-SEVENTH LUNAR AND PLANETARY SCIENCE CONFERENCE PROGRAM OF TECHNICAL SESSIONS MARCH 21–25, 2016 The Woodlands Waterway Marriott Hotel and Convention Center The Woodlands, Texas INSTITUTIONAL SUPPORT Universities Space Research Association Lunar and Planetary Institute National Aeronautics and Space Administration CONFERENCE CO-CHAIRS Stephen Mackwell, Lunar and Planetary Institute Eileen Stansbery, NASA Johnson Space Center PROGRAM COMMITTEE CHAIRS David Draper, NASA Johnson Space Center Walter Kiefer, Lunar and Planetary Institute PROGRAM COMMITTEE P. Doug Archer, NASA Johnson Space Center Nicolas LeCorvec, Lunar and Planetary Institute Katherine Bermingham, University of Maryland Yo Matsubara, Smithsonian Institute Janice Bishop, SETI and NASA Ames Research Center Francis McCubbin, NASA Johnson Space Center Jeremy Boyce, University of California, Los Angeles Andrew Needham, Carnegie Institution of Washington Lisa Danielson, NASA Johnson Space Center Lan-Anh Nguyen, NASA Johnson Space Center Deepak Dhingra, University of Idaho Paul Niles, NASA Johnson Space Center Stephen Elardo, Carnegie Institution of Washington Dorothy Oehler, NASA Johnson Space Center Marc Fries, NASA Johnson Space Center D. Alex Patthoff, Jet Propulsion Laboratory Cyrena Goodrich, Lunar and Planetary Institute Elizabeth Rampe, Aerodyne Industries, Jacobs JETS at John Gruener, NASA Johnson Space Center NASA Johnson Space Center Justin Hagerty, U.S. Geological Survey Carol Raymond, Jet Propulsion Laboratory Lindsay Hays, Jet Propulsion Laboratory Paul Schenk, -
Web Searching in Chinese: a Study of a Search Engine in Hong Kong
Web Searching in Chinese: A Study of a Search Engine in Hong Kong Michael Chau School of Business, University of Hong Kong, Pokfulam, Hong Kong. E-mail: [email protected] Xiao Fang College of Business Administration, University of Toledo, Toledo, OH 43606. E-mail: [email protected] Christopher C. Yang Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong. E-mail: [email protected] The number of non-English resources has been increas- query to a search engine. While most Web contents are in ing rapidly on the Web. Although many studies have English, there are increasingly more Web pages that are au- been conducted on the query logs in search engines that thored in other languages. Besides, many Web users are not are primarily English-based (e.g., Excite and AltaVista), only a few of them have studied the information-seeking native English speakers; some even do not know English at behavior on the Web in non-English languages. In this all. It has been estimated that only around 36.5% of Internet article, we report the analysis of the search-query logs of users are native English speakers (Global Reach, 2004). a search engine that focused on Chinese. Three months Consequently, it is common for users to perform Web of search-query logs of Timway, a search engine based searches for non-English resources. While most large com- in Hong Kong, were collected and analyzed. Metrics on sessions, queries, search topics, and character usage mercial search engines such as Google can handle queries in are reported. -
NSF Sensational 60
Cover credits Background: © 2010 JupiterImages Corporation Inset credits (left to right): Courtesy Woods Hole Oceanographic Institution; Gemini Observatory; Nicolle Rager Fuller, National Science Foundation; Zee Evans, National Science Foundation; Nicolle Rager Fuller, National Science Foundation; Zina Deretsky, National Science Foundation, adapted from map by Chris Harrison, Human-Computer Interaction Institute, Carnegie Mellon University; Tobias Hertel, Insti- tute for Physical Chemistry, University of Würzburg Design by: Adrian Apodaca, National Science Foundation 1 Introduction The National Science Foundation (NSF) is an independent federal agency that supports fundamental research and education across all fields of science and engineering. Congress passed legislation creating the NSF in 1950 and President Harry S. Truman signed that legislation on May 10, 1950, creating a government agency that funds research in the basic sciences, engineering, mathematics and technology. NSF is the federal agency responsible for nonmedical research in all fields of science, engineering, education and technology. NSF funding is approved through the federal budget process. In fiscal year (FY) 2010, its budget is about $6.9 billion. NSF has an independent governing body called the National Science Board (NSB) that oversees and helps direct NSF programs and activities. NSF funds reach all 50 states through grants to nearly 2,000 universities and institutions. NSF is the funding source for approximately 20 percent of all federally supported basic research conducted by America’s colleges and universities. Each year, NSF receives over 45,000 competitive requests for funding, and makes over 11,500 new funding awards. NSF also awards over $400 million in professional and service contracts yearly. NSF has a total workforce of about 1,700 at its Arlington, Va., headquarters, including approximately 1,200 career employees, 150 scientists from research institutions on temporary duty, 200 contract workers and the staff of the NSB office and the Office of the Inspector General. -
Information Rereival, Part 1
11/4/2019 Information Retrieval Deepak Kumar Information Retrieval Searching within a document collection for a particular needed information. 1 11/4/2019 Query Search Engines… Altavista Entireweb Leapfish Spezify Ask Excite Lycos Stinky Teddy Baidu Faroo Maktoob Stumpdedia Bing Info.com Miner.hu Swisscows Blekko Fireball Monster Crawler Teoma ChaCha Gigablast Naver Walla Dogpile Google Omgili WebCrawler Daum Go Rediff Yahoo! Dmoz Goo Scrub The Web Yandex Du Hakia Seznam Yippy Egerin HotBot Sogou Youdao ckDuckGo Soso 2 11/4/2019 Search Engine Marketshare 2019 3 11/4/2019 Search Engine Marketshare 2017 Matching & Ranking matched pages ranked pages 1. 2. query 3. muddy waters matching ranking “hits” 4 11/4/2019 Index Inverted Index • A mapping from content (words) to location. • Example: the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat 5 11/4/2019 Inverted Index the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 dog 2 3 mat 1 2 on 1 2 sat 1 3 stood 2 3 the 1 2 3 while 3 Inverted Index the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 dog 2 3 mat 1 2 Every word in every on 1 2 web page is indexed! sat 1 3 stood 2 3 the 1 2 3 while 3 6 11/4/2019 Searching the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat 1 3 query dog 2 3 mat 1 2 cat on 1 2 sat 1 3 stood 2 3 the 1 2 3 while 3 Searching the cat sat on the dog stood on the cat stood 1 2 3 the mat the mat while a dog sat a 3 cat -
List of Search Engines Listed by Types of Searches
List of Search Engines Listed by Types of Searches - © 09-14-2014 - images removed Copyright - Professional Web Services Internet Marketing SEO Business Solutions - http://pwebs.net - All Rights Reserved List of Search Engines Listed by Types of Searches by ProWebs - Article last updated on: Saturday, July 28, 2012 http://pwebs.net/2011/04/search-engines-list/ To view images click link above. This page posting has been updated with the addition of some of the newer search engines. The original search engine page was dealing mainly with B2B and B2C search. However, with today's broad based Internet activity, and how it relates to various aspects of business usage, personal searches, and even internal intranet enterprise searches, we wanted to highlight some of the different search market segments. This list of the various search engines, is posted here mainly for research and education purposes. We felt it is nice to be able to reference and have links to some of the different search engines all in one place. While the list below does not cover each and every search engine online, it does provide a broad list of most of the major search companies that are available. Also note that some of the search engine links have been redirected to other sites due to search buyouts, mergers, and acquisitions with other companies, along with changes with the search engines themselves (for example: search companies have changed brand names, different URLs, and links). You will also notice that some of the search websites go back a number of years. If you would like to read more about the details of any particular search engine, take a look at the Wikipedia Search Engines List article, and follow the links to each specific search engine for a descriptive overview. -
Readingsample
Information Science and Knowledge Management 14 Web Search Multidisciplinary Perspectives Bearbeitet von Amanda Spink, Michael Zimmer 1. Auflage 2008. Buch. xii, 352 S. Hardcover ISBN 978 3 540 75828 0 Format (B x L): 15,5 x 23,5 cm Gewicht: 703 g Weitere Fachgebiete > EDV, Informatik > EDV, Informatik: Allgemeines, Moderne Kommunikation > Soziale, sicherheitstechnische, ethische Aspekte Zu Inhaltsverzeichnis schnell und portofrei erhältlich bei Die Online-Fachbuchhandlung beck-shop.de ist spezialisiert auf Fachbücher, insbesondere Recht, Steuern und Wirtschaft. Im Sortiment finden Sie alle Medien (Bücher, Zeitschriften, CDs, eBooks, etc.) aller Verlage. Ergänzt wird das Programm durch Services wie Neuerscheinungsdienst oder Zusammenstellungen von Büchern zu Sonderpreisen. Der Shop führt mehr als 8 Millionen Produkte. 16 Web Searching: A Quality Measurement Perspective D. Lewandowski and N. Höchstötter Summary The purpose of this paper is to describe various quality measures for search engines and to ask whether these are suitable. We especially focus on user needs and their use of Web search engines. The paper presents an extensive litera- ture review and a first quality measurement model, as well. Findings include that Web search engine quality can not be measured by just retrieval effectiveness (the quality of the results), but should also consider index quality, the quality of the search features and Web search engine usability . For each of these sections, empiri- cal results from studies conducted in the past, as well as from our own research are presented. These results have implications for the evaluation of Web search engines and for the development of better search systems that give the user the best possible search experience. -
The Retrieval Effectiveness of Web Search Engines
The Retrieval Effectiveness of Web Search Engines: Considering Results Descriptions1 Dirk Lewandowski, Hamburg University of Applied Sciences, Faculty Design, Media and Information Department Information, Berliner Tor 5, D – 20249 Hamburg, Germany. E-Mail: [email protected], Tel: ++49 40 42875-3621, Fax: ++49 40 42875-3609 Abstract Purpose: To compare five major Web search engines (Google, Yahoo, MSN, Ask.com, and Seekport) for their retrieval effectiveness, taking into account not only the results but also the results descriptions. Design/Methodology/Approach: The study uses real-life queries. Results are made anonymous and are randomised. Results are judged by the persons posing the original queries. Findings: The two major search engines, Google and Yahoo, perform best, and there are no significant differences between them. Google delivers significantly more relevant result descriptions than any other search engine. This could be one reason for users perceiving this engine as superior. Research Limitations: The study is based on a user model where the user takes into account a certain amount of results rather systematically. This may not be the case in real life. Practical Implications: Implies that search engines should focus on relevant descriptions. Searchers are advised to use other search engines in addition to Google. Originality/Value: This is the first major study comparing results and descriptions systematically and proposes new retrieval measures to take into account results descriptions. Article type: Research paper Keywords: Word Wide Web / search engines / retrieval effectiveness / results descriptions / retrieval measures Introduction It is hard to say which of the major international search engines is the best. -
Exploring Interaction Patterns in Job Search
Exploring Interaction Patterns in Job Search Alfan Farizki Wicaksono Alistair Moffat The University of Melbourne The University of Melbourne Melbourne, Australia Melbourne, Australia ABSTRACT for the query (the SERP, which itself might be broken into pages by We analyze interaction logs from Seek.com, a well-known Aus- the interface protocol, or might be presented as a single listing via tralasian employment site, with the goal of better understanding the continuous scrolling) is clicked so as to arrive at the corresponding ways in which users pursue their search goals following the issue of job details page; and an application action is recorded when the each query. Of particular interest are the patterns of job summary job seeker clicks the “apply” button in that job details page, with viewing and click-through behaviors that arise, and the differences the presumption being that they will then enter more information, in activity between mobile/tablet-based users (Android/iOS) and and at some time in the future, lodge their application. We also computer-based users. know the absolute time/date associated with the first action in each sequence. KEYWORDS As an example, consider the action sequence: Interaction logs; user behavior; job search A0 = h(“I”; 1; 0); (“I”; 3; 1); (“C”; 3; 3); (“I”; 4; 9); ACM Reference Format: (“I”; 5; 10); (“C”; 5; 11); (“I”; 6; 20); (“I”; 4; 22); Alfan Farizki Wicaksono and Alistair Moffat. 2018. Exploring Interaction (“C”; 4; 25); (“I”; 6; 40); (“I”; 7; 41)i : Patterns in Job Search. In 23rd Australasian Document Computing Symposium (ADCS ’18), December 11–12, 2018, Dunedin, New Zealand. -
You Can't See What You Can't See: Experimental Evidence for How
You can't see what you can't see: Experimental evidence for how much relevant information may be missed due to Google's Web search personalisation Cameron Lai1 and Markus Luczak-Roesch1[0000−0003−4610−7244] Victoria University of Wellington School of Information Management Wellington, New Zealand [email protected] https://www.victoria.ac.nz/sim Abstract. The influence of Web search personalisation on professional knowledge work is an understudied area. Here we investigate how public sector officials self-assess their dependency on the Google Web search engine, whether they are aware of the potential impact of algorithmic biases on their ability to retrieve all relevant information, and how much relevant information may actually be missed due to Web search person- alisation. We find that the majority of participants in our experimental study are neither aware that there is a potential problem nor do they have a strategy to mitigate the risk of missing relevant information when performing online searches. Most significantly, we provide empirical ev- idence that up to 20% of relevant information may be missed due to Web search personalisation. This work has significant implications for Web research by public sector professionals, who should be provided with training about the potential algorithmic biases that may affect their judg- ments and decision making, as well as clear guidelines how to minimise the risk of missing relevant information. Keywords: Web search · Personalisation · Human-computer interaction · Social informatics 1 Introduction arXiv:1904.13022v2 [cs.IR] 20 May 2019 In August 2018 Radio New Zealand (RNZ), a New Zealand public radio broad- caster, reported that the use of Google Web search by the New Zealand Police may have unwittingly revealed a link between two suspects facing charges for a crime committed together but who had no documented history of any joint crime or crime of the same kind [12]. -
A Comparison of Nine Search Engine Transaction Logs
This is the author-version of a paper published as: Jansen, Bernard J. and Spink, Amanda (2006) How are we searching the world wide web? A comparison of nine search engine transaction logs. Information Processing and Management 42(1):pp. 248-263. Copyright 2006 Elsevier HOW ARE WE SEARCHING THE WORLD WIDE WEB?: A COMPARISON OF NINE SEARCH ENGINE TRANSACTION LOGS Bernard J. Jansen Amanda Spink School of Information Sciences and Technology School of Information Sciences The Pennsylvania State University University of Pittsburgh 329F IST Building 610 IS Building, 135 N. Bellefield Avenue University Park, PA 16802 Pittsburgh, PA 15260 Email: [email protected] Email: [email protected] Abstract The Web and especially major Web search engines are essential tools in the quest to locate online information for many people. This paper reports results from research that examines characteristics and changes in Web searching from nine studies of five Web search engines based in the U.S. and Europe. We compare interactions occurring between users and Web search engines from the perspectives of session length, query length, query complexity, and content viewed among the Web search engines. The results of our research shows (1) users are viewing fewer result pages, (2) searchers on U.S.-based Web search engines use more query operators tan searchers on European-based search engines, (3) there are statistically significant differences in the use of Boolean operators and result pages viewed, and (4) one can not necessary apply results from studies of one particular Web search engine to another Web search engine. The wide spread use of Web search engines, employment of simple queries, and decreased viewing of result pages may have resulted from algorithmic enhancements by Web search engine companies. -
Devonagent Pro VERSION 3.11.4 DOCUMENTATION
DEVONagent Pro VERSION 3.11.4 DOCUMENTATION © 2001-2020 DEVONtechnologies TABLE OF CONTENTS READ ME 4 SEARCH SETS 29 The DEVONagent Pro Advantage 5 What are search sets? 29 System Requirements 6 Choosing a search set 29 Installing, Updating, Removing 6 Creating and managing sets 30 Trial Restrictions 7 Sharing sets 31 Version History 7 General tab 31 License Agreement 16 Advanced tab 33 Credits 16 Sites tab 34 Plugins tab 35 GETTING STARTED 17 Actions tab 36 Why use DEVONagent Pro? 17 Schedule tab 37 When to use DEVONagent Pro? 17 MENUS 38 DEVONagent Pro at a Glance 18 First steps with DEVONagent Pro 19 The DEVONagent Pro menu 38 The File menu 39 COMMON TASKS 20 The Edit menu 41 How to find on the Internet 20 The Data menu 41 How to search beyond Google 21 The Sort menu 43 How to customize DEVONagent Pro 21 The View menu 43 How to set up a search set to crawl The Web menu 44 feeds 22 The History menu 46 How to run a search automatically 23 The Go menu 46 How to archive search results 23 The Window menu 47 The Services menu 47 QUERIES 25 The Scripts menu 48 Operators 25 The Help menu 48 Designing a search query 27 The Dock menu 49 DEVONagent Pro 3.11.4 Documentation, page 2 WINDOWS AND PANELS 51 TECHNOLOGY 99 Search window 52 General Concept 99 Web browser 59 Features 99 Archive window 66 Structure 99 Search sets 68 Applications 100 Plugins and scanners 68 OTHER PRODUCTS 101 Downloads 71 Preferences 72 Overview 101 Assistant 72 DEVONthink 101 DEVONagent 101 PREFERENCES 75 DEVONsphere 102 General 75 Needful Things 102 Search 77 APPENDIX -
IODE and Oceanportal Search Engine Registration
IODE and Oceanportal search Engine Registration Download date 29/09/2021 10:31:01 Link to Item http://hdl.handle.net/1834/1626 IODE AND OCEANPORTAL SEARCH ENGINE REGISTRATION 29/08/2000 ANNEX 1 REGISTRATION OF IOC.UNESCO.ORG/IODE Anmeldungsprotokoll Erzeugt am 29/08/00 mit Hello Engines! Angemeldete URL: http://ioc.unesco.org/iode Titel der angemeldeten URL: IODE Erfolgreiche Anmeldungen: 221 Fehlgeschlagene Anmeldungen: 26 Statuscodes Die HTTP-Status-Codes haben folgende Bedeutung: ·200-299 Erfolgreiche Anfrage ·300-399 Client-Anfrage nicht eindeutig ·400-499 Client-Anfrage fehlerhaft ·500-599 Server-Fehler Grundsätzlich deuten nur die Codes zwischen 400 und 599 auf eine fehlgeschlagene Anmeldung hin (z.B. bedeutet der Code 302 in der Regel nur, dass der Suchdienst eine Weiterleitung vorgenommen hat. Das Programm folgt Weiterleitung aus verschiedenen Gründen jedoch nie. Deshalb ist auch die Antwortseite dieses Suchdiensts im Verzeichnis \HTML leer). Erfolgreiche Uebertragung Name Statusmeldung und -Code Linkcentre OK 200 EuroSeek OK 200 Excite (AU) OK 200 Rex (USA) OK 200 Excite (SE) OK 200 AustroNaut OK 200 Excite (NL) OK 200 Galaxy Directory OK 200 Blue Window OK 200 The Yellow Page OK 200 Official Search OK 200 WebCrawler Found 302 5 STAR NETWAY CO UK DIRECTORY Object moved 302 Anzwers Search Centre OK 200 Matilda Found 302 BuildNet Directory Found 302 AdValvas Yellow Pages OK 200 Aladin OK 200 IOC/IODE-XVI/24 Page 2 ADMCity OK 200 A2Z Solutions Search Engine OK 200 Axis-Online Moved Temporarily 302 AltaVista (US) OK 200 BizCardz