Quantitative Analysis of Whether Machine Intelligence Can Surpass
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Erasmus Mundus Master's Journalism and Media Within Globalisation: The
Erasmus Mundus Master’s Journalism and Media within Globalisation: The European Perspective. Blue Book 2009-2011 The 2009- 2011 Masters group includes 49 students from all over the world: Australia, Brazil, Britain, Canada, China, Czech, Cuba, Denmark, Egypt, Ethiopia, Finland, France, Germany, India, Italy, Kenya, Kyrgyzstan, Norway, Panama, Philippines, Poland, Portugal, Serbia, South Africa, Spain, Ukraine and USA. 1 Mundus Masters Journalism and Media class of 2009-2011. Family name First name Nationality Email Specialism Lopez Belinda Australia lopez.belinda[at]gmail.com London City d'Essen Caroline Brazil/France caroldessen[at]yahoo.com.br Hamburg Werber Cassie Britain cassiewerber[at]gmail.com London City Baker Amy Canada amyabaker[at]gmail.com Swansea Halas Sarka Canada/Czech sarkahalasova[at]gmail.com London City Diao Ying China dydiaoying[at]gmail.com London City Piñero Roig Jennifer Cuba jenniferpiero[at]yahoo.es Hamburg Jørgensen Charlotte Denmark charlotte_j84[at]hotmail.com Hamburg Poulsen Martin Kiil Denmark poulsen[at]martinkiil.dk Swansea Billie Nasrin Sharif Denmark Nasrin.Billie[at]gmail.com Swansea Zidore Christensen Ida Denmark IdaZidore[at]gmail.com Swansea Sørensen Lasse Berg Denmark lasseberg[at]gmail.com London City Hansen Mads Stampe Denmark Mads_Stampe[at]hotmail.com London City Al Mojaddidi Sarah Egypt mojaddidi[at]gmail.com Swansea Gebeyehu Abel Adamu Ethiopia abeltesha2003[at]gmail.com Swansea Eronen Eeva Marjatta Finland eeva.eronen[at]iki.fi London City Abbadi Naouel France naouel.mohamed[at]univ-lyon2.fr -
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Table of Contents UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 Form 20-F (Mark One) ¨ REGISTRATION STATEMENT PURSUANT TO SECTION 12(b) OR 12(g) OF THE SECURITIES EXCHANGE ACT OF 1934 or x ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended December 31, 2013. or ¨ TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition period from to or ¨ SHELL COMPANY REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 Date of event requiring this shell company report Commission file number: 000-51469 Baidu, Inc. (Exact name of Registrant as specified in its charter) N/A (Translation of Registrant’s name into English) Cayman Islands (Jurisdiction of incorporation or organization) Baidu Campus No. 10 Shangdi 10th Street Haidian District, Beijing 100085 The People’s Republic of China (Address of principal executive offices) Jennifer Xinzhe Li, Chief Financial Officer Telephone: +(86 10) 5992-8888 Email: [email protected] Facsimile: +(86 10) 5992-0000 Baidu Campus No. 10 Shangdi 10th Street, Haidian District, Beijing 100085 The People’s Republic of China (Name, Telephone, Email and/or Facsimile number and Address of Company Contact Person) Securities registered or to be registered pursuant to Section 12(b) of the Act: Title of Each Class Name of Each Exchange on Which Registered American depositary shares (ten American depositary shares representing one Class A ordinary share, The NASDAQ Stock Market LLC par value US$0.00005 per share) (The NASDAQ Global Select Market) Class A ordinary shares, par value US$0.00005 per share* The NASDAQ Stock Market LLC (The NASDAQ Global Select Market) * Not for trading, but only in connection with the listing on The NASDAQ Global Select Market of American depositary shares. -
Applications: S
Applications: S This chapter contains the following sections: • Sabah, on page 9 • Safari, on page 10 • SAFT, on page 11 • Sage, on page 12 • Sahibinden, on page 13 • Saks Fifth Avenue, on page 14 • Salesforce.com, on page 15 • Salesforce.com Live Agent, on page 16 • Sam's Club, on page 17 • Sametime, on page 18 • SAMR, on page 19 • Samsung, on page 20 • Samsung Push Notification, on page 21 • SANity, on page 22 • Sanook.com, on page 23 • SAP, on page 24 • SAP HostControl, on page 25 • SASCDN, on page 26 • SATNET, on page 27 • SATNET and Backroom EXPAK, on page 28 • SATNET Monitoring, on page 29 • SaveFrom, on page 30 • Sberbank of Russia, on page 31 • SBS, on page 32 • SCC Security, on page 33 • SCCM, on page 34 • SCCM Remote Control, on page 35 • SCCP, on page 36 • Schedule Transfer Protocol, on page 37 • schuelerVZ, on page 38 • Schwab, on page 39 • ScienceDirect, on page 40 Applications: S 1 Applications: S • SCO Desktop Administration Server, on page 41 • Sco I2 Dialog Daemon, on page 42 • SCO System Administration Server, on page 43 • SCO Web Server Manager 3, on page 44 • SCO WebServer Manager, on page 45 • scohelp, on page 46 • Scopia, on page 47 • Scopia Audio, on page 48 • Scopia Video, on page 49 • Scorecard Research, on page 50 • Scottrade, on page 51 • SCPS, on page 52 • Scribd, on page 53 • Scribd Upload, on page 54 • Scribol, on page 55 • SCSI-ST, on page 56 • SCTP, on page 57 • scx-proxy, on page 58 • SDNS-KMP, on page 59 • SDRP, on page 60 • Seamonkey, on page 61 • Search-Result.com, on page 62 • Searchnu, on page 63 • -
User Browsing Graph: Structure, Evolution and Application1
User Browsing Graph: Structure, Evolution and Application1 Yiqun Liu, Min Zhang, Shaoping Ma, Liyun Ru State Key Lab of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University, Beijing, 100084, China P.R. [email protected] ABSTRACT don’t work very well in this new situation. This paper focuses on ‘user browsing graph’ which is constructed Recently, the wisdom of the crowd is paid much attention in with users’ click-through behavior modeled with Web access logs. Web search researches, e.g. [7], [8] and [9]. In their work, users’ User browsing graph has recently been adopted to improve Web browsing behavior is usually considered as implicit feedback search performance and the initial study shows it is more reliable information for page relevance and importance. For example, Liu than hyperlink graph for inferring page importance. However, et. al. constructed ‘user browsing graph’ with search log data [10]. structure and evolution of the user browsing graph haven’t been They proposed a page importance estimation algorithm called fully studied and many questions remain to be answered. In this BrowseRank which performs on the user browsing graph. It is paper, we look into the structure of the user browsing graph and believed that the link structure in user browsing graph is more its evolution over time. We try to give a quantitative analysis on reliable than hyperlink graph because users actually follow links the difference in graph structure between hyperlink graph and in the browsing graph. user browsing graph, and then find out why link analysis Liu’s initial study shows that the BrowseRank algorithm works algorithms perform better on the browsing graph. -
Thème : Le Web Les Moteurs De Recherche Moteur De Recherche
Thème : Le Web Les moteurs de recherche Capacités attendues : - Comprendre le fonctionnement des moteurs de recherche - Mener une analyse critique des résultats d’un moteur de recherche - Comprendre les enjeux de la publication d’informations Moteur de recherche : application informatique permettant de rechercher une ressource (page Web, image, vidéo, fichier…) à partir d’une requête sous forme de mots-clés. 1. Le fonctionnement des moteurs de recherche * Au brouillon, essayez de schématiser le fonctionnement d’un moteur de recherche. Vocabulaire à retenir : - crawlers : robot d’indexation qui explore automatiquement le Web en suivant les liens entre les différentes pages pour collecter les ressources. - indexation : les mots-clés sont listés, classés et enregistrés sur des serveurs qui stockent les données. - pertinence : répond au besoin au moment où il est exprimé. Le Web est un immense graphe : chaque page est un noeud relié à d’autres nœuds par des liens hypertextes. On pourrait le schématiser de façon très simplifiée, comme ci-contre. Mme Suaudeau SNT 2019-2020 * A partir du nœud E, parcourez le graphe précédant en listant les pages consultées et les pages à visiter à chaque étape : Action Pages visitées Pages à visiter On visite E, lié à A et H E A H On visite A , lié à B E A H B On visite H , lié à J E A H B J On visite B , lié à A et C E A H B J C (A déjà visité) On visite J , lié à F E A H B J C F On visite C , lié à A E A H B J C C F (A déjà visité) On visite F , lié à C D G H E A H B J C F D G (C et H déjà visités) On visite D , lié à / E A H B J C F D G On visite G , lié à / E A H B J C F D G * Que se passe-t-il si l’on commence l’exploration par le nœud A ? La visite est terminée en 3 étapes mais on a « raté » une grande partie du graphe. -
Sogou Announces Fourth Quarter and Full Year 2020 Results BEIJING, China, February 4, 2021 – Sogou Inc. (NYSE: SOGO) ("So
Sogou Announces Fourth Quarter and Full Year 2020 Results BEIJING, China, February 4, 2021 – Sogou Inc. (NYSE: SOGO) ("Sogou" or the “Company"), an innovator in search and a leader in China's internet industry, today announced its unaudited financial results for the fourth quarter and full year, ended December 31, 2020. Fourth Quarter 2020 Financial Results Total revenues1 were $189.5 million, a 37% decrease year-over-year. The decrease was primarily driven by uncertainties with respect to Sogou’s business policies among certain advertisers as a result of the previously-announced proposal by Tencent Holdings Limited (“Tencent”) to take Sogou private, as well as reduced traffic acquisition activity. • Search and search-related revenues were $166.7 million, a 39% decrease year- over-year. Auction-based pay-for-click services decreased year-over-year, accounting for 84.0% of search and search-related revenues, compared to 88.2% in the corresponding period in 2019. • Other revenues were $22.8 million, a 14% decrease year-over-year. The decrease was primarily due to decreased revenues from non-core businesses. Cost of revenues was $151.2 million, a 10% decrease year-over-year. Traffic acquisition cost, a primary driver of cost of revenues, was $115.5 million, a 10% decrease year-over-year, representing 60.9% of total revenues, compared to 42.8% in the corresponding period in 2019. The decrease in traffic acquisition costs was driven by decreased traffic acquisition from third parties. Gross profit and non-GAAP2 gross profit were both $38.3 million, a 71% decrease year- over-year for both. -
Characterization of Portuguese Web Searches
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Characterization of Portuguese Web Searches Rui Ribeiro Master in Informatics and Computing Engineering Supervisor: Sérgio Nunes (PhD) July 11, 2011 Characterization of Portuguese Web Searches Rui Ribeiro Master in Informatics and Computing Engineering Approved in oral examination by the committee: Chair: João Pascoal Faria (PhD) External Examiner: Daniel Coelho Gomes (PhD) Supervisor: Sérgio Sobral Nunes (PhD) 5st July, 2011 Abstract Nowadays the Web can be seen as a worldwide library, being one of the main access points to information. The large amount of information available on websites all around the world raises the need for mechanisms capable of searching and retrieving relevant information for the user. Information retrieval systems arise in this context, as systems capable of searching large amounts of information and retrieving relevant information in the user’s perspective. On the Web, search engines are the main information retrieval sys- tems. The search engine returns a list of possible relevant websites for the user, according to his search, trying to fulfill his information need. The need to know what users search for in a search engine led to the development of methodologies that can answer this problem and provide statistical data for analysis. Many search engines store the information about all queries made in files called trans- action logs. The information stored in these logs can vary, but most of them contain information about the user, query date and time and the content of the query itself. With the analysis of these logs, it is possible to get information about the number of queries made on the search engine, the mean terms per query, the mean session duration or the most common topics. -
Is Google the Next Microsoft? Competition, Welfare and Regulation in Online Search
IS GOOGLE THE NEXT MICROSOFT? COMPETITION, WELFARE AND REGULATION IN ONLINE SEARCH RUFUS POLLOCK UNIVERSITY OF CAMBRIDGE Abstract. The rapid growth of online search and its centrality to the ecology of the Internet pose important questions: why is the search engine market so concentrated and will it evolve towards monopoly? What implications does this concentration have for consumers, search engines, and advertisers? Does search require regulation and if so in what form? This paper supplies empirical and theoretical material with which to examine these questions. In particular, we (a) show that the already large levels of concentration are likely to continue (b) identify the consequences, negative and positive, of this outcome (c) discuss the regulatory interventions that policy-makers could use to address these. Keywords: Search Engine, Regulation, Competition, Antitrust, Platform Markets JEL Classification: L40 L10 L50 Emmanuel College and Faculty of Economics, University of Cambridge. Email: [email protected] or [email protected]. I thank the organizers of 2007 IDEI Toulouse Conference on the Economics of the Software and Internet Industries whose search round-table greatly stimulated my thoughts on this topic as well as participants at seminars in Cambridge and at the 2009 RES conference. Particular thanks is also due to the editor and anonymous referee who provided an excellent set of comments that served to greatly improve the paper. Finally, I would like to thank http://searchenginewatch.com and Hitwise who both generously provided me with access to some of their data. This work is licensed under a Creative Commons Attribution Licence (v3.0, all jurisdictions). -
Google/ Doubleclick REGULATION (EC) No 139/2004 MERGER PROCEDURE Article 8(1)
EN This text is made available for information purposes only. A summary of this decision is published in all Community languages in the Official Journal of the European Union. Case No COMP/M.4731 – Google/ DoubleClick Only the English text is authentic. REGULATION (EC) No 139/2004 MERGER PROCEDURE Article 8(1) Date: 11-03-2008 COMMISSION OF THE EUROPEAN COMMUNITIES Brussels, 11/03/2008 C(2008) 927 final PUBLIC VERSION COMMISSION DECISION of 11/03/2008 declaring a concentration to be compatible with the common market and the functioning of the EEA Agreement (Case No COMP/M.4731 – Google/ DoubleClick) (Only the English text is authentic) Table of contents 1 INTRODUCTION .....................................................................................................4 2 THE PARTIES...........................................................................................................5 3 THE CONCENTRATION.........................................................................................6 4 COMMUNITY DIMENSION ...................................................................................6 5 MARKET DESCRIPTION......................................................................................6 6 RELEVANT MARKETS.........................................................................................17 6.1. Relevant product markets ............................................................................17 6.1.1. Provision of online advertising space.............................................17 6.1.2. Intermediation in -
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 -
Exploring Search Engine Counts in the Identification and Characterization
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Open Repository of the University of Porto FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Exploring search engine counts in the identification and characterization of search queries Diogo Magalhães Moura Mestrado Integrado em Engenharia Informática e Computação Supervisor: Carla Teixeira Lopes July 26, 2018 Exploring search engine counts in the identification and characterization of search queries Diogo Magalhães Moura Mestrado Integrado em Engenharia Informática e Computação Approved in oral examination by the committee: Chair: João Moreira External Examiner: Ricardo Campos Supervisor: Carla Lopes July 26, 2018 Abstract The Web is the greatest source of information nowadays and it’s frequently used by most people to seek specific information. People do not search the most efficient way possible. They tend to use a small number of search terms, look into few retrieved documents and rarely use advanced features. This makes it harder of finding the intent and motive of the search and provide the user with relevant and precise documents among the numerous documents available online. This topic is particularly important when the information searched is in the health domain. Health-related searches have gained much popularity. In the U.S. only, 72% of Internet users search in this domain. Being able to provide better results could encourage people to be more participative in managing their health and have a fundamental impact on their quality of life. The purpose of this investigation is to explore the usage of a semantic similarity measure, called “Normalized Google Distance" (NGD), to enrich and increase the context of a health query. -
Microsoft Security Intelligence Report
Microsoft Security Intelligence Report Volume 11 An in-depth perspective on software vulnerabilities and exploits, malicious code threats, and potentially unwanted software in the first half of 2011 Microsoft Security Intelligence Report This document is for informational purposes only. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED, OR STATUTORY, AS TO THE INFORMATION IN THIS DOCUMENT. This document is provided “as-is.” Information and views expressed in this document, including URL and other Internet Web site references, may change without notice. You bear the risk of using it. Copyright © 2011 Microsoft Corporation. All rights reserved. The names of actual companies and products mentioned herein may be the trademarks of their respective owners. ii Authors Joe Faulhaber John Lambert Dave Probert Hemanth Srinivasan Microsoft Malware Protection Microsoft Security Microsoft Security Microsoft Malware Protection Center Engineering Center Engineering Center Center David Felstead Marc Lauricella Tim Rains Holly Stewart Bing Microsoft Trustworthy Microsoft Trustworthy Microsoft Malware Protection Computing Computing Center Paul Henry Wadeware LLC Aaron Margosis Mark E. Russinovich Matt Thomlinson Microsoft Public Sector Microsoft Technical Fellow Microsoft Security Response Jeff Jones Services Center Microsoft Trustworthy Weijuan Shi Computing Michelle Meyer Windows Business Group Jeff Williams Microsoft Trustworthy Microsoft Malware Protection Ellen Cram Kowalczyk Computing Adam Shostack Center Microsoft Trustworthy Microsoft Trustworthy