Search (46 results, page 2 of 3)

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  1. Hodson, H.: Google's fact-checking bots build vast knowledge bank (2014) 0.01 
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    Abstract
    The search giant is automatically building Knowledge Vault, a massive database that could give us unprecedented access to the world's facts GOOGLE is building the largest store of knowledge in human history - and it's doing so without any human help. Instead, Knowledge Vault autonomously gathers and merges information from across the web into a single base of facts about the world, and the people and objects in it.
  2. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.01 
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    Abstract
    Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.
  3. Broder, A.; Kumar, R.; Maghoul, F.; Raghavan, P.; Rajagopalan, S.; Stata, R.; Tomkins, A.; Wiener, J.: Graph structure in the Web (2000) 0.00 
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    Abstract
    The study of the web as a graph is not only fascinating in its own right, but also yields valuable insight into web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution. We report on experiments on local and global properties of the web graph using two Altavista crawls each with over 200M pages and 1.5 billion links. Our study indicates that the macroscopic structure of the web is considerably more intricate than suggested by earlier experiments on a smaller scale
  4. Zhao, Y.; Ma, F.; Xia, X.: Evaluating the coverage of entities in knowledge graphs behind general web search engines : Poster (2017) 0.00 
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    Abstract
    Web search engines, such as Google and Bing, are constantly employing results from knowledge organization and various visualization features to improve their search services. Knowledge graph, a large repository of structured knowledge represented by formal languages such as RDF (Resource Description Framework), is used to support entity search feature of Google and Bing (Demartini, 2016). When a user searchs for an entity, such as a person, an organization, or a place in Google or Bing, it is likely that a knowledge cardwill be presented on the right side bar of the search engine result pages (SERPs). For example, when a user searches the entity Benedict Cumberbatch on Google, the knowledge card will show the basic structured information about this person, including his date of birth, height, spouse, parents, and his movies, etc. The knowledge card, which is used to present the result of entity search, is generated from knowledge graphs. Therefore, the quality of knowledge graphs is essential to the performance of entity search. However, studies on the quality of knowledge graphs from the angle of entity coverage are scant in the literature. This study aims to investigate the coverage of entities of knowledge graphs behind Google and Bing.
  5. Koch, T.: Searching the Web : systematic overview over indexes (1995) 0.00 
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    Object
    Nordic Web Index
  6. Spink, A.; Gunar, O.: E-Commerce Web queries : Excite and AskJeeves study (2001) 0.00 
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  7. Sullivan D.: How search engines rank web pages (1998) 0.00 
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  8. Barlow, L.: ¬The spider's apprentice : how to use Web search engines (1997) 0.00 
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  9. Gerhart, S.L.: Do Web search engines suppress controversy? : Simulating the exchange process (2004) 0.00 
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  10. Bradley, P.: ¬The relevance of underpants to searching the Web (2000) 0.00 
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  11. Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999) 0.00 
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  12. Khare, R.; Cutting, D.; Sitaker, K.; Rifkin, A.: Nutch: a flexible and scalable open-source Web search engine (2004) 0.00 
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    Abstract
    Nutch is an open-source Web search engine that can be used at global, local, and even personal scale. Its initial design goal was to enable a transparent alternative for global Web search in the public interest - one of its signature features is the ability to "explain" its result rankings. Recent work has emphasized how it can also be used for intranets; by local communities with richer data models, such as the Creative Commons metadata-enabled search for licensed content; on a personal scale to index a user's files, email, and web-surfing history; and we also report on several other research projects built on Nutch. In this paper, we present how the architecture of the Nutch system enables it to be more flexible and scalable than other comparable systems today.
  13. Web search service features (2002) 0.00 
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    Abstract
    The table shows some of the features and techniques for the most common general Web search services to show how to use them and to help decide which may be the most appropriate. See the notes below that explain the headings. Each service also provides more detailed instructions. Note that some features will be available under an 'advanced', 'power' or other further search option and not from the main page.
  14. Advanced online media use (2023) 0.00 
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    Content
    "1. Use a range of different media 2. Access paywalled media content 3. Use an advertising and tracking blocker 4. Use alternatives to Google Search 5. Use alternatives to YouTube 6. Use alternatives to Facebook and Twitter 7. Caution with Wikipedia 8. Web browser, email, and internet access 9. Access books and scientific papers 10. Access deleted web content"
  15. Ogden, J.; Summers, E.; Walker, S.: Know(ing) Infrastructure : the wayback machine as object and instrument of digital research (2023) 0.00 
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    Abstract
    From documenting human rights abuses to studying online advertising, web archives are increasingly positioned as critical resources for a broad range of scholarly Internet research agendas. In this article, we reflect on the motivations and methodological challenges of investigating the world's largest web archive, the Internet Archive's Wayback Machine (IAWM). Using a mixed methods approach, we report on a pilot project centred around documenting the inner workings of 'Save Page Now' (SPN) - an Internet Archive tool that allows users to initiate the creation and storage of 'snapshots' of web resources. By improving our understanding of SPN and its role in shaping the IAWM, this work examines how the public tool is being used to 'save the Web' and highlights the challenges of operationalising a study of the dynamic sociotechnical processes supporting this knowledge infrastructure. Inspired by existing Science and Technology Studies (STS) approaches, the paper charts our development of methodological interventions to support an interdisciplinary investigation of SPN, including: ethnographic methods, 'experimental blackbox tactics', data tracing, modelling and documentary research. We discuss the opportunities and limitations of our methodology when interfacing with issues associated with temporality, scale and visibility, as well as critically engage with our own positionality in the research process (in terms of expertise and access). We conclude with reflections on the implications of digital STS approaches for 'knowing infrastructure', where the use of these infrastructures is unavoidably intertwined with our ability to study the situated and material arrangements of their creation.
  16. Koch, T.: Literature about search services (1996) 0.00 
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    Content
    Abschnitte: Search service comparisons; About search services and retrieval; Indexing the Internet; Collections and bibliographies
  17. Shneiderman, B.; Byrd, D.; Croft, W.B.: Clarifying search : a user-interface framework for text searches (1997) 0.00 
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    Footnote
    Vgl.: http://dlib.ukoln.ac.uk/dlib/january97/retrieval/01shneiderman.html.
  18. bbu/c't: Ask Jeeves mit verbesserten Suchfunktionen (2005) 0.00 
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    Abstract
    Mit nicht völlig neuen, aber überarbeiteten Suchfunktionen erweitert das zum Firmenimperium des US-Medienzaren Barry Diller gehörende Unternehmen Ask Jeeves das Leistungsspektrum seiner Suchmaschine. Mit der Ergebnisverfeinerungsfunktion Focus erhält der Suchende auf der rechten oberen Bildschirmseite eine Liste, die das Thema seiner Suche thematisch aufgliedern soll. Eine zweite Neuerung verspricht präzise Antworten auf als Fragen formulierte Sucheinträge. So ergibt der Eintrag "Lady Diana" zum Beispiel eine Liste mit den Items Princess Di, Princess Dianas Life, Princess Diana's Wedding. Interessant dabei ist, dass diese Liste nicht einfach aus einem monolithischen Block von Schlüsselwörtern besteht, sondern in drei Kategorien aufgeteilt ist: "Narrow Your Search", "Expand Your Search" und "Related Names". Waren die eben genannten Beispiele aus der ersten Kategorie, finden sich unter Expand Your Search Einträge wie Royal Family, Princess Di Ring, Princess Di Prince Charles History oder Prince William Harry, allerdings auch Who Is Louis De Funes? "Related Names" verweist auf Einträge wie Diana Spencer, Prince Harry oder Imran Khan. Die Suchfunktion soll also die thematische Verfeinerung oder Ausweitung gleichermaßen wie die Fortsetzung der Suche mit einem verwandten Thema ermöglichen. Auf die Frage "who invented the telephone" erhält der Suchende als ersten Eintrag die Antwort "The telephone was invented by Alexander Graham Bell" mit dem roten Vermerk "Web Answer'. Bemerkenswert ist hier, dass auf eine Frage nicht nur eine passende Webseite mit der Antwort angezeigt wird, sondern die ausformulierte Antwort direkt aus der vorgeschlagenen Webseite zitiert wird. Die Frage "who is the mother of Albert Einstein" gibt immerhin einen Eintrag unter "Narrow Your Search" mit "Albert Einstein Family tree". Ask Jeeves wird wohl noch eine weitere Neuerung bevorstehen: Auf einer Pressekonferenz in San Francisco bemerkte Chief Executive Barry Diller, dass das Unternehmen über eine Namensänderung von Ask Jeeves nachdenke. Wahrscheinlich werde auf eines der beiden Worte verzichtet werden. Mit dem Sucheintrag "How will Ask Jeeves be called in the future" erhält man bislang jedoch noch keine "Web Answer". (26.05.2005 15:30)
  19. Dunning, A.: Do we still need search engines? (1999) 0.00 
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    Source
    Ariadne. 1999, no.22
  20. Rogers, I.: ¬The Google Pagerank algorithm and how it works (2002) 0.00 
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    Abstract
    Page Rank is a topic much discussed by Search Engine Optimisation (SEO) experts. At the heart of PageRank is a mathematical formula that seems scary to look at but is actually fairly simple to understand. Despite this many people seem to get it wrong! In particular "Chris Ridings of www.searchenginesystems.net" has written a paper entitled "PageRank Explained: Everything you've always wanted to know about PageRank", pointed to by many people, that contains a fundamental mistake early on in the explanation! Unfortunately this means some of the recommendations in the paper are not quite accurate. By showing code to correctly calculate real PageRank I hope to achieve several things in this response: - Clearly explain how PageRank is calculated. - Go through every example in Chris' paper, and add some more of my own, showing the correct PageRank for each diagram. By showing the code used to calculate each diagram I've opened myself up to peer review - mostly in an effort to make sure the examples are correct, but also because the code can help explain the PageRank calculations. - Describe some principles and observations on website design based on these correctly calculated examples. Any good web designer should take the time to fully understand how PageRank really works - if you don't then your site's layout could be seriously hurting your Google listings! [Note: I have nothing in particular against Chris. If I find any other papers on the subject I'll try to comment evenly]

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