Search (22 results, page 1 of 2)

  • × theme_ss:"Suchmaschinen"
  • × type_ss:"el"
  • × year_i:[2010 TO 2020}
  1. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
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    Abstract
    This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.
    Date
    17.12.2013 11:02:22
    Type
    a
  2. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01 
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    Date
    19. 2.2019 17:22:00
    Type
    a
  3. Bauckhage, C.: Marginalizing over the PageRank damping factor (2014) 0.01 
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    Abstract
    In this note, we show how to marginalize over the damping parameter of the PageRank equation so as to obtain a parameter-free version known as TotalRank. Our discussion is meant as a reference and intended to provide a guided tour towards an interesting result that has applications in information retrieval and classification.
    Type
    a
  4. 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.
    Type
    a
  5. What is Schema.org? (2011) 0.01 
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    Abstract
    This site provides a collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google and Yahoo! rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure. A shared markup vocabulary makes easier for webmasters to decide on a markup schema and get the maximum benefit for their efforts. So, in the spirit of sitemaps.org, Bing, Google and Yahoo! have come together to provide a shared collection of schemas that webmasters can use.
  6. Li, Z.: ¬A domain specific search engine with explicit document relations (2013) 0.01 
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    Abstract
    The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.
  7. Zhao, Y.; Ma, F.; Xia, X.: Evaluating the coverage of entities in knowledge graphs behind general web search engines : Poster (2017) 0.01 
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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.
    Type
    a
  8. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.00 
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    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
  9. Tetzchner, J. von: As a monopoly in search and advertising Google is not able to resist the misuse of power : is the Internet turning into a battlefield of propaganda? How Google should be regulated (2017) 0.00 
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    Content
    "Let us start with your positive experiences with Google. I have known Google longer than most. At Opera, we were the first to add their search into the browser interface, enabling it directly from the search box and the address field. At that time, Google was an up-and-coming geeky company. I remember vividly meeting with Google's co-founder Larry Page, his relaxed dress code and his love for the Danger device, which he played with throughout our meeting. Later, I met with the other co-founder of Google, Sergey Brin, and got positive vibes. My first impression of Google was that it was a likeable company. Our cooperation with Google was a good one. Integrating their search into Opera helped us deliver a better service to our users and generated revenue that paid the bills. We helped Google grow, along with others that followed in our footsteps and integrated Google search into their browsers. Then the picture for you and for opera darkened. Yes, then things changed. Google increased their proximity with the Mozilla foundation. They also introduced new services such as Google Docs. These services were great, gained quick popularity, but also exposed the darker side of Google. Not only were these services made to be incompatible with Opera, but also encouraged users to switch their browsers. I brought this up with Sergey Brin, in vain. For millions of Opera users to be able to access these services, we had to hide our browser's identity. The browser sniffing situation only worsened after Google started building their own browser, Chrome. ...
    How should Google be regulated? We should limit the amount of information that is being collected. In particular we should look at information that is being collected across sites. It should not be legal to combine data from multiple sites and services. The fact that these sites and services are using the same underlying technology does not change the fact that the user's dealings is with a site at a time and each site should not have the right to share the data with others. I believe this the cornerstone of laws in many countries today, but these laws need to be enforced. Data about us is ours alone and it should not be possible to sell it. We should also limit the ability to target users individually. In the past, ads on sites were ads on sites. You might know what kind of users visited a site and you would place tech ads on tech sites and fashion ads on fashion sites. Now the ads follow you individually. That should be made illegal as it uses data collected from multiple sources and invades our privacy. I also believe there should be regulation as to how location data is used and any information related to our mobile devices. In addition, regulators need to be vigilant as to how companies that have monopoly power use their power. That kind of goes without saying. Companies with monopoly powers should not be able to use those powers when competing in an open market or using their monopoly services to limit competition."
    Type
    a
  10. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.00 
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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.
    Type
    a
  11. Günther, M.: Vermitteln Suchmaschinen vollständige Bilder aktueller Themen? : Untersuchung der Gewichtung inhaltlicher Aspekte von Suchmaschinenergebnissen in Deutschland und den USA (2016) 0.00 
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    Source
    Young information scientists. 1(2016), S.13-29
    Type
    a
  12. Gillitzer, B.: Yewno (2017) 0.00 
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    Date
    22. 2.2017 10:16:49
  13. Haynes, M.: Your Google algorithm cheat sheet : Panda, Penguin, and Hummingbird (2013) 0.00 
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    Abstract
    If you're reading the Moz blog, then you probably have a decent understanding of Google and its algorithm changes. However, there is probably a good percentage of the Moz audience that is still confused about the effects that Panda, Penguin, and Hummingbird can have on your site. I did write a post last year about the main differences between Penguin and a Manual Unnautral Links Penalty, and if you haven't read that, it'll give you a good primer. The point of this article is to explain very simply what each of these algorithms are meant to do. It is hopefully a good reference that you can point your clients to if you want to explain an algorithm change and not overwhelm them with technical details about 301s, canonicals, crawl errors, and other confusing SEO terminologies.
  14. Fiorelli, G.: Hummingbird unleashed (2013) 0.00 
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    Abstract
    Sometimes I think that us SEOs could be wonderful characters for a Woody Allen movie: We are stressed, nervous, paranoid, we have a tendency for sudden changes of mood...okay, maybe I am exaggerating a little bit, but that's how we tend to (over)react whenever Google announces something. One thing that doesn't help is the lack of clarity coming from Google, which not only never mentions Hummingbird in any official document (for example, in the post of its 15th anniversary), but has also shied away from details of this epochal update in the "off-the-record" declarations of Amit Singhal. In fact, in some ways those statements partly contributed to the confusion. When Google announces an update-especially one like Hummingbird-the best thing to do is to avoid trying to immediately understand what it really is based on intuition alone. It is better to wait until the dust falls to the ground, recover the original documents, examine those related to them (and any variants), take the time to see the update in action, calmly investigate, and then after all that try to find the most plausible answers.
  15. Hurz, S.: Google verfolgt Nutzer, auch wenn sie explizit widersprechen (2018) 0.00 
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  16. Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern (2017) 0.00 
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  17. Franke-Maier, M.; Rüter, C.: Discover Sacherschließung! : Was machen suchmaschinenbasierte Systeme mit unseren inhaltlichen Metadaten? (2015) 0.00 
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  18. Griesbaum, J.: Online Marketing : Ein Lehr- und Forschungsgebiet der Informationswissenschaft? (2019) 0.00 
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  19. Sander-Beuermann, W.: Generationswechsel bei MetaGer : ein Rückblick und Ausblick (2019) 0.00 
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  20. Söhler, M.: Schluss mit Schema F (2011) 0.00 
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