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  1. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.03
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    Abstract
    PageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor alpha that spreads uniformly part of the rank. The choice of alpha is eminently empirical, and in most cases the original suggestion alpha=0.85 by Brin and Page is still used. Recently, however, the behaviour of PageRank with respect to changes in alpha was discovered to be useful in link-spam detection. Moreover, an analytical justification of the value chosen for alpha is still missing. In this paper, we give the first mathematical analysis of PageRank when alpha changes. In particular, we show that, contrarily to popular belief, for real-world graphs values of alpha close to 1 do not give a more meaningful ranking. Then, we give closed-form formulae for PageRank derivatives of any order, and an extension of the Power Method that approximates them with convergence O(t**k*alpha**t) for the k-th derivative. Finally, we show a tight connection between iterated computation and analytical behaviour by proving that the k-th iteration of the Power Method gives exactly the PageRank value obtained using a Maclaurin polynomial of degree k. The latter result paves the way towards the application of analytical methods to the study of PageRank.
    Date
    16. 1.2016 10:22:28
    Type
    a
  2. Khare, R.; Cutting, D.; Sitaker, K.; Rifkin, A.: Nutch: a flexible and scalable open-source Web search engine (2004) 0.01
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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.
  3. Broder, A.; Kumar, R.; Maghoul, F.; Raghavan, P.; Rajagopalan, S.; Stata, R.; Tomkins, A.; Wiener, J.: Graph structure in the Web (2000) 0.01
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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. Overton, R.: Search engines get faster and faster, but not always better (1996) 0.01
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    Source
    PC world. 14(1996) Sept., S. -
    Type
    a
  5. Bryan, K.; Leise, T.: ¬The $25.000.000.000 eigenvector : the linear algebra behind Google 0.01
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    Abstract
    Google's success derives in large part from its PageRank algorithm, which ranks the importance of webpages according to an eigenvector of a weighted link matrix. Analysis of the PageRank formula provides a wonderful applied topic for a linear algebra course. Instructors may assign this article as a project to more advanced students, or spend one or two lectures presenting the material with assigned homework from the exercises. This material also complements the discussion of Markov chains in matrix algebra. Maple and Mathematica files supporting this material can be found at www.rose-hulman.edu/~bryan.
    Source
    SIAM review. 48(2006) no.3, S.569-581
    Type
    a
  6. Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999) 0.01
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  7. Campbell, K.: Understanding and comparing search engines (1996) 0.01
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    Abstract
    A meta-list of 11 other sites that critique search engines
  8. El-Ramly, N.; Peterson. R.E.; Volonino, L.: Top ten Web sites using search engines : the case of the desalination industry (1996) 0.01
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    Abstract
    The desalination industry involves the desalting of sea or brackish water and achieves the purpose of increasing the worls's effective water supply. There are approximately 4.000 desalination Web sites. The six major Internet search engines were used to determine, according to each of the six, the top twenty sites for desalination. Each site was visited and the 120 gross returns were pared down to the final ten - the 'Top Ten'. The Top Ten were then analyzed to determine what it was that made the sites useful and informative. The major attributes were: a) currency (up-to-date); b) search site capability; c) access to articles on desalination; d) newsletters; e) databases; f) product information; g) online conferencing; h) valuable links to other sites; l) communication links; j) site maps; and k) case studies. Reasons for having a Web site and the current status and prospects for Internet commerce are discussed
  9. Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006) 0.01
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    Abstract
    This paper introduces a family of link-based ranking algorithms that propagate page importance through links. In these algorithms there is a damping function that decreases with distance, so a direct link implies more endorsement than a link through a long path. PageRank is the most widely known ranking function of this family. The main objective of this paper is to determine whether this family of ranking techniques has some interest per se, and how different choices for the damping function impact on rank quality and on convergence speed. Even though our results suggest that PageRank can be approximated with other simpler forms of rankings that may be computed more efficiently, our focus is of more speculative nature, in that it aims at separating the kernel of PageRank, that is, link-based importance propagation, from the way propagation decays over paths. We focus on three damping functions, having linear, exponential, and hyperbolic decay on the lengths of the paths. The exponential decay corresponds to PageRank, and the other functions are new. Our presentation includes algorithms, analysis, comparisons and experiments that study their behavior under different parameters in real Web graph data. Among other results, we show how to calculate a linear approximation that induces a page ordering that is almost identical to PageRank's using a fixed small number of iterations; comparisons were performed using Kendall's tau on large domain datasets.
    Date
    16. 1.2016 10:22:28
    Type
    a
  10. Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004) 0.01
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    Abstract
    Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.
    Content
    Vgl. unter: http://www.dblab.ntua.gr/~bikakis/LD/5.pdf Vgl. auch: http://swoogle.umbc.edu/. Vgl. auch: http://ebiquity.umbc.edu/paper/html/id/183/. Vgl. auch: Radhakrishnan, A.: Swoogle : An Engine for the Semantic Web unter: http://www.searchenginejournal.com/swoogle-an-engine-for-the-semantic-web/5469/.
    Pages
    xx S
    Type
    a
  11. Spink, A.; Gunar, O.: E-Commerce Web queries : Excite and AskJeeves study (2001) 0.01
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  12. Dunning, A.: Do we still need search engines? (1999) 0.01
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    Source
    Ariadne. 1999, no.22
    Type
    a
  13. 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
  14. Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern (2017) 0.01
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    Footnote
    Bezug zum Buch: White, R.: Interactions with search systems. New York ; Cambridge University Press ; 2016.
    Type
    a
  15. Birmingham, J.: Internet search engines (1996) 0.00
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    Abstract
    Basically a good listing in table format of features from the major search engines
    Date
    10.11.1996 16:36:22
  16. Entlich, R.: FAQ: Image Search Engines (2001) 0.00
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    Abstract
    Everyone loves images. The web wasn't anything until images came along, then it was an overnight success. So how does one find a specific image on the web? By using one of a burgeoning number of image-focused search engines. These search engines are simply optimized versions of typical web indexes, with crawlers that go around sucking down web content and indexing it. But with image search engines, they focus on images only, and the web page text that may describe them. As information professionals, we know that this is a clumsy approach at best, but as the author puts it, until more sophisticated methods become available, the tools profiled here will "have to suffice." Seven search engines are thoroughly tested in this review article, with Google's Image Search (http://www.google.com/imghp?hl=en) being the highest rated
  17. Gillitzer, B.: Yewno (2017) 0.00
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    Date
    22. 2.2017 10:16:49
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. Tyner, R.: Sink or swim : Internet search tools & techniques (1996) 0.00
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  19. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.00
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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
  20. Lischka, K.; Kremp, M.: Was der Google-Gegner weiß - und was nicht (2009) 0.00
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