Search (362 results, page 1 of 19)

  • × theme_ss:"Retrievalalgorithmen"
  1. Sembok, T.M.T.; Rijsbergen, C.J. van: IMAGING: a relevant feedback retrieval with nearest neighbour clusters (1994) 0.09 
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    Abstract
    Reports on a study to implement and evaluate imaging retrieval as a relevance feedback retrieval technique with nearest neighbour clusters. Results obtained from experiments show the viability and validity of this strategy and support it as something worth further investigation
    Pages
    S.91-107
    Source
    Information retrieval: new systems and current research. Proceedings of the 15th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Glasgow 1993. Ed.: Ruben Leon
    Type
    a
  2. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.06 
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    Date
    13. 9.2014 14:45:22
    Pages
    91 S
  3. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.05 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
    Type
    a
  4. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.05 
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    Date
    25. 8.2005 17:42:22
    Source
    Library and information research news. 24(2000) no.77, S.30-34
    Type
    a
  5. Wills, R.S.: Google's PageRank : the math behind the search engine (2006) 0.05 
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    Abstract
    Approximately 91 million American adults use the Internet on a typical day The number-one Internet activity is reading and writing e-mail. Search engine use is next in line and continues to increase in popularity. In fact, survey findings indicate that nearly 60 million American adults use search engines on a given day. Even though there are many Internet search engines, Google, Yahoo!, and MSN receive over 81% of all search requests. Despite claims that the quality of search provided by Yahoo! and MSN now equals that of Google, Google continues to thrive as the search engine of choice, receiving over 46% of all search requests, nearly double the volume of Yahoo! and over four times that of MSN. I use Google's search engine on a daily basis and rarely request information from other search engines. One day, I decided to visit the homepages of Google. Yahoo!, and MSN to compare the quality of search results. Coffee was on my mind that day, so I entered the simple query "coffee" in the search box at each homepage. Table 1 shows the top ten (unsponsored) results returned by each search engine. Although ordered differently, two webpages, www.peets.com and www.coffeegeek.com, appear in all three top ten lists. In addition, each pairing of top ten lists has two additional results in common. Depending on the information I hoped to obtain about coffee by using the search engines, I could argue that any one of the three returned better results: however, I was not looking for a particular webpage, so all three listings of search results seemed of equal quality. Thus, I plan to continue using Google. My decision is indicative of the problem Yahoo!, MSN, and other search engine companies face in the quest to obtain a larger percentage of Internet search volume. Search engine users are loyal to one or a few search engines and are generally happy with search results. Thus, as long as Google continues to provide results deemed high in quality, Google likely will remain the top search engine. But what set Google apart from its competitors in the first place? The answer is PageRank. In this article I explain this simple mathematical algorithm that revolutionized Web search.
    Type
    a
  6. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.04 
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    Abstract
    We propose a novel approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. The ability of the logic to handle expressive representations along with the use of such classical notions are promising characteristics for IR systems. The approach proposed here has been efficiently implemented and experiments against test collections are presented.
    Date
    22. 3.2003 19:27:23
    Footnote
    Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.285-301
    Type
    a
  7. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.03 
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    Abstract
    Keyword based querying has been an immediate and efficient way to specify and retrieve related information that the user inquired. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given. Proposes an idea to integrate 2 existing techniques, query expansion and relevance feedback to achieve a concept-based information search for the Web
    Date
    1. 8.1996 22:08:06
    Footnote
    Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia
    Type
    a
  8. Faloutsos, C.: Signature files (1992) 0.03 
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    Abstract
    Presents a survey and discussion on signature-based text retrieval methods. It describes the main idea behind the signature approach and its advantages over other text retrieval methods, it provides a classification of the signature methods that have appeared in the literature, it describes the main representatives of each class, together with the relative advantages and drawbacks, and it gives a list of applications as well as commercial or university prototypes that use the signature approach
    Date
    7. 5.1999 15:22:48
    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
    Type
    a
  9. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.03 
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    Abstract
    Properties of a percentile-based rating scale needed in bibliometrics are formulated. Based on these properties, P100 was recently introduced as a new citation-rank approach (Bornmann, Leydesdorff, & Wang, 2013). In this paper, we conceptualize P100 and propose an improvement which we call P100'. Advantages and disadvantages of citation-rank indicators are noted.
    Date
    22. 8.2014 17:05:18
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
    Type
    a
  10. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.03 
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    Abstract
    The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
    Date
    16.11.2008 16:22:48
    Type
    a
  11. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.03 
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    Abstract
    Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.
    Date
    22. 3.2003 19:35:46
    Footnote
    Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.321-334
    Type
    a
  12. Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.03 
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    Abstract
    Research an the use of mathematical, logical, and formal methods, has been central to Information Retrieval research for a long time. Research in this area is important not only because it helps enhancing retrieval effectiveness, but also because it helps clarifying the underlying concepts of Information Retrieval. In this article we outline some of the major aspects of the subject, and summarize the papers of this special issue with respect to how they relate to these aspects. We conclude by highlighting some directions of future research, which are needed to better understand the formal characteristics of Information Retrieval.
    Date
    22. 3.2003 19:27:36
    Footnote
    Einführung zu den Beiträgen eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.281-284
    Type
    a
  13. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.03 
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    Abstract
    Im Rahmen des klassischen Information Retrieval wurden verschiedene Verfahren für das Ranking sowie die Suche in einer homogenen strukturlosen Dokumentenmenge entwickelt. Die Erfolge der Suchmaschine Google haben gezeigt dass die Suche in einer zwar inhomogenen aber zusammenhängenden Dokumentenmenge wie dem Internet unter Berücksichtigung der Dokumentenverbindungen (Links) sehr effektiv sein kann. Unter den von der Suchmaschine Google realisierten Konzepten ist ein Verfahren zum Ranking von Suchergebnissen (PageRank), das in diesem Artikel kurz erklärt wird. Darüber hinaus wird auf die Konzepte eines Systems namens CiteSeer eingegangen, welches automatisch bibliographische Angaben indexiert (engl. Autonomous Citation Indexing, ACI). Letzteres erzeugt aus einer Menge von nicht vernetzten wissenschaftlichen Dokumenten eine zusammenhängende Dokumentenmenge und ermöglicht den Einsatz von Banking-Verfahren, die auf den von Google genutzten Verfahren basieren.
    Date
    20. 3.2005 16:23:22
    Source
    Information - Wissenschaft und Praxis. 56(2005) H.2, S.87-92
    Type
    a
  14. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.03 
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    Abstract
    Relevance Feedback consists in automatically formulating a new query according to the relevance judgments provided by the user after evaluating a set of retrieved documents. In this article, we introduce several relevance feedback methods for the Bayesian Network Retrieval ModeL The theoretical frame an which our methods are based uses the concept of partial evidences, which summarize the new pieces of information gathered after evaluating the results obtained by the original query. These partial evidences are inserted into the underlying Bayesian network and a new inference process (probabilities propagation) is run to compute the posterior relevance probabilities of the documents in the collection given the new query. The quality of the proposed methods is tested using a preliminary experimentation with different standard document collections.
    Date
    22. 3.2003 19:30:19
    Footnote
    Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.302-313
    Type
    a
  15. Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015) 0.03 
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    Abstract
    Purpose In a system-based approach, replicating the web would require large test collections, and judging the relevancy of all documents per topic in creating relevance judgment through human assessors is infeasible. Due to the large amount of documents that requires judgment, there are possible errors introduced by human assessors because of disagreements. The paper aims to discuss these issues. Design/methodology/approach This study explores exponential variation and document ranking methods that generate a reliable set of relevance judgments (pseudo relevance judgments) to reduce human efforts. These methods overcome problems with large amounts of documents for judgment while avoiding human disagreement errors during the judgment process. This study utilizes two key factors: number of occurrences of each document per topic from all the system runs; and document rankings to generate the alternate methods. Findings The effectiveness of the proposed method is evaluated using the correlation coefficient of ranked systems using mean average precision scores between the original Text REtrieval Conference (TREC) relevance judgments and pseudo relevance judgments. The results suggest that the proposed document ranking method with a pool depth of 100 could be a reliable alternative to reduce human effort and disagreement errors involved in generating TREC-like relevance judgments. Originality/value Simple methods proposed in this study show improvement in the correlation coefficient in generating alternate relevance judgment without human assessors while contributing to information retrieval evaluation.
    Date
    20. 1.2015 18:30:22
    18. 9.2018 18:22:56
    Source
    Aslib journal of information management. 67(2015) no.6, S.700-714
    Type
    a
  16. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.02 
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    Abstract
    Genetic-based evolutionary learning algorithms, such as genetic algorithms (GAs) and genetic programming (GP), have been applied to information retrieval (IR) since the 1980s. Recently, GP has been applied to a new IR taskdiscovery of ranking functions for Web search-and has achieved very promising results. However, in our prior research, only one fitness function has been used for GP-based learning. It is unclear how other fitness functions may affect ranking function discovery for Web search, especially since it is weIl known that choosing a proper fitness function is very important for the effectiveness and efficiency of evolutionary algorithms. In this article, we report our experience in contrasting different fitness function designs an GP-based learning using a very large Web corpus. Our results indicate that the design of fitness functions is instrumental in performance improvement. We also give recommendations an the design of fitness functions for genetic-based information retrieval experiments.
    Date
    31. 5.2004 19:22:06
    Source
    Journal of the American Society for Information Science and technology. 55(2004) no.7, S.628-636
    Type
    a
  17. Witschel, H.F.: Global term weights in distributed environments (2008) 0.02 
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    Abstract
    This paper examines the estimation of global term weights (such as IDF) in information retrieval scenarios where a global view on the collection is not available. In particular, the two options of either sampling documents or of using a reference corpus independent of the target retrieval collection are compared using standard IR test collections. In addition, the possibility of pruning term lists based on frequency is evaluated. The results show that very good retrieval performance can be reached when just the most frequent terms of a collection - an "extended stop word list" - are known and all terms which are not in that list are treated equally. However, the list cannot always be fully estimated from a general-purpose reference corpus, but some "domain-specific stop words" need to be added. A good solution for achieving this is to mix estimates from small samples of the target retrieval collection with ones derived from a reference corpus.
    Date
    1. 8.2008 9:44:22
    Source
    Information processing and management. 44(2008) no.3, S.1049-1061
    Type
    a
  18. Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.02 
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    Abstract
    Proposes that signature files be used as a viable alternative to other indexing strategies such as inverted files for searching through large volumes of text. Demonstrates through simulation, that search times can be further reduced by enhancing the basic signature file concept using deterministic partitioning algorithms which eliminate the need for an exhaustive search of the entire signature file. Reports research to evaluate the performance of some deterministic partitioning algorithms in a non simulated environment using 276 MB of raw newspaper text (taken from the Wall Street Journal) and real user queries. Presents a selection of results to illustrate trends and highlight important aspects of the performance of these methods under realistic rather than simulated operating conditions. As a result of the research reported here certain aspects of this approach to signature files are shown to be found wanting and require improvement. Suggests lines of future research on the partitioning of signature files
    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
    Type
    a
  19. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.02 
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    Abstract
    This book offers a comprehensive and consistent mathematical approach to information retrieval (IR) without which no implementation is possible, and sheds an entirely new light upon the structure of IR models. It contains the descriptions of all IR models in a unified formal style and language, along with examples for each, thus offering a comprehensive overview of them. The book also creates mathematical foundations and a consistent mathematical theory (including all mathematical results achieved so far) of IR as a stand-alone mathematical discipline, which thus can be read and taught independently. Also, the book contains all necessary mathematical knowledge on which IR relies, to help the reader avoid searching different sources. The book will be of interest to computer or information scientists, librarians, mathematicians, undergraduate students and researchers whose work involves information retrieval.
    Date
    22. 3.2008 12:26:32
    LCSH
    Information storage and retrieval
    Subject
    Information storage and retrieval
  20. Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013) 0.02 
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    Abstract
    A new challenge, accessing multiple relevant entities, arises from the availability of linked heterogeneous data. In this article, we address more specifically the problem of accessing relevant entities, such as publications and authors within a bibliographic network, given an information need. We propose a novel algorithm, called BibRank, that estimates a joint relevance of documents and authors within a bibliographic network. This model ranks each type of entity using a score propagation algorithm with respect to the query topic and the structure of the underlying bi-type information entity network. Evidence sources, namely content-based and network-based scores, are both used to estimate the topical similarity between connected entities. For this purpose, authorship relationships are analyzed through a language model-based score on the one hand and on the other hand, non topically related entities of the same type are detected through marginal citations. The article reports the results of experiments using the Bibrank algorithm for an information retrieval task. The CiteSeerX bibliographic data set forms the basis for the topical query automatic generation and evaluation. We show that a statistically significant improvement over closely related ranking models is achieved.
    Date
    22. 3.2013 19:34:49
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.500-515
    Type
    a

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