Search (149 results, page 1 of 8)

  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[2000 TO 2010}
  1. Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.03
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    Abstract
    The rapid development of the Internet and World Wide Web has caused some critical problem for information retrieval. Researchers have made several attempts to solve these problems. Thesauri and subject heading lists as traditional information retrieval tools have been criticised for their efficiency to tackle these newly emerging problems. This paper proposes an information retrieval tool generated by cocitation analysis, comprising keyword clusters with relationships based on the co-occurrences of keywords in the literature. Such a tool can play the role of an associative thesaurus that can provide information about the keywords in a domain that might be useful for information searching and query expansion
  2. Picard, J.; Savoy, J.: Enhancing retrieval with hyperlinks : a general model based on propositional argumentation systems (2003) 0.03
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    Abstract
    Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information an the ever-increasing World Wide Web. In that respect, different strategies have been suggested to take hypertext links into account. For example, hyperlinks have been used to (1) enhance document representation, (2) improve document ranking by propagating document score, (3) provide an indicator of popularity, and (4) find hubs and authorities for a given topic. Although the TREC experiments have not demonstrated the usefulness of hyperlinks for retrieval, the hypertext structure is nevertheless an essential aspect of the Web, and as such, should not be ignored. The development of abstract models of the IR task was a key factor to the improvement of search engines. However, at this time conceptual tools for modeling the hypertext retrieval task are lacking, making it difficult to compare, improve, and reason an the existing techniques. This article proposes a general model for using hyperlinks based an Probabilistic Argumentation Systems, in which each of the above-mentioned techniques can be stated. This model will allow to discover some inconsistencies in the mentioned techniques, and to take a higher level and systematic approach for using hyperlinks for retrieval.
    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.347-355
  3. 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
  4. Meghabghab, G.: Google's Web page ranking applied to different topological Web graph structures (2001) 0.02
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    Abstract
    This research is part of the ongoing study to better understand web page ranking on the web. It looks at a web page as a graph structure or a web graph, and tries to classify different web graphs in the new coordinate space: (out-degree, in-degree). The out-degree coordinate od is defined as the number of outgoing web pages from a given web page. The in-degree id coordinate is the number of web pages that point to a given web page. In this new coordinate space a metric is built to classify how close or far different web graphs are. Google's web ranking algorithm (Brin & Page, 1998) on ranking web pages is applied in this new coordinate space. The results of the algorithm has been modified to fit different topological web graph structures. Also the algorithm was not successful in the case of general web graphs and new ranking web algorithms have to be considered. This study does not look at enhancing web ranking by adding any contextual information. It only considers web links as a source to web page ranking. The author believes that understanding the underlying web page as a graph will help design better ranking web algorithms, enhance retrieval and web performance, and recommends using graphs as a part of visual aid for browsing engine designers
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.9, S.736-747
  5. Mandl, T.: Web- und Multimedia-Dokumente : Neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen (2003) 0.02
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    Abstract
    Die Menge an Daten im Internet steigt weiter rapide an. Damit wächst auch der Bedarf an qualitativ hochwertigen Information Retrieval Diensten zur Orientierung und problemorientierten Suche. Die Entscheidung für die Benutzung oder Beschaffung von Information Retrieval Software erfordert aussagekräftige Evaluierungsergebnisse. Dieser Beitrag stellt neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen vor und zeigt den Trend zu Spezialisierung und Diversifizierung von Evaluierungsstudien, die den Realitätsgrad derErgebnisse erhöhen. DerSchwerpunkt liegt auf dem Retrieval von Fachtexten, Internet-Seiten und Multimedia-Objekten.
    Source
    Information - Wissenschaft und Praxis. 54(2003) H.4, S.203-210
  6. Henzinger, M.R.: Hyperlink analysis for the Web (2001) 0.02
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    Abstract
    Hyperlink analysis algorithms allow search engines to deliver focused results to user queries.This article surveys ranking algorithms used to retrieve information on the Web.
    Content
    Information retrieval is a computer science subfield whose goal is to find all documents relevant to a user query in a given collection of documents. As such, information retrieval should really be called document retrieval. Before the advent of the Web, IR systems were typically installed in libraries for use mostly by reference librarians. The retrieval algorithm for these systems was usually based exclusively on analysis of the words in the document. The Web changed all this. Now each Web user has access to various search engines whose retrieval algorithms often use not only the words in the documents but also information like the hyperlink structure of the Web or markup language tags. How are hyperlinks useful? The hyperlink functionality alone-that is, the hyperlink to Web page B that is contained in Web page A-is not directly useful in information retrieval. However, the way Web page authors use hyperlinks can give them valuable information content. Authors usually create hyperlinks they think will be useful to readers. Some may be navigational aids that, for example, take the reader back to the site's home page; others provide access to documents that augment the content of the current page. The latter tend to point to highquality pages that might be on the same topic as the page containing the hyperlink. Web information retrieval systems can exploit this information to refine searches for relevant documents. Hyperlink analysis significantly improves the relevance of the search results, so much so that all major Web search engines claim to use some type of hyperlink analysis. However, the search engines do not disclose details about the type of hyperlink analysis they perform- mostly to avoid manipulation of search results by Web-positioning companies. In this article, I discuss how hyperlink analysis can be applied to ranking algorithms, and survey other ways Web search engines can use this analysis.
  7. Dominich, S.; Skrop, A.: PageRank and interaction information retrieval (2005) 0.02
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    Abstract
    The PageRank method is used by the Google Web search engine to compute the importance of Web pages. Two different views have been developed for the Interpretation of the PageRank method and values: (a) stochastic (random surfer): the PageRank values can be conceived as the steady-state distribution of a Markov chain, and (b) algebraic: the PageRank values form the eigenvector corresponding to eigenvalue 1 of the Web link matrix. The Interaction Information Retrieval (1**2 R) method is a nonclassical information retrieval paradigm, which represents a connectionist approach based an dynamic systems. In the present paper, a different Interpretation of PageRank is proposed, namely, a dynamic systems viewpoint, by showing that the PageRank method can be formally interpreted as a particular case of the Interaction Information Retrieval method; and thus, the PageRank values may be interpreted as neutral equilibrium points of the Web.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.1, S.63-69
  8. Effektive Information Retrieval Verfahren in Theorie und Praxis : ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005 (2006) 0.02
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    Abstract
    Information Retrieval hat sich zu einer Schlüsseltechnologie in der Wissensgesellschaft entwickelt. Die Anzahl der täglichen Anfragen an Internet-Suchmaschinen bildet nur einen Indikator für die große Bedeutung dieses Themas. Der Sammelbandband informiert über Themen wie Information Retrieval-Grundlagen, Retrieval Systeme, Digitale Bibliotheken, Evaluierung und Multilinguale Systeme, beschreibt Anwendungsszenarien und setzt sich mit neuen Herausforderungen an das Information Retrieval auseinander. Die Beiträge behandeln aktuelle Themen und neue Herausforderungen an das Information Retrieval. Die intensive Beteiligung der Informationswissenschaft der Universität Hildesheim am Cross Language Evaluation Forum (CLEF), einer europäischen Evaluierungsinitiative zur Erforschung mehrsprachiger Retrieval Systeme, berührt mehrere der Beiträge. Ebenso spielen Anwendungsszenarien und die Auseinandersetzung mit aktuellen und praktischen Fragestellungen eine große Rolle.
    Content
    Inhalt: Jan-Hendrik Scheufen: RECOIN: Modell offener Schnittstellen für Information-Retrieval-Systeme und -Komponenten Markus Nick, Klaus-Dieter Althoff: Designing Maintainable Experience-based Information Systems Gesine Quint, Steffen Weichert: Die benutzerzentrierte Entwicklung des Produkt- Retrieval-Systems EIKON der Blaupunkt GmbH Claus-Peter Klas, Sascha Kriewel, André Schaefer, Gudrun Fischer: Das DAFFODIL System - Strategische Literaturrecherche in Digitalen Bibliotheken Matthias Meiert: Entwicklung eines Modells zur Integration digitaler Dokumente in die Universitätsbibliothek Hildesheim Daniel Harbig, René Schneider: Ontology Learning im Rahmen von MyShelf Michael Kluck, Marco Winter: Topic-Entwicklung und Relevanzbewertung bei GIRT: ein Werkstattbericht Thomas Mandl: Neue Entwicklungen bei den Evaluierungsinitiativen im Information Retrieval Joachim Pfister: Clustering von Patent-Dokumenten am Beispiel der Datenbanken des Fachinformationszentrums Karlsruhe Ralph Kölle, Glenn Langemeier, Wolfgang Semar: Programmieren lernen in kollaborativen Lernumgebungen Olga Tartakovski, Margaryta Shramko: Implementierung eines Werkzeugs zur Sprachidentifikation in mono- und multilingualen Texten Nina Kummer: Indexierungstechniken für das japanische Retrieval Suriya Na Nhongkai, Hans-Joachim Bentz: Bilinguale Suche mittels Konzeptnetzen Robert Strötgen, Thomas Mandl, René Schneider: Entwicklung und Evaluierung eines Question Answering Systems im Rahmen des Cross Language Evaluation Forum (CLEF) Niels Jensen: Evaluierung von mehrsprachigem Web-Retrieval: Experimente mit dem EuroGOV-Korpus im Rahmen des Cross Language Evaluation Forum (CLEF)
    Footnote
    Rez. in: Information - Wissenschaft und Praxis 57(2006) H.5, S.290-291 (C. Schindler): "Weniger als ein Jahr nach dem "Vierten Hildesheimer Evaluierungs- und Retrievalworkshop" (HIER 2005) im Juli 2005 ist der dazugehörige Tagungsband erschienen. Eingeladen hatte die Hildesheimer Informationswissenschaft um ihre Forschungsergebnisse und die einiger externer Experten zum Thema Information Retrieval einem Fachpublikum zu präsentieren und zur Diskussion zu stellen. Unter dem Titel "Effektive Information Retrieval Verfahren in Theorie und Praxis" sind nahezu sämtliche Beiträge des Workshops in dem nun erschienenen, 15 Beiträge umfassenden Band gesammelt. Mit dem Schwerpunkt Information Retrieval (IR) wird ein Teilgebiet der Informationswissenschaft vorgestellt, das schon immer im Zentrum informationswissenschaftlicher Forschung steht. Ob durch den Leistungsanstieg von Prozessoren und Speichermedien, durch die Verbreitung des Internet über nationale Grenzen hinweg oder durch den stetigen Anstieg der Wissensproduktion, festzuhalten ist, dass in einer zunehmend wechselseitig vernetzten Welt die Orientierung und das Auffinden von Dokumenten in großen Wissensbeständen zu einer zentralen Herausforderung geworden sind. Aktuelle Verfahrensweisen zu diesem Thema, dem Information Retrieval, präsentiert der neue Band anhand von praxisbezogenen Projekten und theoretischen Diskussionen. Das Kernthema Information Retrieval wird in dem Sammelband in die Bereiche Retrieval-Systeme, Digitale Bibliothek, Evaluierung und Multilinguale Systeme untergliedert. Die Artikel der einzelnen Sektionen sind insgesamt recht heterogen und bieten daher keine Überschneidungen inhaltlicher Art. Jedoch ist eine vollkommene thematische Abdeckung der unterschiedlichen Bereiche ebenfalls nicht gegeben, was bei der Präsentation von Forschungsergebnissen eines Institutes und seiner Kooperationspartner auch nur bedingt erwartet werden kann. So lässt sich sowohl in der Gliederung als auch in den einzelnen Beiträgen eine thematische Verdichtung erkennen, die das spezielle Profil und die Besonderheit der Hildesheimer Informationswissenschaft im Feld des Information Retrieval wiedergibt. Teil davon ist die mehrsprachige und interdisziplinäre Ausrichtung, die die Schnittstellen zwischen Informationswissenschaft, Sprachwissenschaft und Informatik in ihrer praxisbezogenen und internationalen Forschung fokussiert.
    Im ersten Kapitel "Retrieval-Systeme" werden verschiedene Information RetrievalSysteme präsentiert und Verfahren zu deren Gestaltung diskutiert. Jan-Hendrik Scheufen stellt das Meta-Framework RECOIN zur Information Retrieval Forschung vor, das sich durch eine flexible Handhabung unterschiedlichster Applikationen auszeichnet und dadurch eine zentrierte Protokollierung und Steuerung von Retrieval-Prozessen ermöglicht. Dieses Konzept eines offenen, komponentenbasierten Systems wurde in Form eines Plug-Ins für die javabasierte Open-Source-Plattform Eclipse realisiert. Markus Nick und Klaus-Dieter Althoff erläutern in ihrem Beitrag, der übrigens der einzige englischsprachige Text im Buch ist, das Verfahren DILLEBIS zur Erhaltung und Pflege (Maintenance) von erfahrungsbasierten Informationssystemen. Sie bezeichnen dieses Verfahren als Maintainable Experience-based Information System und plädieren für eine Ausrichtung von erfahrungsbasierten Systemen entsprechend diesem Modell. Gesine Quint und Steffen Weichert stellen dagegen in ihrem Beitrag die benutzerzentrierte Entwicklung des Produkt-Retrieval-Systems EIKON vor, das in Kooperation mit der Blaupunkt GmbH realisiert wurde. In einem iterativen Designzyklus erfolgte die Gestaltung von gruppenspezifischen Interaktionsmöglichkeiten für ein Car-Multimedia-Zubehör-System. Im zweiten Kapitel setzen sich mehrere Autoren dezidierter mit dem Anwendungsgebiet "Digitale Bibliothek" auseinander. Claus-Peter Klas, Sascha Kriewel, Andre Schaefer und Gudrun Fischer von der Universität Duisburg-Essen stellen das System DAFFODIL vor, das durch eine Vielzahl an Werkzeugen zur strategischen Unterstützung bei Literaturrecherchen in digitalen Bibliotheken dient. Zusätzlich ermöglicht die Protokollierung sämtlicher Ereignisse den Einsatz des Systems als Evaluationsplattform. Der Aufsatz von Matthias Meiert erläutert die Implementierung von elektronischen Publikationsprozessen an Hochschulen am Beispiel von Abschlussarbeiten des Studienganges Internationales Informationsmanagement der Universität Hildesheim. Neben Rahmenbedingungen werden sowohl der Ist-Zustand als auch der Soll-Zustand des wissenschaftlichen elektronischen Publizierens in Form von gruppenspezifischen Empfehlungen dargestellt. Daniel Harbig und Rene Schneider beschreiben in ihrem Aufsatz zwei Verfahrensweisen zum maschinellen Erlernen von Ontologien, angewandt am virtuellen Bibliotheksregal MyShelf. Nach der Evaluation dieser beiden Ansätze plädieren die Autoren für ein semi-automatisiertes Verfahren zur Erstellung von Ontologien.
    "Evaluierung", das Thema des dritten Kapitels, ist in seiner Breite nicht auf das Information Retrieval beschränkt sondern beinhaltet ebenso einzelne Aspekte der Bereiche Mensch-Maschine-Interaktion sowie des E-Learning. Michael Muck und Marco Winter von der Stiftung Wissenschaft und Politik sowie dem Informationszentrum Sozialwissenschaften thematisieren in ihrem Beitrag den Einfluss der Fragestellung (Topic) auf die Bewertung von Relevanz und zeigen Verfahrensweisen für die Topic-Erstellung auf, die beim Cross Language Evaluation Forum (CLEF) Anwendung finden. Im darauf folgenden Aufsatz stellt Thomas Mandl verschiedene Evaluierungsinitiativen im Information Retrieval und aktuelle Entwicklungen dar. Joachim Pfister erläutert in seinem Beitrag das automatisierte Gruppieren, das sogenannte Clustering, von Patent-Dokumenten in den Datenbanken des Fachinformationszentrums Karlsruhe und evaluiert unterschiedliche Clusterverfahren auf Basis von Nutzerbewertungen. Ralph Kölle, Glenn Langemeier und Wolfgang Semar widmen sich dem kollaborativen Lernen unter den speziellen Bedingungen des Programmierens. Dabei werden das System VitaminL zur synchronen Bearbeitung von Programmieraufgaben und das Kennzahlensystem K-3 für die Bewertung kollaborativer Zusammenarbeit in einer Lehrveranstaltung angewendet. Der aktuelle Forschungsschwerpunkt der Hildesheimer Informationswissenschaft zeichnet sich im vierten Kapitel unter dem Thema "Multilinguale Systeme" ab. Hier finden sich die meisten Beiträge des Tagungsbandes wieder. Olga Tartakovski und Margaryta Shramko beschreiben und prüfen das System Langldent, das die Sprache von mono- und multilingualen Texten identifiziert. Die Eigenheiten der japanischen Schriftzeichen stellt Nina Kummer dar und vergleicht experimentell die unterschiedlichen Techniken der Indexierung. Suriya Na Nhongkai und Hans-Joachim Bentz präsentieren und prüfen eine bilinguale Suche auf Basis von Konzeptnetzen, wobei die Konzeptstruktur das verbindende Elemente der beiden Textsammlungen darstellt. Das Entwickeln und Evaluieren eines mehrsprachigen Question-Answering-Systems im Rahmen des Cross Language Evaluation Forum (CLEF), das die alltagssprachliche Formulierung von konkreten Fragestellungen ermöglicht, wird im Beitrag von Robert Strötgen, Thomas Mandl und Rene Schneider thematisiert. Den Schluss bildet der Aufsatz von Niels Jensen, der ein mehrsprachiges Web-Retrieval-System ebenfalls im Zusammenhang mit dem CLEF anhand des multilingualen EuroGOVKorpus evaluiert.
    Abschließend lässt sich sagen, dass der Tagungsband einen gelungenen Überblick über die Information Retrieval Projekte der Hildesheimer Informationswissenschaft und ihrer Kooperationspartner gibt. Die einzelnen Beiträge sind sehr anregend und auf einem hohen Niveau angesiedelt. Ein kleines Hindernis für den Leser stellt die inhaltliche und strukturelle Orientierung innerhalb des Bandes dar. Der Bezug der einzelnen Artikel zum Thema des Kapitels wird zwar im Vorwort kurz erläutert. Erschwert wird die Orientierung im Buch jedoch durch fehlende Kapitelüberschriften am Anfang der einzelnen Sektionen. Außerdem ist zu erwähnen, dass einer der Artikel einen anderen Titel als im Inhaltsverzeichnis angekündigt trägt. Sieht der Leser von diesen formalen Mängeln ab, wird er reichlich mit praxisbezogenen und theoretisch fundierten Projektdarstellungen und Forschungsergebnissen belohnt. Dies insbesondere, da nicht nur aktuelle Themen der Informationswissenschaft aufgegriffen, sondern ebenso weiterentwickelt und durch die speziellen interdisziplinären und internationalen Bedingungen in Hildesheim geformt werden. Dabei zeigt sich anhand der verschiedenen Projekte, wie gut die Hildesheimer Informationswissenschaft in die Community überregionaler Informationseinrichtungen und anderer deutscher informationswissenschaftlicher Forschungsgruppen eingebunden ist. Damit hat der Workshop bei einer weiteren Öffnung der Expertengruppe das Potential zu einer eigenständigen Institution im Bereich des Information Retrieval zu werden. In diesem Sinne lässt sich auf weitere fruchtbare Workshops und deren Veröffentlichungen hoffen. Ein nächster Workshop der Universität Hildesheim zum Thema Information Retrieval, organisiert mit der Fachgruppe Information Retrieval der Gesellschaft für Informatik, kündigt sich bereits für den 9. bis 13- Oktober 2006 an."
  9. Henzinger, M.R.: Link analysis in Web information retrieval (2000) 0.02
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    Abstract
    The analysis of the hyperlink structure of the web has led to significant improvements in web information retrieval. This survey describes two successful link analysis algorithms and the state-of-the art of the field.
    Content
    The goal of information retrieval is to find all documents relevant for a user query in a collection of documents. Decades of research in information retrieval were successful in developing and refining techniques that are solely word-based (see e.g., [2]). With the advent of the web new sources of information became available, one of them being the hyperlinks between documents and records of user behavior. To be precise, hypertexts (i.e., collections of documents connected by hyperlinks) have existed and have been studied for a long time. What was new was the large number of hyperlinks created by independent individuals. Hyperlinks provide a valuable source of information for web information retrieval as we will show in this article. This area of information retrieval is commonly called link analysis. Why would one expect hyperlinks to be useful? Ahyperlink is a reference of a web page B that is contained in a web page A. When the hyperlink is clicked on in a web browser, the browser displays page B. This functionality alone is not helpful for web information retrieval. However, the way hyperlinks are typically used by authors of web pages can give them valuable information content. Typically, authors create links because they think they will be useful for the readers of the pages. Thus, links are usually either navigational aids that, for example, bring the reader back to the homepage of the site, or links that point to pages whose content augments the content of the current page. The second kind of links tend to point to high-quality pages that might be on the same topic as the page containing the link.
  10. Thelwall, M.; Vaughan, L.: New versions of PageRank employing alternative Web document models (2004) 0.02
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    Abstract
    Introduces several new versions of PageRank (the link based Web page ranking algorithm), based on an information science perspective on the concept of the Web document. Although the Web page is the typical indivisible unit of information in search engine results and most Web information retrieval algorithms, other research has suggested that aggregating pages based on directories and domains gives promising alternatives, particularly when Web links are the object of study. The new algorithms introduced based on these alternatives were used to rank four sets of Web pages. The ranking results were compared with human subjects' rankings. The results of the tests were somewhat inconclusive: the new approach worked well for the set that includes pages from different Web sites; however, it does not work well in ranking pages that are from the same site. It seems that the new algorithms may be effective for some tasks but not for others, especially when only low numbers of links are involved or the pages to be ranked are from the same site or directory.
  11. Lalmas, M.: XML retrieval (2009) 0.02
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    Abstract
    Documents usually have a content and a structure. The content refers to the text of the document, whereas the structure refers to how a document is logically organized. An increasingly common way to encode the structure is through the use of a mark-up language. Nowadays, the most widely used mark-up language for representing structure is the eXtensible Mark-up Language (XML). XML can be used to provide a focused access to documents, i.e. returning XML elements, such as sections and paragraphs, instead of whole documents in response to a query. Such focused strategies are of particular benefit for information repositories containing long documents, or documents covering a wide variety of topics, where users are directed to the most relevant content within a document. The increased adoption of XML to represent a document structure requires the development of tools to effectively access documents marked-up in XML. This book provides a detailed description of query languages, indexing strategies, ranking algorithms, presentation scenarios developed to access XML documents. Major advances in XML retrieval were seen from 2002 as a result of INEX, the Initiative for Evaluation of XML Retrieval. INEX, also described in this book, provided test sets for evaluating XML retrieval effectiveness. Many of the developments and results described in this book were investigated within INEX.
    Content
    Table of Contents: Introduction / Basic XML Concepts / Historical Perspectives / Query Languages / Indexing Strategies / Ranking Strategies / Presentation Strategies / Evaluating XML Retrieval Effectiveness / Conclusions
    LCSH
    Information retrieval
    Series
    Synthesis lectures on information concepts, retrieval & services; 7
    Subject
    Information retrieval
  12. Stock, M.; Stock, W.G.: Internet-Suchwerkzeuge im Vergleich (IV) : Relevance Ranking nach "Popularität" von Webseiten: Google (2001) 0.02
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    Abstract
    In unserem Retrievaltest von Suchwerkzeugen im World Wide Web (Password 11/2000) schnitt die Suchmaschine Google am besten ab. Im Vergleich zu anderen Search Engines setzt Google kaum auf Informationslinguistik, sondern auf Algorithmen, die sich aus den Besonderheiten der Web-Dokumente ableiten lassen. Kernstück der informationsstatistischen Technik ist das "PageRank"- Verfahren (benannt nach dem Entwickler Larry Page), das aus der Hypertextstruktur des Web die "Popularität" von Seiten anhand ihrer ein- und ausgehenden Links berechnet. Google besticht durch das Angebot intuitiv verstehbarer Suchbildschirme sowie durch einige sehr nützliche "Kleinigkeiten" wie die Angabe des Rangs einer Seite, Highlighting, Suchen in der Seite, Suchen innerhalb eines Suchergebnisses usw., alles verstaut in einer eigenen Befehlsleiste innerhalb des Browsers. Ähnlich wie RealNames bietet Google mit dem Produkt "AdWords" den Aufkauf von Suchtermen an. Nach einer Reihe von nunmehr vier Password-Artikeln über InternetSuchwerkzeugen im Vergleich wollen wir abschließend zu einer Bewertung kommen. Wie ist der Stand der Technik bei Directories und Search Engines aus informationswissenschaftlicher Sicht einzuschätzen? Werden die "typischen" Internetnutzer, die ja in der Regel keine Information Professionals sind, adäquat bedient? Und können auch Informationsfachleute von den Suchwerkzeugen profitieren?
  13. Bidoki, A.M.Z.; Yazdani, N.: an intelligent ranking algorithm for web pages : DistanceRank (2008) 0.02
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    Abstract
    A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank, HITS and OPIC have been proposed. In this paper, we propose a novel recursive method based on reinforcement learning which considers distance between pages as punishment, called "DistanceRank" to compute ranks of web pages. The distance is defined as the number of "average clicks" between two pages. The objective is to minimize punishment or distance so that a page with less distance to have a higher rank. Experimental results indicate that DistanceRank outperforms other ranking algorithms in page ranking and crawling scheduling. Furthermore, the complexity of DistanceRank is low. We have used University of California at Berkeley's web for our experiments.
    Source
    Information processing and management. 44(2008) no.2, S.877-892
  14. Ning, X.; Jin, H.; Jia, W.; Yuan, P.: Practical and effective IR-style keyword search over semantic web (2009) 0.02
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    Abstract
    This paper presents a novel IR-style keyword search model for semantic web data retrieval, distinguished from current retrieval methods. In this model, an answer to a keyword query is a connected subgraph that contains all the query keywords. In addition, the answer is minimal because any proper subgraph can not be an answer to the query. We provide an approximation algorithm to retrieve these answers efficiently. A special ranking strategy is also proposed so that answers can be appropriately ordered. The experimental results over real datasets show that our model outperforms existing possible solutions with respect to effectiveness and efficiency.
    Source
    Information processing and management. 45(2009) no.2, S.263-271
  15. Thelwall, M.: Can Google's PageRank be used to find the most important academic Web pages? (2003) 0.02
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    Abstract
    Google's PageRank is an influential algorithm that uses a model of Web use that is dominated by its link structure in order to rank pages by their estimated value to the Web community. This paper reports on the outcome of applying the algorithm to the Web sites of three national university systems in order to test whether it is capable of identifying the most important Web pages. The results are also compared with simple inlink counts. It was discovered that the highest inlinked pages do not always have the highest PageRank, indicating that the two metrics are genuinely different, even for the top pages. More significantly, however, internal links dominated external links for the high ranks in either method and superficial reasons accounted for high scores in both cases. It is concluded that PageRank is not useful for identifying the top pages in a site and that it must be combined with a powerful text matching techniques in order to get the quality of information retrieval results provided by Google.
  16. Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003) 0.01
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    Abstract
    The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
    Footnote
    Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.7, S.683-694
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.01
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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
  18. 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) 0.01
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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
  19. Berry, M.W.; Browne, M.: Understanding search engines : mathematical modeling and text retrieval (2005) 0.01
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    Abstract
    The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.
    Content
    Inhalt: Introduction Document File Preparation - Manual Indexing - Information Extraction - Vector Space Modeling - Matrix Decompositions - Query Representations - Ranking and Relevance Feedback - Searching by Link Structure - User Interface - Book Format Document File Preparation Document Purification and Analysis - Text Formatting - Validation - Manual Indexing - Automatic Indexing - Item Normalization - Inverted File Structures - Document File - Dictionary List - Inversion List - Other File Structures Vector Space Models Construction - Term-by-Document Matrices - Simple Query Matching - Design Issues - Term Weighting - Sparse Matrix Storage - Low-Rank Approximations Matrix Decompositions QR Factorization - Singular Value Decomposition - Low-Rank Approximations - Query Matching - Software - Semidiscrete Decomposition - Updating Techniques Query Management Query Binding - Types of Queries - Boolean Queries - Natural Language Queries - Thesaurus Queries - Fuzzy Queries - Term Searches - Probabilistic Queries Ranking and Relevance Feedback Performance Evaluation - Precision - Recall - Average Precision - Genetic Algorithms - Relevance Feedback Searching by Link Structure HITS Method - HITS Implementation - HITS Summary - PageRank Method - PageRank Adjustments - PageRank Implementation - PageRank Summary User Interface Considerations General Guidelines - Search Engine Interfaces - Form Fill-in - Display Considerations - Progress Indication - No Penalties for Error - Results - Test and Retest - Final Considerations Further Reading
    LCSH
    Web search engines
    RSWK
    Suchmaschine / Information Retrieval
    Suchmaschine / Information Retrieval / Mathematisches Modell (HEBIS)
    Subject
    Web search engines
    Suchmaschine / Information Retrieval
    Suchmaschine / Information Retrieval / Mathematisches Modell (HEBIS)
  20. Stock, W.G.: On relevance distributions (2006) 0.01
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    Abstract
    There are at least three possible ways that documents are distributed by relevance: informetric (power law), inverse logistic, and dichotomous. The nature of the type of distribution has implications for the construction of relevance ranking algorithms for search engines, for automated (blind) relevance feedback, for user behavior when using Web search engines, for combining of outputs of search engines for metasearch, for topic detection and tracking, and for the methodology of evaluation of information retrieval systems.
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.8, S.1126-1129

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