Search (9 results, page 1 of 1)

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Abstract

With the proliferation of huge amounts of (heterogeneous) data on the Web, the importance of information retrieval (IR) has grown considerably over the last few years. Big players in the computer industry, such as Google, Microsoft and Yahoo!, are the primary contributors of technology for fast access to Web-based information; and searching capabilities are now integrated into most information systems, ranging from business management software and customer relationship systems to social networks and mobile phone applications. Ceri and his co-authors aim at taking their readers from the foundations of modern information retrieval to the most advanced challenges of Web IR. To this end, their book is divided into three parts. The first part addresses the principles of IR and provides a systematic and compact description of basic information retrieval techniques (including binary, vector space and probabilistic models as well as natural language search processing) before focusing on its application to the Web. Part two addresses the foundational aspects of Web IR by discussing the general architecture of search engines (with a focus on the crawling and indexing processes), describing link analysis methods (specifically Page Rank and HITS), addressing recommendation and diversification, and finally presenting advertising in search (the main source of revenues for search engines). The third and final part describes advanced aspects of Web search, each chapter providing a self-contained, up-to-date survey on current Web research directions. Topics in this part include meta-search and multi-domain search, semantic search, search in the context of multimedia data, and crowd search. The book is ideally suited to courses on information retrieval, as it covers all Web-independent foundational aspects. Its presentation is self-contained and does not require prior background knowledge. It can also be used in the context of classic courses on data management, allowing the instructor to cover both structured and unstructured data in various formats. Its classroom use is facilitated by a set of slides, which can be downloaded from www.search-computing.org.

Date

16.10.2013 19:22:44

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Abstract

Das Semantic Web bezeichnet ein erweitertes World Wide Web (WWW), das die Bedeutung von präsentierten Inhalten in neuen standardisierten Sprachen wie RDF Schema und OWL modelliert. Diese Arbeit befasst sich mit dem Aspekt des Information Retrieval, d.h. es wird untersucht, in wie weit Methoden der Informationssuche sich auf modelliertes Wissen übertragen lassen. Die kennzeichnenden Merkmale von IR-Systemen wie vage Anfragen sowie die Unterstützung unsicheren Wissens werden im Kontext des Semantic Web behandelt. Im Fokus steht die Suche nach Fakten innerhalb einer Wissensdomäne, die entweder explizit modelliert sind oder implizit durch die Anwendung von Inferenz abgeleitet werden können. Aufbauend auf der an der Universität Duisburg-Essen entwickelten Retrievalmaschine PIRE wird die Anwendung unsicherer Inferenz mit probabilistischer Prädikatenlogik (pDatalog) implementiert.

Footnote

Zugl.: Dortmund, Univ., Dipl.-Arb., 2006 u.d.T.: Hüsken, Peter: Information-Retrieval im Semantic-Web.

RSWK

Information Retrieval / Semantic Web

Subject

Information Retrieval / Semantic Web

Theme

Semantic Web

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Content

Inhalt Collaborating to search effectively in different searcher modes through cues and specialty search / Naresh Kumar Agarwal and Danny C.C. Poo -- Collaborative querying using a hybrid content and results-based approach / Chandrani Sinha Ray ... [et al.] -- Collaborative classification for group-oriented organization of search results / Keiichi Nakata and Amrish Singh -- A case study of use-centered descriptions : archival descriptions of what can be done with a collection / Richard Butterworth -- Metadata for social recommendations : storing, sharing, and reusing evaluations of learning resources / Riina Vuorikari, Nikos Manouselis, and Erik Duval -- Social network models for enhancing reference-based search engine rankings / Nikolaos Korfiatis ... [et al.] -- From PageRank to social rank : authority-based retrieval in social information spaces / Sebastian Marius Kirsch ... [et al.] -- Adaptive peer-to-peer social networks for distributed content-based Web search / Le-Shin Wu ... [et al.] -- The ethics of social information retrieval / Brendan Luyt and Chu Keong Lee -- The social context of knowledge / Daniel Memmi -- Social information seeking in digital libraries / George Buchanan and Annika Hinze -- Relevant intra-actions in networked environments / Theresa Dirndorfer Anderson -- Publication and citation analysis as a tool for information retrieval / Ronald Rousseau -- Personalized information retrieval in a semantic-based learning environment / Antonella Carbonaro and Rodolfo Ferrini -- Multi-agent tourism system (MATS) / Soe Yu Maw and Myo-Myo Naing -- Hybrid recommendation systems : a case study on the movies domain / Konstantinos Markellos ... [et al.].

LCSH

Web search engines
World Wide Web / Subject access

RSWK

World Wide Web 2.0
Information Retrieval / World Wide Web / Suchmaschine

Subject

Web search engines
World Wide Web / Subject access
World Wide Web 2.0
Information Retrieval / World Wide Web / Suchmaschine

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Abstract

Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers. - This book provides what Salton and Van Rijsbergen both failed to achieve. Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. Its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.

Content

Inhalt: Boolean retrieval - The term vocabulary & postings lists - Dictionaries and tolerant retrieval - Index construction - Index compression - Scoring, term weighting & the vector space model - Computing scores in a complete search system - Evaluation in information retrieval - Relevance feedback & query expansion - XML retrieval - Probabilistic information retrieval - Language models for information retrieval - Text classification & Naive Bayes - Vector space classification - Support vector machines & machine learning on documents - Flat clustering - Hierarchical clustering - Matrix decompositions & latent semantic indexing - Web search basics - Web crawling and indexes - Link analysis Vgl. die digitale Fassung unter: http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf.

LCSH

Semantic Web

RSWK

Semantic Web (BVB)
World Wide Web / Suchmaschine (HBZ)

Subject

Semantic Web (BVB)
World Wide Web / Suchmaschine (HBZ)
Semantic Web

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Content

Introduction -- Definitions -- Descriptive metadata -- Administrative metadata -- Use metadata -- Enabling technologies for metadata -- The Semantic Web -- The future of metadata.

RSWK

Metadaten / Semantic Web / Metadatenmodell

Subject

Metadaten / Semantic Web / Metadatenmodell

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Date

22. 3.2008 12:26:32

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LCSH

Web search engines / Research

Subject

Web search engines / Research

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Abstract

How do you find your way in an age of information overload? How can you filter streams of complex information to pull out only what you want? Why does it matter how information is structured when Google seems to magically bring up the right answer to your questions? What does it mean to be "findable" in this day and age? This eye-opening new book examines the convergence of information and connectivity. Written by Peter Morville, author of the groundbreakin Information Architecture for the World Wide Web, the book defines our current age as a state of unlimited findability. In other words, anyone can find anything at any time. Complete navigability. Morville discusses the Internet, GIS, and other network technologies that are coming together to make unlimited findability possible. He explores how the melding of these innovations impacts society, since Web access is now a standard requirement for successful people and businesses. But before he does that, Morville looks back at the history of wayfinding and human evolution, suggesting that our fear of being lost has driven us to create maps, charts, and now, the mobile Internet.

Footnote

Rez. in: nfd - Information Wissenschaft und Praxis 57(2006) H.3, S.177-178 (D. Lewandowski): "Wohl unbestritten ist, dass die Suche in Informationsbeständen eine immer größere Bedeutung erhält. Wir suchen nicht nur noch explizit, indem wir ein Informationssystem anwählen und dort eine Suche absetzen, sondern verwenden Suchfunktionen innerhalb von Programmen, auf Websites, innerhalb des Betriebssystems unseres Computers oder sogar ziemlich unbewusst, indem wir Informationen maßgeschneidert aufgrund einer einmal hinterlegten Suche oder eines automatisch erstellten Suchprofils erhalten. Man kann also in der Tat davon sprechen, dass wir von der Suche umgeben werden. Das ist mit dem Konzept der "Ambient Findability" gemeint. Angelehnt ist diese Bezeichnung an den Begriff der "Ambient Music" (in den 70er Jahren durch Brian Eno geprägt), die den Hörer umgibt und von ihm oft gar nicht aktiv wahrgenommen wird. Um eine Vorstellung von dieser Musik zu bekommen, eignet sich vielleicht am besten der Titel einer Platte eben von Brian Eno: "Music for Airports". Peter Morville, bekannt als Co-Autor des empfehlenswerten Buchs "Information Architecture for the World Wide Web"', hat sich nun mit der Veränderung der Suche auseinandergesetzt. Sein Buch bedient sich in ganz unterschiedlichen Disziplinen, um die Prozesse des Suchens, Stöberns und Findens aufzuzeigen. So finden sich Betrachtungen über die Orientierung des Menschen in unbekannten Umgebungen, über die Interaktion mit Informationssystemen, über das soziale Verhalten der Web-Nutzer (Stichworte: Content-Tagging, Folksonomies, Social Networking) und über technische Veränderungen durch die Verfügbarkeit von Informationssystemen in allen Lebenskontexten, vor allem auch über mobile Endgeräte. Das Buch ist in sieben Kapitel gegliedert. Das erste, "Lost and Found" betitelt, bietet auf wenigen Seiten die Definitionen der zentralen Begriffe ambient und findability, erläutert kurz das Konzept der Information Literacy und zeigt, dass die bessere Auffindbarkeit von Informationen nicht nur ein schöner Zusatznutzen ist, sondern sich für Unternehmen deutlich auszahlt.
Im Kapitel über das "Sociosemantic Web" werden die groben Grundzüge der Klassifikationslehre erläutert, um dann ausführlich auf neuere Ansätze der Web-Erschließung wie Social Tagging und Folksonomies einzugehen. Auch dieses Kapitel gibt eher einen Überblick als den schon Kundigen vertiefende Informationen zu liefern. Das letzte Kapitel widmet sich schließlich der Art, wie Entscheidungen getroffen werden, der Network Culture, dem Information Overload, um schließlich zu den "Inspired Decisions" zu gelangen - Entscheidungen, die sowohl auf "sachlichen Informationen" (also den klassischen Zutaten der "informed decisions") als auch aus aus Netzwerken stammenden Informationen wie etwa Empfehlungen durch Freunde oder Community-Mitglieder irgendeiner Art gewonnen werden. Fasst man zusammen, so ist an Morvilles Text besonders bemerkenswert, dass nach einigen Jahren, in denen die Suche im Web als ein Problem der Suche in unstrukturierten Daten angesehen wurde, nun wieder verstärkt Erschließungsansätze, die auf klassische Erschließungsinstrumente zurückgreifen, propagiert werden. Zwar sollen sie nicht in ihrer ursprünglichen Form angewandt werden, da den Nutzern nicht zuzumuten ist, sich mit den entsprechenden Regeln auseinanderzusetzen, aber auch hinter der auf den ersten Blick zumindest chaotisch wirkenden Folksonomy ist das Prinzip der Klassifikation zu erkennen. Um die modernen Ansätze erfolgreich zu machen, bedarf es aber dringend Information Professionals, die das "beste aus beiden Welten" verbinden, um moderne, für den Nutzer optimale Informationssysteme zu schaffen. Für die Gesamtbewertung des Buchs gelten die bereits zu einzelnen Kapitels angeführten Kritikpunkte: In erster Linie bleibt das Buch zu sehr an der Oberfläche und wirkt irgendwie "zusammengeschrieben" anstatt als Ergebnis der tiefgreifenden Beschäftigung mit dem Thema. Als eine Einführung in aufkommende Technologien rund um die Suche ist es aber durchaus geeignet - gut lesbar ist der Text auf jeden Fall.

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Abstract

The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.

Content

Enthält die Beiträge: 1. The Text REtrieval Conference - Ellen M. Voorhees and Donna K. Harman 2. The TREC Test Collections - Donna K. Harman 3. Retrieval System Evaluation - Chris Buckley and Ellen M. Voorhees 4. The TREC Ad Hoc Experiments - Donna K. Harman 5. Routing and Filtering - Stephen Robertson and Jamie Callan 6. The TREC Interactive Tracks: Putting the User into Search - Susan T. Dumais and Nicholas J. Belkin 7. Beyond English - Donna K. Harman 8. Retrieving Noisy Text - Ellen M. Voorhees and John S. Garofolo 9.The Very Large Collection and Web Tracks - David Hawking and Nick Craswell 10. Question Answering in TREC - Ellen M. Voorhees 11. The University of Massachusetts and a Dozen TRECs - James Allan, W. Bruce Croft and Jamie Callan 12. How Okapi Came to TREC - Stephen Robertson 13. The SMART Project at TREC - Chris Buckley 14. Ten Years of Ad Hoc Retrieval at TREC Using PIRCS - Kui-Lam Kwok 15. MultiText Experiments for TREC - Gordon V. Cormack, Charles L. A. Clarke, Christopher R. Palmer and Thomas R. Lynam 16. A Language-Modeling Approach to TREC - Djoerd Hiemstra and Wessel Kraaij 17. BM Research Activities at TREC - Eric W. Brown, David Carmel, Martin Franz, Abraham Ittycheriah, Tapas Kanungo, Yoelle Maarek, J. Scott McCarley, Robert L. Mack, John M. Prager, John R. Smith, Aya Soffer, Jason Y. Zien and Alan D. Marwick Epilogue: Metareflections on TREC - Karen Sparck Jones

Footnote

Rez. in: JASIST 58(2007) no.6, S.910-911 (J.L. Vicedo u. J. Gomez): "The Text REtrieval Conference (TREC) is a yearly workshop hosted by the U.S. government's National Institute of Standards and Technology (NIST) that fosters and supports research in information retrieval as well as speeding the transfer of technology between research labs and industry. Since 1992, TREC has provided the infrastructure necessary for large-scale evaluations of different text retrieval methodologies. TREC impact has been very important and its success has been mainly supported by its continuous adaptation to the emerging information retrieval needs. Not in vain, TREC has built evaluation benchmarks for more than 20 different retrieval problems such as Web retrieval, speech retrieval, or question-answering. The large and intense trajectory of annual TREC conferences has resulted in an immense bulk of documents reflecting the different eval uation and research efforts developed. This situation makes it difficult sometimes to observe clearly how research in information retrieval (IR) has evolved over the course of TREC. TREC: Experiment and Evaluation in Information Retrieval succeeds in organizing and condensing all this research into a manageable volume that describes TREC history and summarizes the main lessons learned. The book is organized into three parts. The first part is devoted to the description of TREC's origin and history, the test collections, and the evaluation methodology developed. The second part describes a selection of the major evaluation exercises (tracks), and the third part contains contributions from research groups that had a large and remarkable participation in TREC. Finally, Karen Spark Jones, one of the main promoters of research in IR, closes the book with an epilogue that analyzes the impact of TREC on this research field.