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Ceri, S.; Bozzon, A.; Brambilla, M.; Della Valle, E.; Fraternali, P.; Quarteroni, S.: Web Information Retrieval (2013)
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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
- Language
- e
-
Dominich, S.: Mathematical foundations of information retrieval (2001)
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- Date
- 22. 3.2008 12:26:32
- Language
- e
-
Manning, C.D.; Raghavan, P.; Schütze, H.: Introduction to information retrieval (2008)
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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.
- Language
- e
-
TREC: experiment and evaluation in information retrieval (2005)
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- Footnote
- ... TREC: Experiment and Evaluation in Information Retrieval is a reliable and comprehensive review of the TREC program and has been adopted by NIST as the official history of TREC (see http://trec.nist.gov). We were favorably surprised by the book. Well structured and written, chapters are self-contained and the existence of references to specialized and more detailed publications is continuous, which makes it easier to expand into the different aspects analyzed in the text. This book succeeds in compiling TREC evolution from its inception in 1992 to 2003 in an adequate and manageable volume. Thanks to the impressive effort performed by the authors and their experience in the field, it can satiate the interests of a great variety of readers. While expert researchers in the IR field and IR-related industrial companies can use it as a reference manual, it seems especially useful for students and non-expert readers willing to approach this research area. Like NIST, we would recommend this reading to anyone who may be interested in textual information retrieval."
- Language
- e
-
Tunkelang, D.: Faceted search (2009)
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- Abstract
- We live in an information age that requires us, more than ever, to represent, access, and use information. Over the last several decades, we have developed a modern science and technology for information retrieval, relentlessly pursuing the vision of a "memex" that Vannevar Bush proposed in his seminal article, "As We May Think." Faceted search plays a key role in this program. Faceted search addresses weaknesses of conventional search approaches and has emerged as a foundation for interactive information retrieval. User studies demonstrate that faceted search provides more effective information-seeking support to users than best-first search. Indeed, faceted search has become increasingly prevalent in online information access systems, particularly for e-commerce and site search. In this lecture, we explore the history, theory, and practice of faceted search. Although we cannot hope to be exhaustive, our aim is to provide sufficient depth and breadth to offer a useful resource to both researchers and practitioners. Because faceted search is an area of interest to computer scientists, information scientists, interface designers, and usability researchers, we do not assume that the reader is a specialist in any of these fields. Rather, we offer a self-contained treatment of the topic, with an extensive bibliography for those who would like to pursue particular aspects in more depth.
- Classification
- AZE (E)
- GHBS
- AZE (E)
- Language
- e
-
Kantardzic, M.: Data mining : concepts, models, methods, and algorithms (2003)
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- Classification
- TWX (E)
- GHBS
- TWX (E)
- Language
- e
-
Pomerantz, J.: Metadata (2015)
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- Classification
- AZC (E)
- GHBS
- AZC (E)
- Language
- e
-
Croft, W.B.; Metzler, D.; Strohman, T.: Search engines : information retrieval in practice (2010)
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Widhalm, R.; Mück, T.: Topic maps : Semantische Suche im Internet (2002)
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- Classification
- BFP (E)
- GHBS
- BFP (E)
-
Kuropka, D.: Modelle zur Repräsentation natürlichsprachlicher Dokumente : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2004)
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- Abstract
- Kostengünstige Massenspeicher und die zunehmende Vernetzung von Rechnern haben die Anzahl der Dokumente, auf die ein einzelnes Individuum zugreifen kann (bspw. Webseiten) oder die auf das Individuum einströmen (bspw. E-Mails), in den letzten Jahren rapide ansteigen lassen. In immer mehr Bereichen der Wirtschaft, Wissenschaft und Verwaltung nimmt der Bedarf an hochwertigen Information-Filtering und -Retrieval Werkzeugen zur Beherrschung der Informationsflut zu. Zur computergestützten Lösung dieser Problemstellung sind Modelle zur Repräsentation natürlichsprachlicher Dokumente erforderlich, um formale Kriterien für die automatisierte Auswahl relevanter Dokumente definieren zu können. Dominik Kuropka gibt in seiner Arbeit eine umfassende Übersicht über den Themenbereich der Suche und Filterung von natürlichsprachlichen Dokumenten. Es wird eine Vielzahl von Modellen aus Forschung und Praxis vorgestellt und evaluiert. Auf den Ergebnissen aufbauend wird das Potenzial von Ontologien in diesem Zusammenhang eruiert und es wird ein neues, ontologie-basiertes Modell für das Information-Filtering und -Retrieval erarbeitet, welches anhand von Text- und Code-Beispielen ausführlich erläutert wird. Das Buch richtet sich an Dozenten und Studenten der Informatik, Wirtschaftsinformatik und (Computer-)Linguistik sowie an Systemdesigner und Entwickler von dokumentenorientierten Anwendungssystemen und Werkzeugen.
-
Kuropka, D.: Modelle zur Repräsentation natürlichsprachlicher Dokumente : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2004)
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- Abstract
- Kostengünstige Massenspeicher und die zunehmende Vernetzung von Rechnern haben die Anzahl der Dokumente, auf die ein einzelnes Individuum zugreifen kann (bspw. Webseiten) oder die auf das Individuum einströmen (bspw. E-Mails), in den letzten Jahren rapide ansteigen lassen. In immer mehr Bereichen der Wirtschaft, Wissenschaft und Verwaltung nimmt der Bedarf an hochwertigen Information-Filtering und -Retrieval Werkzeugen zur Beherrschung der Informationsflut zu. Zur computergestützten Lösung dieser Problemstellung sind Modelle zur Repräsentation natürlichsprachlicher Dokumente erforderlich, um formale Kriterien für die automatisierte Auswahl relevanter Dokumente definieren zu können. Dominik Kuropka gibt in seiner Arbeit eine umfassende Übersicht über den Themenbereich der Suche und Filterung von natürlichsprachlichen Dokumenten. Es wird eine Vielzahl von Modellen aus Forschung und Praxis vorgestellt und evaluiert. Auf den Ergebnissen aufbauend wird das Potenzial von Ontologien in diesem Zusammenhang eruiert und es wird ein neues, ontologie-basiertes Modell für das Information-Filtering und -Retrieval erarbeitet, welches anhand von Text- und Code-Beispielen ausführlich erläutert wird. Das Buch richtet sich an Dozenten und Studenten der Informatik, Wirtschaftsinformatik und (Computer-)Linguistik sowie an Systemdesigner und Entwickler von dokumentenorientierten Anwendungssystemen und Werkzeugen.
-
Colomb, R.M.: Information spaces : the architecture of cyberspace (2002)
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White, R.W.: Interactions with search systems (2016)
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Looking for information : a survey on research on information seeking, needs, and behavior (2016)
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Crestani, F.; Mizzaro, S.; Scagnetto, I,: Mobile information retrieval (2017)
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Social information retrieval systems : emerging technologies and applications for searching the Web effectively (2008)
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Theory development in the information sciences (2016)
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Morville, P.: Ambient findability : what we find changes who we become (2005)
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