Search (51 results, page 2 of 3)

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Abstract

This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.

LCSH

Information storage and retrieval

Series

Lecture Notes in Computer Scienc;10370 )(Information Systems and Applications, incl. Internet/Web, and HCI

Subject

Information storage and retrieval

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Abstract

Content Management Systems (CMSs) are used in almost every industry by millions of end-user organizations. In contrast to the 90s, they are no longer used as isolated applications in one organization but they support critical core operations in business ecosystems. Content management today is more interactive and more integrative: interactive because end-users are increasingly content creators themselves and integrative because content elements can be embedded into various other applications. The authors of this book investigate how Semantic Technologies can increase interactivity and integration capabilities of CMSs and discuss their business value to millions of end-user organizations. This book has therefore the objective, to reflect existing applications as well as to discuss and present new applications for CMSs that use Semantic Technologies. An evaluation of 27 CMSs concludes this book and provides a basis for IT executives that plan to adopt or replace a CMS in the near future.

Content

On the Changing Market for Content Management Systems: Status and Outlook - Wolfgang Maass Empowering the Distributed Editorial Workforce - Steve McNally The Rise of Semantic-aware Applications - Stéphane Croisier Simplified Semantic Enhancement of JCR-based Content Applications -Bertrand Delacretaz and Michael Marth Dynamic Semantic Publishing - Jem Rayfield Semantics in the Domain of eGovernment - Luis Alvarez Sabucedo and Luis Anido Rifón The Interactive Knowledge Stack (IKS): A Vision for the Future of CMS - Wernher Behrendt Essential Requirements for Semantic CMS - Valentina Presutti Evaluation of Content Management Systems - Tobias Kowatsch and Wolfgang Maass CMS with No Particular Industry Focus (versch. Beiträge)

LCSH

Information storage and retrieval systems
Information Systems
Management information systems

Subject

Information storage and retrieval systems
Information Systems
Management information systems

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Content

Information representation and retrieval : an overview -- Information representation I : basic approaches -- Information representation II : related topics -- Language in information representation and retrieval -- Retrieval techniques and query representation -- Retrieval approaches -- Information retrieval models -- Information retrieval systems -- Retrieval of information unique in content or format -- The user dimension in information representation and retrieval -- Evaluation of information representation and retrieval -- Artificial intelligence in information representation and retrieval.

Footnote

Rez. in: JASIST 56(2005) no.2, S.215-216 (A. Heath): "What is small, thoroughly organized, and easy to understand? Well, it's Heting Chu's latest book an information retrieval. A very welcome release, this small literary addition to the field (only 248 pages) contains a concise and weIl-organized discussion of every major topic in information retrieval. The often-complex field of information retrieval is presented from its origin in the early 1950s to the present day. The organization of this text is top-notch, thus making this an easy read for even the novice. Unlike other titles in this area, Chu's user-friendly style of writing is done an purpose to properly introduce newcomers to the field in a less intimidating way. As stated by the author in the Preface, the purpose of the book is to "present a systematic, thorough yet nontechnical view of the field by using plain language to explain complex subjects." Chu has definitely struck up the right combination of ingredients. In a field so broad and complex, a well-organized presentation of topics that don't trip an themselves is essential. The use of plain language where possible is also a good choice for this topic because it allows one to absorb topics that are, by nature, not as easy to grasp. For instance, Chapters 6 and 7, which cover retrieval approaches and techniques, an often painstaking topic for many students and teachers is deftly handled with the use of tables that can be used to compare and contrast the various models discussed. I particularly loved Chu's use of Koll's 2000 article from the Bulletin of the American Society for Information Science to explain subject searching at the beginning of Chapter 6, which discusses the differences between browsing and searching. The Koll article uses the task of finding a needle in a haystack as an analogy.
Chu's intent with this book is clear throughout the entire text. With this presentation, she writes with the novice in mind or as she puls it in the Preface, "to anyone who is interested in learning about the field, particularly those who are new to it." After reading the text, I found that this book is also an appropriate reference book for those who are somewhat advanced in the field. I found the chapters an information retrieval models and techniques, metadata, and AI very informative in that they contain information that is often rather densely presented in other texts. Although, I must say, the metadata section in Chapter 3 is pretty basic and contains more questions about the area than information. . . . It is an excellent book to have in the classroom, an your bookshelf, etc. It reads very well and is written with the reader in mind. If you are in need of a more advanced or technical text an the subject, this is not the book for you. But, if you are looking for a comprehensive, manual that can be used as a "flip-through," then you are in luck."
Weitere Rez. in: Rez. in: nfd 55(2004) H.4, S.252 (D. Lewandowski):"Die Zahl der Bücher zum Thema Information Retrieval ist nicht gering, auch in deutscher Sprache liegen einige Titel vor. Trotzdem soll ein neues (englischsprachiges) Buch zu diesem Thema hier besprochen werden. Dieses zeichnet sich durch eine Kürze (nur etwa 230 Seiten Text) und seine gute Verständlichkeit aus und richtet sich damit bevorzugt an Studenten in den ersten Semestern. Heting Chu unterrichtet seit 1994 an Palmer School of Library and Information Science der Long Island University New York. Dass die Autorin viel Erfahrung in der Vermittlung des Stoffs in ihren Information-Retrieval-Veranstaltungen sammeln konnte, merkt man dem Buch deutlich an. Es ist einer klaren und verständlichen Sprache geschrieben und führt in die Grundlagen der Wissensrepräsentation und des Information Retrieval ein. Das Lehrbuch behandelt diese Themen als Gesamtkomplex und geht damit über den Themenbereich ähnlicher Bücher hinaus, die sich in der Regel auf das Retrieval beschränken. Das Buch ist in zwölf Kapitel gegliedert, wobei das erste Kapitel eine Übersicht über die zu behandelnden Themen gibt und den Leser auf einfache Weise in die Grundbegriffe und die Geschichte des IRR einführt. Neben einer kurzen chronologischen Darstellung der Entwicklung der IRR-Systeme werden auch vier Pioniere des Gebiets gewürdigt: Mortimer Taube, Hans Peter Luhn, Calvin N. Mooers und Gerard Salton. Dies verleiht dem von Studenten doch manchmal als trocken empfundenen Stoff eine menschliche Dimension. Das zweite und dritte Kapitel widmen sich der Wissensrepräsentation, wobei zuerst die grundlegenden Ansätze wie Indexierung, Klassifikation und Abstracting besprochen werden. Darauf folgt die Behandlung von Wissensrepräsentation mittels Metadaten, wobei v.a. neuere Ansätze wie Dublin Core und RDF behandelt werden. Weitere Unterkapitel widmen sich der Repräsentation von Volltexten und von Multimedia-Informationen. Die Stellung der Sprache im IRR wird in einem eigenen Kapitel behandelt. Dabei werden in knapper Form verschiedene Formen des kontrollierten Vokabulars und die wesentlichen Unterscheidungsmerkmale zur natürlichen Sprache erläutert. Die Eignung der beiden Repräsentationsmöglichkeiten für unterschiedliche IRR-Zwecke wird unter verschiedenen Aspekten diskutiert.
Die Kapitel fünf bis neun widmen sich dann ausführlich dem Information Retrieval. Zuerst werden grundlegende Retrievaltechniken vorgestellt und ihre Vor- und Nachteile dargestellt. Aus der Sicht des Nutzers von IR-Systemen wird der Prozess des Bildens einer Suchanfrage diskutiert und die damit verbundenen Probleme aufgezeigt. Im sechsten Kapitel werden die Retrieval-Ansätze Suchen und Browsen gegenübergestellt, entsprechende Suchstrategien aufgezeigt und schließlich Ansätze diskutiert, die suchen und browsen zu integrieren versuchen. Das siebte Kapitel beschäftigt sich dann mit dem, was den Kern der meisten IRBücher ausmacht: den IR-Modellen. Diese werden kurz vorgestellt, auf Formeln wird weitgehend verzichtet. Dies ist jedoch durchaus als Vorteil zu sehen, denn gerade Studienanfängern bereitet das Verständnis der IR-Modelle aufgrund deren Komplexität oft Schwierigkeiten. Nach der Lektüre dieses Kapitels wird man zwar nicht im Detail über die verschiedenen Modelle Bescheid wissen, wird sie jedoch kennen und einordnen können.
In Kapitel acht werden unterschiedliche Arten von IR-Systemen vorgestellt. Dies sind Online IR-Systeme, CD-ROM-Systeme, OPACs und Internet IR-Systeme, denen der Grossteil dieses Kapitels gewidmet ist. Zu jeder Art von System werden die historische Entwicklung und die Besonderheiten genannt. Bei den Internet-IR-Systemen wird ausführlich auf die besonderen Probleme, die bei diesen im Vergleich zu klassischen IR-Systemen auftauchen, eingegangen. Ein extra Kapitel behandelt die Besonderheiten des Retrievals bei besonderen Dokumentkollektionen und besonderen Formaten. Hier finden sich Informationen zum multilingualen Retrieval und zur Suche nach Multimedia-Inhalten, wobei besonders auf die Unterscheidung zwischen beschreibungs- und inhaltsbasiertem Ansatz der Erschließung solcher Inhalte eingegangen wird. In Kapitel zehn erfährt der Leser mehr über die Stellung des Nutzers in IRR-Prozessen. Die Autorin stellt verschiedene Arten von Suchinterfaces bzw. Benutzeroberflächen und Ansätze der Evaluation der Mensch-Maschine-Interaktion in solchen Systemen vor. Kapitel elf beschäftigt sich ausführlich mit der Evaluierung von IRR-Systemen und stellt die bedeutendsten Test (Cranfield und TREC) vor Ein kurzes abschließendes Kapitel behandelt Ansätze der künstlichen Intelligenz und ihre Anwendung bei IRR-Systemen. Der Aufbau, die knappe, aber dennoch präzise Behandlung des Themas sowie die verständliche Sprache machen dieses Buch zu eine sehr guten Einführung für Studenten in den ersten Semestern, die der englischen Sprache mächtig sind. Besonders positiv hervorzuheben ist die Behandlung auch der aktuellen Themen des IRR wie der Einsatz von Metadaten, die Behandlung von Multimedia-Informationen und der Schwerpunk bei den Internet-IR-Systemen.
Leider gibt es in deutscher Sprache keinen vergleichbaren Titel. Das Information-Retrieval-Buch von Ferber (2003) ist eher mathematisch orientiert und dürfte Studienanfänger der Informationswissenschaft durch seine große Detailliertheit und der damit einhergehenden großen Anzahl von Formeln eher abschrecken. Es ist eher denjenigen empfohlen, die sich intensiver mit dem Thema beschäftigen möchten. Ähnlich verhält es sich mit dem von manchen gerne genutzten Skript von Fuhr. Das Buch von Gaus (2003) ist mittlerweile schon ein Klassiker, beschäftigt sich aber im wesentlichen mit der Wissensrepräsentation und bietet zudem wenig Aktuelles. So fehlen etwa die Themen Information Retrieval im Internet und Multimedia-Retrieval komplett. Auch die Materialsammlung von Poetzsch (2002) konzentriert sich auf IR in klassischen Datenbanken und strebt zudem auch keine systematische Darstellung des Gebiets an. Zu wünschen wäre also, dass das hier besprochene Buch auch hierzulande in der Lehre Verwendung finden würde, da es den Studierenden einen knappen, gut lesbaren Einblick in das Themengebiet gibt. Es sollte aufgrund der vorbildlichen Aufbereitung des Stoffs auch Vorbild für zukünftige Autoren von Lehrbüchern sein. Und letztlich würde sich der Rezensent eine deutsche Übersetzung dieses Bandes wünschen."

LCSH

Information retrieval
Information storage and retrieval systems

Subject

Information retrieval
Information storage and retrieval systems

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Abstract

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

LCSH

Information storage and retrieval

Subject

Information storage and retrieval

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Abstract

This book constitutes the thoroughly refereed post-conference proceedings of the Second COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016, held in Cluj-Napoca, Romania, in September 2016. The 15 revised full papers and 2 invited papers are reviewed and selected from 18 initial submissions and cover the areas of keyword extraction, natural language searches, graph databases, information retrieval techniques for keyword search and document retrieval.

Content

Inhalt: Retrieval, Crawling and Fusion of Entity-centric Data on the Web / Dietze, Stefan - Data Multiverse: The Uncertainty Challenge of Future Big Data Analytics / Tudoran, Radu (et al.) - Experiments with Document Retrieval from Small Text Collections Using Latent Semantic Analysis or Term Similarity with Query Coordination and Automatic Relevance Feedback / Layfield, Colin (et al.) - Unsupervised Extraction of Conceptual Keyphrases from Abstracts / Ludwig, Philipp (et al.) - Back to the Sketch-Board: Integrating Keyword Search, Semantics, and Information Retrieval / Azzopardi, Joel (et al.) - Topic Detection in Multichannel Italian Newspapers / Po, Laura (et al.) - Random Walks Analysis on Graph Modelled Multimodal Collections / Sabetghadam, Serwah (et al.) - A Software Processing Chain for Evaluating Thesaurus Quality / Lacasta, Javier (et al.) - Comparison of Collaborative and Content-Based Automatic Recommendation Approaches in a Digital Library of Serbian PhD Dissertations / Azzopardi, Joel (et al.) - Keyword-Based Search on Bilingual Digital Libraries / Stankovic, Ranka (et al.) - Network-Enabled Keyword Extraction for Under-Resourced Languages / Beliga, Slobodan (et al.) - Making Sense of Citations / Koulouri, Xenia (et al.) - An Ontology-Based Approach to Information Retrieval / Mestrovic, Ana (et al.) - Game with a Purpose for Verification of Mappings Between Wikipedia and WordNet / Boinski, Tomasz - TB-Structure: Collective Intelligence for Exploratory Keyword Search / Terziyan, Vagan (et al.) - Using Natural Language to Search Linked Data / Rozinajová, Viera (et al.) - The Use of Semantics in the CrossCult H2020 Project / Bampatzia, Stavroula (et al.) Vgl. auch: http://www.keystone-cost.eu/ikc2016/program.php.

LCSH

Information storage and retrieval

Series

Lecture notes in computer science / Information Systems and Applications, incl. Internet/Web, and HCI ; 10151

Subject

Information storage and retrieval

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Abstract

Users' preferences for folders versus tags was studied in 2 working environments where both options were available to them. In the Gmail study, we informed 75 participants about both folder-labeling and tag-labeling, observed their storage behavior after 1 month, and asked them to estimate the proportions of different retrieval options in their behavior. In the Windows 7 study, we informed 23 participants about tags and asked them to tag all their files for 2 weeks, followed by a period of 5 weeks of free choice between the 2 methods. Their storage and retrieval habits were tested prior to the learning session and, after 7 weeks, using special classification recording software and a retrieval-habits questionnaire. A controlled retrieval task and an in-depth interview were conducted. Results of both studies show a strong preference for folders over tags for both storage and retrieval. In the minority of cases where tags were used for storage, participants typically used a single tag per information item. Moreover, when multiple classification was used for storage, it was only marginally used for retrieval. The controlled retrieval task showed lower success rates and slower retrieval speeds for tag use. Possible reasons for participants' preferences are discussed.

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Abstract

In this chapter, the authors describe the key indexing components of today's web search engines. As the World Wide Web has grown, the systems and methods for indexing have changed significantly. The authors present the data structures used, the features extracted, the infrastructure needed, and the options available for designing a brand new search engine. Techniques are highlighted that improve relevance of results, discuss trade-offs to best utilize machine resources, and cover distributed processing concepts in this context. In particular, the authors delve into the topics of indexing phrases instead of terms, storage in memory vs. on disk, and data partitioning. Some thoughts on information organization for the newly emerging data-forms conclude the chapter.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

Helen Brownson was a federal government employee from 1942 to 1970. At a time when scientific data were becoming exceedingly hard to manage, Brownson was instrumental in coordinating national and international efforts for more efficient, cost-effective, and universal information exchange. Her most significant contributions to documentation/information science were during her years at the National Science Foundation's Office of Scientific Information. From 1951 to 1966, Brownson played a key role in identifying and subsequently distributing government funds toward projects that sought to resolve information-handling problems of the time: information access, preservation, storage, classification, and retrieval. She is credited for communicating the need for information systems and indexing mechanisms to have stricter criteria, standards, and evaluation methods; laying the foundation for present-day NSF-funded computational linguistics projects; and founding several pertinent documentation/information science publications including the Annual Review of Information Science and Technology.

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Abstract

For introductory information retrieval courses at the undergraduate and graduate level in computer science, information science and computer engineering departments. Written by a leader in the field of information retrieval, Search Engines: Information Retrieval in Practice, is designed to give undergraduate students the understanding and tools they need to evaluate, compare and modify search engines. Coverage of the underlying IR and mathematical models reinforce key concepts. The book's numerous programming exercises make extensive use of Galago, a Java-based open source search engine. SUPPLEMENTS / Extensive lecture slides (in PDF and PPT format) / Solutions to selected end of chapter problems (Instructors only) / Test collections for exercises / Galago search engine

LCSH

Information retrieval
Information Storage and Retrieval

RSWK

Suchmaschine / Information Retrieval

Subject

Suchmaschine / Information Retrieval
Information retrieval
Information Storage and Retrieval

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LCSH

Information Systems
Information storage and retrieval systems
Multimedia systems

Subject

Information Systems
Information storage and retrieval systems
Multimedia systems

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LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems

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Abstract

Scholars have uncovered abundant data about the history of the term "information," as well as some of its many combined phrases (e.g., "information science," "information retrieval," and "information technology"). Many other compounds that involve "information" seem, however, not to have a known origin yet. In this article, further information about the phrase "information storage and retrieval" is provided. Knowing the history of terms and their associated concepts is an important prescription against poor terminological phrasing and theoretical confusion.

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Abstract

Recent, rapid changes in technology have resulted in a proliferation of choices for music storage and access. Portable, web-enabled music devices are widespread, and listeners now enjoy a plethora of options regarding formats, devices, and access methods. Yet in this mobile music environment, listeners' access and management strategies for music collections are poorly understood, because behaviors surrounding the organization and retrieval of music collections have received little formal study. Our current research seeks to enrich our knowledge of people's music listening and collecting behavior through a series of systematic user studies. In this paper we present our findings from interviews involving 20 adult and 20 teen users of commercial cloud music services. Our results contribute to theoretical understandings of users' music information behavior in a time of upheaval in music usage patterns, and more generally, the purposes and meanings users ascribe to personal media collections in cloud-based systems. The findings suggest improvements to the future design of cloud-based music services, as well as to any information systems and services designed for personal media collections, benefiting both commercial entities and listeners.

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Abstract

Purpose - This study aims to explore the journal bibliometric characteristics of the Journal of Documentation (JOD) and the subject relationship with other disciplines by citation analysis. Design/methodology/approach - The citation data were drawn from references of each article of JOD during 1998 and 2008. Ulrich's Periodicals Directory, Library of Congress Subject Heading, retrieved from the WorldCat and LISA database were used to identify the main class, subclass and subject of cited journals and books. Findings - The results of this study revealed that journal articles are the most cited document, followed by books and book chapters, electronic resources, and conference proceedings, respectively. The three main classes of cited journals in JOD papers are library science, science, and social sciences. The three subclasses of non-LIS journals that were highly cited in JOD papers are Science, "Mathematics. Computer science", and "Industries. Land use. Labor". The three highly cited subjects of library and information science journals encompass searching, information work, and online information retrieval. The most cited main class of books in JOD papers is library and information science, followed by social sciences, science, "Philosophy. Psychology. Religion." The three highly cited subclasses of books in JOD papers are "Books (General). Writing. Paleography. Book industries and trade. Libraries. Bibliography," "Philology and linguistics," and Science, and the most cited subject of books is information storage and retrieval systems. Originality/value - Results for the present research found that information science, as represented by JOD, is a developing discipline with an expanding literature relating to multiple subject areas.

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Abstract

This article first analyzes library and information science (LIS) research articles published in core LIS journals in 2005. It also examines the development of LIS from 1965 to 2005 in light of comparable data sets for 1965, 1985, and 2005. In both cases, the authors report (a) how the research articles are distributed by topic and (b) what approaches, research strategies, and methods were applied in the articles. In 2005, the largest research areas in LIS by this measure were information storage and retrieval, scientific communication, library and information-service activities, and information seeking. The same research areas constituted the quantitative core of LIS in the previous years since 1965. Information retrieval has been the most popular area of research over the years. The proportion of research on library and information-service activities decreased after 1985, but the popularity of information seeking and of scientific communication grew during the period studied. The viewpoint of research has shifted from library and information organizations to end users and development of systems for the latter. The proportion of empirical research strategies was high and rose over time, with the survey method being the single most important method. However, attention to evaluation and experiments increased considerably after 1985. Conceptual research strategies and system analysis, description, and design were quite popular, but declining. The most significant changes from 1965 to 2005 are the decreasing interest in library and information-service activities and the growth of research into information seeking and scientific communication.

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Abstract

Classification is the process of assigning objects to pre-defined classes based on observations or characteristics of those objects, and there are many approaches to performing this task. The overall objective of this study is to demonstrate the use of two learning techniques to analyze the results of a manual classification system. Our sample consisted of 1,026 documents, from the ACM Computing Classification System, classified by their authors as belonging to one of the groups of the classification system: "H.3 Information Storage and Retrieval." A singular value decomposition of the documents' weighted term-frequency matrix was used to represent each document in a 50-dimensional vector space. The analysis of the representation using both supervised (decision tree) and unsupervised (clustering) techniques suggests that two pairs of the ACM classes are closely related to each other in the vector space. Class 1 (Content Analysis and Indexing) is closely related to Class 3 (Information Search and Retrieval), and Class 4 (Systems and Software) is closely related to Class 5 (Online Information Services). Further analysis was performed to test the diffusion of the words in the two classes using both cosine and Euclidean distance.

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Abstract

The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.
With the rapid growth of web-based applications, such as search engines, Facebook, and Twitter, the development of effective and personalized information retrieval techniques and of user interfaces is essential. The amount of shared information and of social networks has also considerably grown, requiring metadata for new sources of information, like Wikipedia and ODP. These metadata have to provide classification information for a wide range of topics, as well as for social networking sites like Twitter, and Facebook, each of which provides additional preferences, tagging information and social contexts. Due to the explosion of social networks and other metadata sources, it is an opportune time to identify ways to exploit such metadata in IR tasks such as user modeling, query understanding, and personalization, to name a few. Although the use of traditional metadata such as html text, web page titles, and anchor text is fairly well-understood, the use of category information, user behavior data, and geographical information is just beginning to be studied. This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers.

Content

Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.

LCSH

Information retrieval
Information retrieval / Research
Information storage and retrieval systems / Research
User interfaces (Computer systems)

Subject

Information retrieval
Information retrieval / Research
Information storage and retrieval systems / Research
User interfaces (Computer systems)

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Abstract

Archival Information Systems (AIS) are becoming increasingly important. For decades, the amount of content created digitally is growing and its complete life cycle nowadays tends to remain digital. A selection of this content is expected to be of value for the future and can thus be considered being part of our cultural heritage. However, digital content poses many challenges for long-term or indefinite preservation, e.g. digital publications become increasingly complex by the embedding of different kinds of multimedia, data in arbitrary formats and software. As soon as these digital publications become obsolete, but are still deemed to be of value in the future, they have to be transferred smoothly into appropriate AIS where they need to be kept accessible even through changing technologies. The successful previous SDA workshop in 2011 showed: Both, the library and the archiving community have made valuable contributions to the management of huge amounts of knowledge and data. However, both are approaching this topic from different views which shall be brought together to cross-fertilize each other. There are promising combinations of pertinence and provenance models since those are traditionally the prevailing knowledge organization principles of the library and archiving community, respectively. Another scientific discipline providing promising technical solutions for knowledge representation and knowledge management is semantic technologies, which is supported by appropriate W3C recommendations and a large user community. At the forefront of making the semantic web a mature and applicable reality is the linked data initiative, which already has started to be adopted by the library community. It can be expected that using semantic (web) technologies in general and linked data in particular can mature the area of digital archiving as well as technologically tighten the natural bond between digital libraries and digital archives. Semantic representations of contextual knowledge about cultural heritage objects will enhance organization and access of data and knowledge. In order to achieve a comprehensive investigation, the information seeking and document triage behaviors of users (an area also classified under the field of Human Computer Interaction) will also be included in the research.
One of the major challenges of digital archiving is how to deal with changing technologies and changing user communities. On the one hand software, hardware and (multimedia) data formats that become obsolete and are not supported anymore still need to be kept accessible. On the other hand changing user communities necessitate technical means to formalize, detect and measure knowledge evolution. Furthermore, digital archival records are usually not deleted from the AIS and therefore, the amount of digitally archived (multimedia) content can be expected to grow rapidly. Therefore, efficient storage management solutions geared to the fact that cultural heritage is not as frequently accessed like up-to-date content residing in a digital library are required. Software and hardware needs to be tightly connected based on sophisticated knowledge representation and management models in order to face that challenge. In line with the above, contributions to the workshop should focus on, but are not limited to:
Semantic search & semantic information retrieval in digital archives and digital libraries Semantic multimedia archives Ontologies & linked data for digital archives and digital libraries Ontologies & linked data for multimedia archives Implementations and evaluations of semantic digital archives Visualization and exploration of digital content User interfaces for semantic digital libraries User interfaces for intelligent multimedia information retrieval User studies focusing on end-user needs and information seeking behavior of end-users Theoretical and practical archiving frameworks using Semantic (Web) technologies Logical theories for digital archives Semantic (Web) services implementing the OAIS standard Semantic or logical provenance models for digital archives or digital libraries Information integration/semantic ingest (e.g. from digital libraries) Trust for ingest and data security/integrity check for long-term storage of archival records Semantic extensions of emulation/virtualization methodologies tailored for digital archives Semantic long-term storage and hardware organization tailored for AIS Migration strategies based on Semantic (Web) technologies Knowledge evolution We expect new insights and results for sustainable technical solutions for digital archiving using knowledge management techniques based on semantic technologies. The workshop emphasizes interdisciplinarity and aims at an audience consisting of scientists and scholars from the digital library, digital archiving, multimedia technology and semantic web community, the information and library sciences, as well as, from the social sciences and (digital) humanities, in particular people working on the mentioned topics. We encourage end-users, practitioners and policy-makers from cultural heritage institutions to participate as well.

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Abstract

Purpose - Content-based image retrieval (CBIR) technologies offer many advantages over purely text-based image search. However, one of the drawbacks associated with CBIR is the increased computational cost arising from tasks such as image processing, feature extraction, image classification, and object detection and recognition. Consequently CBIR systems have suffered from a lack of scalability, which has greatly hampered their adoption for real-world public and commercial image search. At the same time, paradigms for large-scale heterogeneous distributed computing such as grid computing, cloud computing, and utility-based computing are gaining traction as a way of providing more scalable and efficient solutions to large-scale computing tasks. Design/methodology/approach - This paper presents an approach in which a large distributed processing grid has been used to apply a range of CBIR methods to a substantial number of images. By massively distributing the required computational task across thousands of grid nodes, very high through-put has been achieved at relatively low overheads. Findings - This has allowed one to analyse and index about 25 million high resolution images thus far, while using just two servers for storage and job submission. The CBIR system was developed by Imense Ltd and is based on automated analysis and recognition of image content using a semantic ontology. It features a range of image-processing and analysis modules, including image segmentation, region classification, scene analysis, object detection, and face recognition methods. Originality/value - In the case of content-based image analysis, the primary performance criterion is the overall through-put achieved by the system in terms of the number of images that can be processed over a given time frame, irrespective of the time taken to process any given image. As such, grid processing has great potential for massively parallel content-based image retrieval and other tasks with similar performance requirements.

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Abstract

Discover Digital Libraries: Theory and Practice is a book that integrates both research and practice concerning digital library development, use, preservation, and evaluation. The combination of current research and practical guidelines is a unique strength of this book. The authors bring in-depth expertise on different digital library issues and synthesize theoretical and practical perspectives relevant to researchers, practitioners, and students. The book presents a comprehensive overview of the different approaches and tools for digital library development, including discussions of the social and legal issues associated with digital libraries. Readers will find current research and the best practices of digital libraries, providing both US and international perspectives on the development of digital libraries and their components, including collection, digitization, metadata, interface design, sustainability, preservation, retrieval, and evaluation of digital libraries.

Content

Introduction to digital libraries - Digital library initiatives and international projects - Collection development - Techniques and technologies for multimedia storage and retrieval - Digitization - Knowledge representation and organization - Digital Library Content Management Systems - Interface design and evaluation - Sustainability and preservation - User needs and information retrieval - Evaluation of digital libraries - Impact, challenges, and trends for the future