Search (97 results, page 5 of 5)

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Abstract

Eine der größten Herausforderungen für alle technischen Anwendungen ist die sogenannte Mensch-Maschine-Schnittstelle, also der Problemkreis, wie der bedienende Mensch mit der zu bedienenden Technik kommunizieren kann. Waren die Benutzungsschnittstellen bis Ende der Achtziger Jahre vor allem durch die Notwendigkeit des Benutzers geprägt, sich an die Erfordernisse der Maschine anzupassen, so wurde mit Durchsetzung grafischer Benutzungsoberflächen zunehmend versucht, die Bedienbarkeit so zu gestalten, dass ein Mensch auch ohne größere Einarbeitung in die Lage versetzt werden sollte, seine Befehle der Technik - letztlich also dem Computer - zu übermitteln. Trotz aller Fortschritte auf diesem Gebiet blieb immer die Anforderung, der Mensch solle auf die ihm natürlichste Art und Weise kommunizieren können, mit menschlicher Sprache. Diese Anforderung gilt gerade auch für das Retrieval von Informationen: Warum ist es nötig, die Nutzung von Booleschen Operatoren zu erlernen, nur um eine Suchanfrage stellen zu können? Ein anderes Thema ist die Frage nach der Visualisierung von Wissenszusammenhängen, die sich der Herausforderung stellt, in einem geradezu uferlos sich ausweitenden Informationsangebot weiterhin den Überblick behalten und relevante Informationen schnellstmöglich finden zu können.

Series

Schriften der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare (VÖB); Bd. 2

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Abstract

Es wird eine Methode vorgestellt, wie sich Ordnungssysteme für die Suche in textbasierten Datenbeständen verwenden lassen. "Ordnungssystem" wird hier als Oberbegriff für beliebige geordnete Begriffssammlungen verwendet. Dies sind beispielsweise Thesauri, Klassifikationen und formale Systematiken. Weil Thesauri dabei die leistungsfähigsten Ordnungssysteme sind, finden sie eine besondere Berücksichtigung. Der Beitrag ist streng praxisbezogenen und auf die Nutzerschnittstelle konzentriert. Die Basis für die Nutzerschnittstelle bilden Ordnungssysteme, die über eine WWW-Schnittstelle angeboten werden. Je nach Fachgebiet kann der Nutzer ein spezielles Ordnungssystem für die Suche auswählen. Im Unterschied zu klassischen Verfahren werden die Ordnungssysteme nicht zur ausschließlichen Suche in Deskriptorenfeldern, sondern für die Suche in einem Basic Index verwendet. In der Anwendung auf den Basic Index sind die Ordnungssysteme quasi "entkoppelt" von der ursprünglichen Datenbank und den Deskriptorenfeldern, für die das Ordnungssystem entwickelt wurde. Die Inhalte einer Datenbank spielen bei der Wahl der Ordnungssysteme zunächst keine Rolle. Sie machen sich erst bei der Suche in der Anzahl der Treffer bemerkbar: so findet ein rechtswissenschaftlicher Thesaurus natürlicherweise in einer Medizin-Datenbank weniger relevante Dokumente als in einer Rechts-Datenbank, weil das im Rechts-Thesaurus abgebildete Begriffsgut eher in einer Rechts-Datenbank zu finden ist. Das Verfahren ist modular aufgebaut und sieht in der Konzeption nachgeordnete semantische Retrievalverfahren vor, die zu einer Verbesserung von Retrievaleffektivität und -effizienz führen werden. So werden aus einer Ergebnismenge, die ausschließlich durch exakten Zeichenkettenabgleich gefunden wurde, in einem nachfolgenden Schritt durch eine semantische Analyse diejenigen Dokumente herausgefiltert, die für die Suchfrage relevant sind. Die WWW-Nutzerschnittstelle und die Verwendung bereits bestehender Ordnungssysteme führen zu einer Minimierung des Arbeitsaufwands auf Nutzerseite. Die Kosten für eine Suche lassen sich sowohl auf der Input-Seite verringern, indem eine aufwendige "manuelle" Indexierung entfällt, als auch auf der Output-Seite, indem den Nutzern leicht bedienbare Suchoptionen zur Verfügung gestellt werden

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Footnote

Rez. in: JASIST 54(2003) no.7, S.695-697 (R. Savolainen): "Donald O. Case has written an ambitious book to create an overall picture of the major approaches to information needs and seeking (INS) studies. The aim to write an extensive review is reflected in the list of references containing about 700 items. The high ambitions are explained an p. 14, where Case states that he is aiming at a multidisciplinary understanding of the concept of information seeking. In the Preface, the author characterizes his book as an introduction to the topic for students at the graduate level, as well as as a review and handbook for scholars engagged in information behavior research. In my view, Looking for Information is particularly welcome as an academic textbook because the field of INS studies suffers from the lack of monographs. Along with the continuous growth of the number of journal articles and conference papers, there is a genuine need for a book that picks up the numerous pieces and puts them together. The use of the study as a textbook is facilitated by clearly delineated sections an major themes and the wealth of concrete examples of information seeking in everyday contexts. The book is lucidly written and it is accessible to novice readers, too. At first glance, the idea of providing a comprehensive review of INS studies may seem a mission impossible because the current number of articles, papers, and other contributions in this field is nearing the 10,000 range (p. 224). Donald Case is not alone in the task of coming to grips with an increasing number of studies; similar problems have been faced by those writing INS-related chapters for the Annual Review of Information Science and Technology (ARIST). Case has solved the problem of "too many publications to be reviewed" by concentrating an the INS literature published during the last two decades. Secondly, studies an library use and information retrieval are discussed only to a limited extent. In addition, Case is highly selective as to studies focusing an the use of specific sources and channels such as WWW. These delineations are reasonable, even though they beg some questions. First, how should one draw the line between studies an information seeking and information retrieval? Case does not discuss this question in greater detail, although in recent years, the overlapping areas of information seeking and retrieval studies have been broadened, along with the growing importance of WWW in information seeking/retrieval. Secondly, how can one define the concept of information searching (or, more specifically, Internet or Web searching) in relation to information seeking and information retrieval? In the field of Web searching studies, there is an increasing number of contributions that are of direct relevance to information-seeking studies. Clearly, the advent of the Internet, particularly, the Web, has blurred the previous lines between INS and IR literature, making them less clear cut. The book consists of five main sections, and comprises 13 chapters. There is an Appendix serving the needs of an INS textbook (questions for discussion and application). The structure of the book is meticulously planned and, as a whole, it offers a sufficiently balanced contribution to theoretical, methodological, and empirical issues of INS. The title, Looking for Information: A Survey of Research an Information Seeking, Needs, and Behavior aptly describes the main substance of the book. . . . It is easy to agree with Case about the significance of the problem of specialization and fragmentation. This problem seems to be concomitant with the broadening field of INS research. In itself, Case's book can be interpreted as a struggle against this fragmentation. His book suggests that this struggle is not hopeless and that it is still possible to draw an overall picture of the evolving research field. The major pieces of the puzzle were found and the book will provide a useful overview of INS studies for many years."

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Abstract

Today's complex, information-intensive problems often require people to work together. Mostly these tasks go far beyond simply searching together; they include information lookup, sharing, synthesis, and decision-making. In addition, they all have an end-goal that is mutually beneficial to all parties involved. Such "collaborative information seeking" (CIS) projects typically last several sessions and the participants all share an intention to contribute and benefit. Not surprisingly, these processes are highly interactive. Shah focuses on two individually well-understood notions: collaboration and information seeking, with the goal of bringing them together to show how it is a natural tendency for humans to work together on complex tasks. The first part of his book introduces the general notions of collaboration and information seeking, as well as related concepts, terminology, and frameworks; and thus provides the reader with a comprehensive treatment of the concepts underlying CIS. The second part of the book details CIS as a standalone domain. A series of frameworks, theories, and models are introduced to provide a conceptual basis for CIS. The final part describes several systems and applications of CIS, along with their broader implications on other fields such as computer-supported cooperative work (CSCW) and human-computer interaction (HCI). With this first comprehensive overview of an exciting new research field, Shah delivers to graduate students and researchers in academia and industry an encompassing description of the technologies involved, state-of-the-art results, and open challenges as well as research opportunities.

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Abstract

Purpose - The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach - The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings - The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value - Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.

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Abstract

This paper presents a Graph Inference retrieval model that integrates structured knowledge resources, statistical information retrieval methods and inference in a unified framework. Key components of the model are a graph-based representation of the corpus and retrieval driven by an inference mechanism achieved as a traversal over the graph. The model is proposed to tackle the semantic gap problem-the mismatch between the raw data and the way a human being interprets it. We break down the semantic gap problem into five core issues, each requiring a specific type of inference in order to be overcome. Our model and evaluation is applied to the medical domain because search within this domain is particularly challenging and, as we show, often requires inference. In addition, this domain features both structured knowledge resources as well as unstructured text. Our evaluation shows that inference can be effective, retrieving many new relevant documents that are not retrieved by state-of-the-art information retrieval models. We show that many retrieved documents were not pooled by keyword-based search methods, prompting us to perform additional relevance assessment on these new documents. A third of the newly retrieved documents judged were found to be relevant. Our analysis provides a thorough understanding of when and how to apply inference for retrieval, including a categorisation of queries according to the effect of inference. The inference mechanism promoted recall by retrieving new relevant documents not found by previous keyword-based approaches. In addition, it promoted precision by an effective reranking of documents. When inference is used, performance gains can generally be expected on hard queries. However, inference should not be applied universally: for easy, unambiguous queries and queries with few relevant documents, inference did adversely affect effectiveness. These conclusions reflect the fact that for retrieval as inference to be effective, a careful balancing act is involved. Finally, although the Graph Inference model is developed and applied to medical search, it is a general retrieval model applicable to other areas such as web search, where an emerging research trend is to utilise structured knowledge resources for more effective semantic search.

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Abstract

The field of human information behavior runs the gamut of processes from the realization of a need or gap in understanding, to the search for information from one or more sources to fill that gap, to the use of that information to complete a task at hand or to satisfy a curiosity, as well as other behaviors such as avoiding information or finding information serendipitously. Designers of mechanisms, tools, and computer-based systems to facilitate this seeking and search process often lack a full knowledge of the context surrounding the search. This context may vary depending on the job or role of the person; individual characteristics such as personality, domain knowledge, age, gender, perception of self, etc.; the task at hand; the source and the channel and their degree of accessibility and usability; and the relationship that the seeker shares with the source. Yet researchers have yet to agree on what context really means. While there have been various research studies incorporating context, and biennial conferences on context in information behavior, there lacks a clear definition of what context is, what its boundaries are, and what elements and variables comprise context. In this book, we look at the many definitions of and the theoretical and empirical studies on context, and I attempt to map the conceptual space of context in information behavior. I propose theoretical frameworks to map the boundaries, elements, and variables of context. I then discuss how to incorporate these frameworks and variables in the design of research studies on context. We then arrive at a unified definition of context. This book should provide designers of search systems a better understanding of context as they seek to meet the needs and demands of information seekers. It will be an important resource for researchers in Library and Information Science, especially doctoral students looking for one resource that covers an exhaustive range of the most current literature related to context, the best selection of classics, and a synthesis of these into theoretical frameworks and a unified definition. The book should help to move forward research in the field by clarifying the elements, variables, and views that are pertinent. In particular, the list of elements to be considered, and the variables associated with each element will be extremely useful to researchers wanting to include the influences of context in their studies.

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Abstract

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.

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Abstract

In der folgenden Studie wird eine Komponente für eine visuelle Benutzerschnittstelle zu Textdatenbanken entworfen. Mit Hilfe einer Terminologievisualisierung wird dem Benutzer eine Hilfestellung bei der Relevanzbewertung von Dokumenten und bei der Erweiterung seiner visuellen Anfrage an das Retrieval-System gegeben. Dazu werden zuerst die grundlegenden Information-Retrieval-Modelle eingehender vorgestellt, d.h., generelle Retrieval-Modelle, Retrievaloperationen und spezielle Retrieval-Modelle wie Text-Retrieval werden erläutert. Die Funktionalität eines Text-Retrieval-Systems wird vorgestellt. Darüber hinaus werden bereits existierende Implementierungen visueller Information-Retrieval-Benutzerschnittstellen vorgestellt. Im weiteren Verlauf der Arbeit werden mögliche Visualisierungen der mit Hilfe eines Text-Retrieval-Systems gefundenen Dokumente aufgezeigt. Es werden mehrere Vorschläge zur Visualisierung von Thesauri diskutiert. Es wird gezeigt, wie neuronale Netze zur Kartierung eines Eingabebereiches benutzt werden können. Klassifikationsebenen einer objekt-orientierten Annäherung eines Information-Retrieval-Systems werden vorgestellt. In diesem Zusammenhang werden auch die Eigenschaften von Thesauri sowie die Architektur und Funktion eines Parsersystems erläutert. Mit diesen Voraussetzung wird die Implementierung einer visuellen Terminologierunterstützung realisiert. Abschließend wird ein Fazit zur vorgestellten Realisierung basierend auf einem Drei-Schichten-Modell von [Agosti et al. 1990] gezogen.

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Abstract

Volltextsuchmaschinen sind längst nicht mehr in der Lage, das Informationsbedürfnis angesichts ständig wachsender Datenmengen zu erfüllen. Gerade Unternehmen suchen nach Alternativen und Ergänzungen, um ihre Wissensressourcen effizient zu nutzen. Verschiedene Wissensmanagement-Lösungen erfreuen sich daher wachsender Beliebtheit.

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Theme

Konzeption und Anwendung des Prinzips Thesaurus

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Series

Bibliotheca Academica - Reihe Informations- und Bibliothekswissenschaften; Bd. 1

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Abstract

However, this assumption does not hold in all cases, the needs of the user evolve over time and can move away from his previous interests stored in his profile. In other cases, the user's profile may be misused to extract or infer new information needs. This problem is much more accentuated with ambiguous queries. When multiple POIs linked to a search query are identified in the user's profile, the system is unable to select the relevant data from that profile to respond to that request. This has a direct impact on the quality of the results provided to this user. In order to overcome some of these limitations, in this research thesis, we have been interested in the development of techniques aimed mainly at improving the relevance of the results of current SRIs and facilitating the exploration of major collections of documents. To do this, we propose a solution based on a new concept and model of indexing and information retrieval called multi-spaces projection. This proposal is based on the exploitation of different categories of semantic and social information that enrich the universe of document representation and search queries in several dimensions of interpretations. The originality of this representation is to be able to distinguish between the different interpretations used for the description and the search for documents. This gives a better visibility on the results returned and helps to provide a greater flexibility of search and exploration, giving the user the ability to navigate one or more views of data that interest him the most. In addition, the proposed multidimensional representation universes for document description and search query interpretation help to improve the relevance of the user's results by providing a diversity of research / exploration that helps meet his diverse needs and those of other different users. This study exploits different aspects that are related to the personalized search and aims to solve the problems caused by the evolution of the information needs of the user. Thus, when the profile of this user is used by our system, a technique is proposed and used to identify the interests most representative of his current needs in his profile. This technique is based on the combination of three influential factors, including the contextual, frequency and temporal factor of the data. The ability of users to interact, exchange ideas and opinions, and form social networks on the Web, has led systems to focus on the types of interactions these users have at the level of interaction between them as well as their social roles in the system. This social information is discussed and integrated into this research work. The impact and how they are integrated into the IR process are studied to improve the relevance of the results.