Search (53 results, page 2 of 3)

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Abstract

This book outlines the human side of the information seeking process, and focuses on the aspects of this process that can best be supported by the user interface. It describes the methods behind user interface design generally, and search interface design in particular, with an emphasis on how best to evaluate search interfaces. It discusses research results and current practices surrounding user interfaces for query specification, display of retrieval results, grouping retrieval results, navigation of information collections, query reformulation, search personalization, and the broader tasks of sensemaking and text analysis. Much of the discussion pertains to Web search engines, but the book also covers the special considerations surrounding search of other information collections.

RSWK

World Wide Web / Information Retrieval / Mensch-Maschine-Kommunikation / Benutzerorientierung (HBZ)

Subject

World Wide Web / Information Retrieval / Mensch-Maschine-Kommunikation / Benutzerorientierung (HBZ)

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Abstract

Purpose The study aims to paint a representative picture of the current state of search interfaces of Swedish online museum collections, focussing on search functionalities with particular reference to subject searching, as well as the use of controlled vocabularies, with the purpose of identifying which improvements of the search interfaces are needed to ensure high-quality information retrieval for the end user. Design/methodology/approach In the first step, a set of 21 search interface criteria was identified, based on related research and current standards in the domain of cultural heritage knowledge organization. Secondly, a complete set of Swedish museums that provide online access to their collections was identified, comprising nine cross-search services and 91 individual museums' websites. These 100 websites were each evaluated against the 21 criteria, between 1 July and 31 August 2020. Findings Although many standards and guidelines are in place to ensure quality-controlled subject indexing, which in turn support information retrieval of relevant resources (as individual or full search results), the study shows that they are not broadly implemented, resulting in information retrieval failures for the end user. The study also demonstrates a strong need for the implementation of controlled vocabularies in these museums. Originality/value This study is a rare piece of research which examines subject searching in online museums; the 21 search criteria and their use in the analysis of the complete set of online collections of a country represents a considerable and unique contribution to the fields of knowledge organization and information retrieval of cultural heritage. Its particular value lies in showing how the needs of end users, many of which are documented and reflected in international standards and guidelines, should be taken into account in designing search tools for these museums; especially so in subject searching, which is the most complex and yet the most common type of search. Much effort has been invested into digitizing cultural heritage collections, but access to them is hindered by poor search functionality. This study identifies which are the most important aspects to improve.

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Abstract

The use of thesaurus-based indexing is a common approach for increasing the performance of information retrieval. In this thesis, we examine the suitability of a thesaurus for a given set of information and evaluate improvements of existing thesauri to get better search results. On this area, we focus on two aspects: 1. We demonstrate an analysis of the indexing results achieved by an automatic document indexer and the involved thesaurus. 2. We propose a method for thesaurus evaluation which is based on a combination of statistical measures and appropriate visualization techniques that support the detection of potential problems in a thesaurus. In this chapter, we give an overview of the context of our work. Next, we briefly outline the basics of thesaurus-based information retrieval and describe the Collexis Engine that was used for our experiments. In Chapter 3, we describe two experiments in automatically indexing documents in the areas of medicine and economics with corresponding thesauri and compare the results to available manual annotations. Chapter 4 describes methods for assessing thesauri and visualizing the result in terms of a treemap. We depict examples of interesting observations supported by the method and show that we actually find critical problems. We conclude with a discussion of open questions and future research in Chapter 5.

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Abstract

In this article we present a method for retrieving documents from a digital library through a visual interface based on automatically generated concepts. We used a vocabulary generation algorithm to generate a set of concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. An online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test the utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks. Over the past few years, the volume of information available through the World Wide Web has been expanding exponentially. Never has so much information been so readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over networks have made it hard for users to sift through and find relevant information. To deal with this problem, information retrieval (IR) techniques have gained more intensive attention from both industrial and academic researchers. Numerous IR techniques have been developed to help deal with the information overload problem. These techniques concentrate on mathematical models and algorithms for retrieval. Popular IR models such as the Boolean model, the vector-space model, the probabilistic model and their variants are well established.
From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

The internal organization of large software projects requires an extraordinary effort in the development and maintenance of repositories made up of software artifacts (business components, data models, functional and technical documentation, etc.). During the software development process, different artifacts are created to help users in the transfer of knowledge and enable communication between workers and teams. The storage, maintenance and publication of these artifacts in knowledge bases - usually referred to as "software repositories" are a useful tool for future software development projects, as they contain the collective, learned experience of the teams and provide the basis to estimate and reuse the work completed in the past. Different techniques similar to those used by the library community have been used in the past to organize these software repositories and help users in the difficult task or identifying and retrieving artifacts (software and documentation). These techniques include software classification - with a special emphasis on faceted classifications, keyword-based retrieval and formal method techniques. The paper discusses the different knowledge organization techniques applied in these repositories to identify and retrieve software artifacts and ensure the reusability of software components and documentation at the different phases of the development process across different projects. An enumeration of the main approaches documented in specialized bibliography is provided.

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Theme

Klassifikationssysteme im Online-Retrieval

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Abstract

Geospatial information technologies revolutionize the way we have traditionally approached navigation and browsing in information systems. Colorful graphics, statistical summaries, geospatial relationships of underlying collections make them attractive for text retrieval systems. This paper examines the nature of georeferenced information in academic library catalogs organized according to the Library of Congress Classification (LCC) with the goal of understanding their implications for geovisualization of library collections.

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Date

1. 2.2016 18:25:22

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Theme

Klassifikationssysteme im Online-Retrieval

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Theme

Klassifikationssysteme im Online-Retrieval

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Content

The aim of this study is to develop a software tool, VisuaLCSH, for effective searching, browsing, and maintenance of LCSH. This tool enables visualizing subject headings and hierarchical structures implied and embedded in LCSH. A conceptual framework for converting the hierarchical structure of headings in LCSH to an explicit tree structure is proposed, described, and implemented. The highlights of VisuaLCSH are summarized below: 1) revealing multiple aspects of a heading; 2) normalizing the hierarchical relationships in LCSH; 3) showing multi-level hierarchies in LCSH sub-trees; 4) improving the navigational function of LCSH in retrieval; and 5) enabling the implementation of generic search, i.e., the 'exploding' feature, in searching LCSH.

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Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56

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Abstract

The concept of c-space is proposed as a visualization schema relating containers of content to cataloging surrogates and classification structures. Possible applications of keyword vector clusters within c-space could include improved retrieval rates through the use of captioning within visual hierarchies, tracings of semantic bleeding among subclasses, and access to buried knowledge within subject-neutral publication containers. The Scholastica Project is described as one example, following a tradition of research dating back to the 1980's. Preliminary focus group assessment indicates that this type of classification rendering may offer digital library searchers enriched entry strategies and an expanded range of re-entry vocabularies. Those of us who work in traditional libraries typically assume that our systems of classification: Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC), are descriptive rather than prescriptive. In other words, LCC classes and subclasses approximate natural groupings of texts that reflect an underlying order of knowledge, rather than arbitrary categories prescribed by librarians to facilitate efficient shelving. Philosophical support for this assumption has traditionally been found in a number of places, from the archetypal tree of knowledge, to Aristotelian categories, to the concept of discursive formations proposed by Michel Foucault. Gary P. Radford has elegantly described an encounter with Foucault's discursive formations in the traditional library setting: "Just by looking at the titles on the spines, you can see how the books cluster together...You can identify those books that seem to form the heart of the discursive formation and those books that reside on the margins. Moving along the shelves, you see those books that tend to bleed over into other classifications and that straddle multiple discursive formations. You can physically and sensually experience...those points that feel like state borders or national boundaries, those points where one subject ends and another begins, or those magical places where one subject has morphed into another..."
But what happens to this awareness in a digital library? Can discursive formations be represented in cyberspace, perhaps through diagrams in a visualization interface? And would such a schema be helpful to a digital library user? To approach this question, it is worth taking a moment to reconsider what Radford is looking at. First, he looks at titles to see how the books cluster. To illustrate, I scanned one hundred books on the shelves of a college library under subclass HT 101-395, defined by the LCC subclass caption as Urban groups. The City. Urban sociology. Of the first 100 titles in this sequence, fifty included the word "urban" or variants (e.g. "urbanization"). Another thirty-five used the word "city" or variants. These keywords appear to mark their titles as the heart of this discursive formation. The scattering of titles not using "urban" or "city" used related terms such as "town," "community," or in one case "skyscrapers." So we immediately see some empirical correlation between keywords and classification. But we also see a problem with the commonly used search technique of title-keyword. A student interested in urban studies will want to know about this entire subclass, and may wish to browse every title available therein. A title-keyword search on "urban" will retrieve only half of the titles, while a search on "city" will retrieve just over a third. There will be no overlap, since no titles in this sample contain both words. The only place where both words appear in a common string is in the LCC subclass caption, but captions are not typically indexed in library Online Public Access Catalogs (OPACs). In a traditional library, this problem is mitigated when the student goes to the shelf looking for any one of the books and suddenly discovers a much wider selection than the keyword search had led him to expect. But in a digital library, the issue of non-retrieval can be more problematic, as studies have indicated. Micco and Popp reported that, in a study funded partly by the U.S. Department of Education, 65 of 73 unskilled users searching for material on U.S./Soviet foreign relations found some material but never realized they had missed a large percentage of what was in the database.

Theme

Klassifikationssysteme im Online-Retrieval

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Abstract

UDC aims to be a consistent and complete classification system, that enables practitioners to classify documents swiftly and smoothly. The eventual goal of UDC is to enable the public at large to retrieve documents from large collections of documents that are classified with UDC. The large size of the UDC Master Reference File, MRF with over 66.000 records, makes it difficult to obtain an overview and to understand its structure. Moreover, finding the right classification in MRF turns out to be difficult in practice. Last but not least, retrieval of documents requires insight and understanding of the coding system. Visualization is an effective means to support the development of UDC as well as its use by practitioners. Moreover, visualization offers possibilities to use the classification without use of the coding system as such. MagnaView has developed an application which demonstrates the use of interactive visualization to face these challenges. In our presentation, we discuss these challenges, and we give a demonstration of the way the application helps face these. Examples of visualizations can be found below.

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Abstract

Purpose - This paper aims to explore the theory and practice of knowledge organization and its necessary connection to human perception, and shows a solution of the potential ones. Design/methodology/approach - The author attempts to survey the problem of concept-building and extension, as well as the determination of semantics in different aspects. The purpose is to find criteria for the choice of the solution that best incorporates users into the design cycles of knowledge organization systems. Findings - It is widely agreed that cognition provides the basis for concept-building; however, at the next stage of processing there is a debate. Fundamentally, what is the connection between perception and the superior cognitive processes? The perceptual method does not separate these two but rather considers them united, with perception permeating cognition. By contrast, the linguistic method considers perception as an information-receiving system. Separate from, and following, perception, the cognitive subsystems then perform information and data processing, leading to both knowledge organization and representation. We assume by that model that top-level concepts emerge from knowledge organization and representation. This paper points obvious connection of visual imagery and the internet; perceptual access of knowledge organization and information retrieval. There are some practical and characteristic solutions for the visualization of information without demand of completeness. Research limitations/implications - Librarians need to identify those semantic characteristics which stimulate a similar conceptual image both in the mind of the librarian and in the mind of the user. Originality/value - For a fresh perspective, an understanding of perception is required as well.

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Abstract

Although information retrieval techniques used by Web search engines have improved substantially over the years, the results of Web searches have continued to be represented in simple list-based formats. Although the list-based representation makes it easy to evaluate a single document for relevance, it does not support the users in the broader tasks of manipulating or exploring the search results as they attempt to find a collection of relevant documents. HotMap is a meta-search system that provides a compact visual representation of Web search results at two levels of detail, and it supports interactive exploration via nested sorting of Web search results based on query term frequencies. An evaluation of the search results for a set of vague queries has shown that the re-sorted search results can provide a higher portion of relevant documents among the top search results. User studies show an increase in speed and effectiveness and a reduction in missed documents when comparing HotMap to the list-based representation used by Google. Subjective measures were positive, and users showed a preference for the HotMap interface. These results provide evidence for the utility of next-generation Web search results interfaces that promote interactive search results exploration.

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Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Topic models have been shown to be a useful way of representing the content of large document collections, for example, via visualization interfaces (topic browsers). These systems enable users to explore collections by way of latent topics. A standard way to represent a topic is using a term list; that is the top-n words with highest conditional probability within the topic. Other topic representations such as textual and image labels also have been proposed. However, there has been no comparison of these alternative representations. In this article, we compare 3 different topic representations in a document retrieval task. Participants were asked to retrieve relevant documents based on predefined queries within a fixed time limit, presenting topics in one of the following modalities: (a) lists of terms, (b) textual phrase labels, and (c) image labels. Results show that textual labels are easier for users to interpret than are term lists and image labels. Moreover, the precision of retrieved documents for textual and image labels is comparable to the precision achieved by representing topics using term lists, demonstrating that labeling methods are an effective alternative topic representation.

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Theme

Semantisches Umfeld in Indexierung u. Retrieval