15,289 research outputs found

    Slicing and dicing the information space using local contexts

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    In recent years there has been growing interest in faceted grouping of documents for Interactive Information Retrieval (IIR). It is suggested that faceted grouping can offer a flexible way of browsing a collection compared to clustering. However, the success of faceted grouping seems to rely on sufficient knowledge of collection structure. In this paper we propose an approach based on the local contexts of query terms, which is inspired by the interaction of faceted search and browsing. The use of local contexts is appealing since it requires less knowledge of the collection than existing approaches. A task-based user study was carried out to investigate the effectiveness of our interface in varied complexity. The results suggest that the local contexts can be exploited as the source of search result browsing in IIR, and that our interface appears to facilitate different aspects of search process over the task complexity. The implication of the evaluation methodology using high complexity tasks is also discussed

    ImageSieve: Exploratory search of museum archives with named entity-based faceted browsing

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    Over the last few years, faceted search emerged as an attractive alternative to the traditional "text box" search and has become one of the standard ways of interaction on many e-commerce sites. However, these applications of faceted search are limited to domains where the objects of interests have already been classified along several independent dimensions, such as price, year, or brand. While automatic approaches to generate faceted search interfaces were proposed, it is not yet clear to what extent the automatically-produced interfaces will be useful to real users, and whether their quality can match or surpass their manually-produced predecessors. The goal of this paper is to introduce an exploratory search interface called ImageSieve, which shares many features with traditional faceted browsing, but can function without the use of traditional faceted metadata. ImageSieve uses automatically extracted and classified named entities, which play important roles in many domains (such as news collections, image archives, etc.). We describe one specific application of ImageSieve for image search. Here, named entities extracted from the descriptions of the retrieved images are used to organize a faceted browsing interface, which then helps users to make sense of and further explore the retrieved images. The results of a user study of ImageSieve demonstrate that a faceted search system based on named entities can help users explore large collections and find relevant information more effectively

    EGO: a personalised multimedia management tool

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    The problems of Content-Based Image Retrieval (CBIR) sys- tems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces, and introduce our view on how to solve some of the problems of the studied interfaces. To address the semantic gap and long-term multifaceted information needs, we propose a "retrieval in context" system. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user's personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is detailed, which is based on relevance feedback techniques

    Which user interaction for cross-language information retrieval? Design issues and reflections

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    A novel and complex form of information access is cross-language information retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. The authors present three user evaluations undertaken during the iterative design of Clarity, a cross-language retrieval system for low-density languages, and shows how the user-interaction design evolved depending on the results of usability tests. The first test was instrumental to identify weaknesses in both functionalities and interface; the second was run to determine if query translation should be shown or not; the final was a global assessment and focused on user satisfaction criteria. Lessons were learned at every stage of the process leading to a much more informed view of what a cross-language retrieval system should offer to users

    Evaluating a workspace's usefulness for image retrieval

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    Image searching is a creative process. We have proposed a novel image retrieval system that supports creative search sessions by allowing the user to organise their search results on a workspace. The workspace’s usefulness is evaluated in a task-oriented and user-centred comparative experiment, involving design professionals and several types of realistic search tasks. In particular, we focus on its effect on task conceptualisation and query formulation. A traditional relevance feedback system serves as a baseline. The results of this study show that the workspace is more useful in terms of both of the above aspects and that the proposed approach leads to a more effective and enjoyable search experience. This paper also highlights the influence of tasks on the users’ search and organisation strategy

    From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

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    A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

    An adaptive technique for content-based image retrieval

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    We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs—a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search

    Is query translation a distinct task from search?

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    INTRODUCTION The University of Sheffield participated in iCLEF 2002 using, as a test-bed, the prototype under development in the Clarity project. Clarity is an EU funded project aimed at developing a system for cross-language information retrieval for so-called low density languages, those with few translation resources. Currently translation between English and Finnish is supported; soon Swedish will be added and in the near future Latvian and Lithuanian. Clarity is being developed in a user-centred way with user involvement from the beginning. The design of the first user interface was based on current best practise, particular attention was paid to empirical evidence for a specific design choice. Six paper-based interface mock-ups representing important points in the cross-language search task were generated and presented for user assessment as a part of an extensive user study. The study (reported in Petrelli et al. 2002) was conducted to understand users and uses of cross-language information retrieval systems. Many different techniques were applied: contextual enquiry, interviews, questionnaires, informal evaluation of existing cross-language technology, and participatory design sessions with the interface mock-ups mentioned above. As a result, a user class profile was sketched and a long list of user requirements was compiled. As a followup, a redesign session took place and the new system was designed for users whoknow the language(s) they are searching (polyglots); • search for writing (journalists, translators business analysts); • have limited searching skills; • know the topic in advance or will learn/read on it while searching; • use many languages in the same search session and often swap between them. New system features were listed as important and the user interface was redesigned. Considering the result of the study the new interface allowed the user to dynamically change the language setting from query to query, hid the query translation and showed the retrieved set as ranked list primary. Despite the fact that this new design was considered to be more effective, a comparison between the first layout based on the relevant literature and the new one based on the user study was considered an important research question. In particular, the choice of hiding the query translation was considered an important design decision, against the common agreement to allow and support the user in controlling the system actions. Thus the participation of Sheffield in iCLEF was organized around the idea of checking if the user should validate the query translation before the search is run or instead if the system should perform the translation and search in a single step without any user’s supervision
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