Desktop Search Engine Visualisation and Evaluation

Foo, Schubert; Hendry, Douglas

doi:10.1007/978-3-540-77094-7_47

Cited by 6 publications

(7 citation statements)

References 9 publications

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“…The evaluators liked the highlighting of the search terms in the file viewer and clear indication of the number of hits per result file, and suggested improvements related to more flexible sorting of the results and more document and result information to be made easily available. These results confirm that the basic de-sign and operation of the desktop search engine is effective and useful [11].…”

Section: Figure 2 List Viewsupporting

confidence: 75%

Visualization for Information Retrieval in Regional Distributed Environment

Salama

2013

IJEEI

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Nowadays, efficient information retrieval has become an important issue. Using information retrieval system backs more retrieval results, some of them more relevant than other, and some is not relevant. While using search engine to retrieve information has grown very substantially, there remain problems with the information retrieval systems. The interface of the systems does not help them to perceive the precision of these results. It is therefore not surprising that graphical visualizations have been employed in search engines to assist users. The main objective of Internet users is to find the required information with high efficiency and effectiveness. In this paper we present brief sides of information visualization's role in enhancing web information retrieval system as in some of its techniques such as tree view, title view, map view, bubble view and cloud view and its tools such as highlighting and Colored Query Result.

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Section: Figure 2 List Viewsupporting

confidence: 75%

Visualization for Information Retrieval in Regional Distributed Environment

Salama

2013

IJEEI

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“…RDF triples are used for conceptually describing web content and consist of subject, predicate and object. Foo et al [8] provide a desktop search engine containing six different visualisations (tree, graph view, bubble chart, tile chart and cloud view) for analysing the results. However, the provided interaction possibilities for search refinement within the visualisations are limited.…”

Section: Related Workmentioning

confidence: 99%

Knowminer Search - A Multi-visualisation Collaborative Approach to Search Result Analysis

Rauch

Klieber

Wozelka

et al. 2015

2015 19th International Conference on Information Visualisation

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The amount of information available on the internet and within enterprises has reached an incredible dimension. Efficiently finding and understanding information and thereby saving resources remains one of the major challenges in our daily work. Powerful text analysis methods, a scalable faceted retrieval engine and a well-designed interactive user interface are required to address the problem. Besides providing means for drilling-down to the relevant piece of information, a part of the challenge arises from the need of analysing and visualising data to discover relationships and correlations, gain an overview of data distributions and unveil trends. Visual interfaces leverage the enormous bandwidth of the human visual system to support pattern discovery in large amounts of data. Our Knowminer search builds upon the well-known faceted search approach which is extended with interactive visualisations allowing users to analyse different aspects of the result set. Additionally, our system provides functionality for organising interesting search results into portfolios, and also supports social features for rating and boosting search results and for sharing and annotating portfolios.

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“…Veerasamy and Heikes (1997)) designed a visualization that displayed the relevant documents and assisted users to effectively reformulate queries based on the searched keywords in the first stage. Foo and Hendry (2007) created and evaluated a suite of visualizations for searching one's desktop. Relevant results to the search keywords and filters were categorized by using different colors, shapes, etc.…”

Section: Visual Indication Of Search Relevance and Matched Abstractmentioning

confidence: 99%

VisArchive: a time and relevance based visual interface for searching, browsing, and exploring project archives

Staub‐French

Tory

et al. 2016

Vis. in Eng.

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Background: Project archives are becoming increasingly large and complex. On construction projects in particular, the increasing amount of information and the increasing complexity of its structure make searching and exploring information in the project archive challenging and time-consuming. Methods: This research investigates a query-driven approach that represents new forms of contextual information to help users understand the set of documents resulting from queries of construction project archives. Specifically, this research extends query-driven interface research by representing three types of contextual information: (1) the temporal context is represented in the form of a timeline to show when each document was created; (2) the search-relevance context shows exactly which of the entered keywords matched each document; and (3) the usage context shows which project participants have accessed or modified a file.

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Desktop Search Engine Visualisation and Evaluation

Cited by 6 publications

References 9 publications

Visualization for Information Retrieval in Regional Distributed Environment

Visualization for Information Retrieval in Regional Distributed Environment

Knowminer Search - A Multi-visualisation Collaborative Approach to Search Result Analysis

VisArchive: a time and relevance based visual interface for searching, browsing, and exploring project archives

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