Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Tag Clouds: Data Analysis Tool or Social Signaller?
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Introduction to Information Retrieval
Introduction to Information Retrieval
Music information retrieval using social tags and audio
IEEE Transactions on Multimedia - Special section on communities and media computing
Number of people required for usability evaluation: the 10±2 rule
Communications of the ACM
Assessment of the utility of tag clouds for faster image retrieval
Proceedings of the international conference on Multimedia information retrieval
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UI-HCII'07 Proceedings of the 2nd international conference on Usability and internationalization
Interactive information retrieval
Annual Review of Information Science and Technology
Methodological Review: Formal representation of eligibility criteria: A literature review
Journal of Biomedical Informatics
Selectively diversifying web search results
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A practical method for transforming free-text eligibility criteria into computable criteria
Journal of Biomedical Informatics
Tag clouds for displaying semantics: the case of filmscripts
Information Visualization
On the role of novelty for search result diversification
Information Retrieval
Journal of Biomedical Informatics
Journal of Web Engineering
Unsupervised mining of frequent tags for clinical eligibility text indexing
Journal of Biomedical Informatics
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Objective: Information overload is a significant problem facing online clinical trial searchers. We present eTACTS, a novel interactive retrieval framework using common eligibility tags to dynamically filter clinical trial search results. Materials and methods: eTACTS mines frequent eligibility tags from free-text clinical trial eligibility criteria and uses these tags for trial indexing. After an initial search, eTACTS presents to the user a tag cloud representing the current results. When the user selects a tag, eTACTS retains only those trials containing that tag in their eligibility criteria and generates a new cloud based on tag frequency and co-occurrences in the remaining trials. The user can then select a new tag or unselect a previous tag. The process iterates until a manageable number of trials is returned. We evaluated eTACTS in terms of filtering efficiency, diversity of the search results, and user eligibility to the filtered trials using both qualitative and quantitative methods. Results: eTACTS (1) rapidly reduced search results from over a thousand trials to ten; (2) highlighted trials that are generally not top-ranked by conventional search engines; and (3) retrieved a greater number of suitable trials than existing search engines. Discussion: eTACTS enables intuitive clinical trial searches by indexing eligibility criteria with effective tags. User evaluation was limited to one case study and a small group of evaluators due to the long duration of the experiment. Although a larger-scale evaluation could be conducted, this feasibility study demonstrated significant advantages of eTACTS over existing clinical trial search engines. Conclusion: A dynamic eligibility tag cloud can potentially enhance state-of-the-art clinical trial search engines by allowing intuitive and efficient filtering of the search result space.