Searching Fast and Slow

Knowledge workers (e.g. healthcare information professionals, legal researchers, librarians) need to create and execute search strategies that are comprehensive, transparent, and reproducible. The traditional solution (command-line query builders offered by proprietary database vendors) dates from the days when users could access databases only via text-based terminals and command-line syntax. This article presents a new approach in which users express concepts as objects on a visual canvas and manipulate them to articulate relationships. This offers a more intuitive user experience (UX) that eliminates many sources of error, makes the query semantics more transparent, and offers new ways to collaborate, share, and optimise search strategies and best practices.

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The Enterprise Search User Experience

While research shows that different types of searchers interact differently with search applications, vendors are unlikely to offer an interface that is optimised for specific tasks or customisable by the user. Examples of how the user experience can be improved include ensuring results are presented for ease of scanning and reviewing and providing a well structured and presented snippet. Vendors that focus on customisable interfaces will find it easier to differentiate their products in the marketplace.

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The Art and Craft of Search Auto-Suggest

Search auto-suggest -- the drop-down menu of suggestions displayed while typing into a search box -- is the first and often the only search interaction that users encounter. The goal of auto-suggest is to show users possibilities related to their typing, and provide them dynamic context information about what is available. This article explores creating auto-suggest indexes, matching, retrieval and ranking, handling zero matches, and user interface options, with considerations and trade-offs for various approaches.

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