BasketLens: Searching for baskets of words in text collectionsDarya Filippova, Catherine Plaisant, Ben Shneiderman

OverviewBasketLens is an interface that allows users browse a document collection and search for preset baskets of words, revealing the distribution of those words in the collection.

University of Maryland, Human-Computer Interaction Lab www.cs.umd.edu/hcil

www.cs.umd.edu/hcil/textvis/basketlens

When searching for baskets of words, the table view has one column for each basket. Here comparing the use of terms for pain and pleasure (which in this example rarely overlap). Users can chose a different color for each basket.

The document view show multiple documents at once, sorted by the number or matches.

Users can create their own baskets, or use predefined baskets, e.g. baskets imported from Inquirer (www.wjh.harvard.edu/~inquirer/).

The list of words are saved in a simple text format so they can be easily edited and shared with other users.

Searching for words

Searching for baskets of words

Basket library

Revealing individual words of the baskets

Users can type lists of words and see which document contain those terms. The table view has one column per term. Each column contains the number of matches of this particular word in each document. Cells are color coded: the more matches the document had, the brighter the color of the cell.

Users can ungroup the baskets to reveal where individual words are used. Options allow users to see more compact views when the number of words becomes large.