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Interfaces for Retrieval Results. Information Retrieval Activities. Selecting a collection Talked about last class Lists, overviews, wizards, automatic selection Submitting a request Balancing expressiveness and usability Command line, graphical, and NL interfaces Examining the response
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Information Retrieval Activities • Selecting a collection • Talked about last class • Lists, overviews, wizards, automatic selection • Submitting a request • Balancing expressiveness and usability • Command line, graphical, and NL interfaces • Examining the response • Comprehension • Contextual displays
Evaluating Retrieval Results • Selecting among returned documents • Requires partial understanding of documents without looking at whole document • To provide understanding of documents: • Show relations to query terms • Show in collection overviews • Provide descriptive metadata • Indicate document structure • Indicate the hyperlink structure • Indicate relations between returned documents
Document Surrogates • Resulting documents are presented by partial information about document • Important metadata (title, date, source) • Selected chunks of document • Thumbnail images of documents • Some systems provide short and long document surrogates. • Normally, clicking on a surrogate causes the document to be displayed.
Document Relation to Query • Simple ways to indicate relation: • Select snippet with query terms • Highlight query terms in document display (thumbnail or whole) • Scroll to first occurrence of query term
Keyword in Context (KWIC) • KWIC document surrogates • Phrases and sentences with query terms are extracted • These snippets are presented along with metadata • Design issues • Deciding how many and which occurrences of keywords to show • Use query term weights, if any • Evidence indicates selecting text segments with largest number of query terms that appear near beginning of document
TileBars • TileBars is a compact visualization of documents’ relation to query terms. • Document surrogate is a rectangular bar divided into a matrix/table • Rows correspond to query facets • Columns are sections of document • Darkness in each row/column position indicates the occurrence of that facet in that portion of the document.
SeeSoft • Visualization where each line of document is visualized as line in graphical column • Color indicates characteristics of the line. • Originally developed to help understand program code • Applied to document analysis and text retrieval
Relative Query Term Relations • Prior set of systems present individual documents and their relation to query terms • To present a larger number of results • Visually represent sets of documents • Indicate sets’ relations to query terms • Examples • InfoCrystal • VIBE
Superbook • Uses a table of contents to indicate where query terms appear • Requires document structure
Categories for Retrieval Results • Present results in groups based on some categorization • Categories can be based on metadata • Categories canbe inferred • Categories canbe chosen basedon query type(DynaCat)
Hyperlinks for Retrieval Results • Present navigational links between retrieved documents • Relies on links between documents • Most often used for searching a single web site (or similar repository) • Examples • Cha-Cha • Mapuccino
Table Views for Retrieval Results • Category and link views present only one type of interdocument relation • Documents have many different potential relations • Tabular views can provide an overview of a set of relations • Each row is a document • Each column is an attribute (metadata field or other) • Content of table indicates values and relations between values • Examples • Envision • TableLens
Summary • Users must partly understand retrieval results to select which to view. • Techniques: • Highlighting and scrolling indications of relations to search terms (snippets, Google cache, Popout Prism) • Set-based views in relation to search terms (InfoCrystal, VIBE) • Visualization of search terms in sections (TileBars, SeeSoft, SuperBook) • Categorization of results (DynaCat, clusty.com) • Hyperlinks between results (Cha-Cha, Mapuccino) • Table views of results (Envision, TableLens)
