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– Comprehension– Contextual displays

Evaluating Retrieval ResultsSelecting 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 SurrogatesResulting 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.

Example Surrogates

Ranked List

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

Popout Prism

Popout Prism

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.

TileBars

SeeSoftVisualization 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

SeeSoft

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

InfoCrystal

VIBE

SuperbookUses 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 can

be inferred– Categories can

be chosen basedon query type(DynaCat)

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

Cha-Cha

Mapuccino

Table Views for Retrieval Results

Category and link views present only one type of interdocument relation

Documents have many different potential relationsTabular 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 valuesExamples

– Envision– TableLens

Envision

TableLens

SummaryUsers 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)