Jane Reid, AMSc IRIC, QMUL, 13/11/01 1 IR interfaces Purpose: to support users in information-seeking tasks Issues: –Functionality –Usability Motivations for interface design: –General interface design principles –Visualisation –Need to provide support for information-seeking process itself

Jane Reid, AMSc IRIC, QMUL, 13/11/01 2 Interface design principles Particularly relevant to IR interfaces: –Reduce working memory load –Informative feedback –Internal locus of control –Alternative interfaces for expert/novice users –Easy reversal of actions [Schneiderman]

Jane Reid, AMSc IRIC, QMUL, 13/11/01 3 Visualisation [1] Visual representation of large information spaces 2D / 3D representations Difficulty representing: –Abstract ideas –Textual information Techniques: –Graphical E.g. icons, colour highlighting –Brushing and linking Connection of 2 or more views of the same data

Jane Reid, AMSc IRIC, QMUL, 13/11/01 4 Visualisation [2] –Panning and zooming Scanning sideways and focussing in / out –Focus-plus-context Makes focus area larger and shrinks surrounding objects, e.g. fisheye view –Magic lenses Use of a transparent overlaid window which transforms the underlying data –Animation

Jane Reid, AMSc IRIC, QMUL, 13/11/01 5 Support for information-seeking process Interface must support: –Starting-point –Query specification –Presentation of results –Relevance feedback –IS process as a whole

Jane Reid, AMSc IRIC, QMUL, 13/11/01 6 Starting-point Lists Overviews Examples Automated source selection

Jane Reid, AMSc IRIC, QMUL, 13/11/01 7 Lists User chooses from list of collection names to search No other collection information, so: –Efficient for: Frequent searchers Domain experts –Not efficient for: Infrequent searchers Domain novices

Jane Reid, AMSc IRIC, QMUL, 13/11/01 8 Overviews Overview of topic domains of collections Used in combination with navigation Three main types: –Category hierarchies –Automatic collection overviews –Co-citation clustering

Jane Reid, AMSc IRIC, QMUL, 13/11/01 9 Category hierarchies Structured overview of topic categories Uses manually assigned category labels Provides logical high-level starting-point Disadvantages: –Category contents not always intuitive –Difficult to combine categories and queries E.g. Yahoo! directory

Jane Reid, AMSc IRIC, QMUL, 13/11/01 10 Automatic collection overviews Usually based on unsupervised clustering Combination with searching facility is most effective Often used with graphical display to support browsing Disadvantages: –Differences in cohesion of categories –Graphical display: Is difficult for non-expert users Does not support focussed search well E.g. Scatter/Gather

Jane Reid, AMSc IRIC, QMUL, 13/11/01 11 Co-citation clustering Clustering by citation analysis: –Pairing of documents which Both cite the same article Are both cited by the same article –Documents clustered on the basis of co-citation similarity Identifies dominant themes in the collection Disadvantages: –Differences in cohesion of categories

Jane Reid, AMSc IRIC, QMUL, 13/11/01 12 Examples [1] Initial example provided by the system Retrieval by reformulation Methods of choosing initial examples: –Template provided and partially completed -> partial matching –Case-based reasoning, according to general interests Dialogue systems –System-user question-answer

Jane Reid, AMSc IRIC, QMUL, 13/11/01 13 Examples [2] Wizards: –Step-by-step short-cuts for certain tasks –Useful for: Multi-step, fixed-sequence tasks Users lacking domain knowledge Possible future strategy: guided tour (static or dynamic)

Jane Reid, AMSc IRIC, QMUL, 13/11/01 14 Automated source selection User modelling systems Intelligent tutoring systems Matching on the basis of: –Query / user profile –Query / contents of information sources Alternative strategy: data fusion

Jane Reid, AMSc IRIC, QMUL, 13/11/01 15 Query specification For different functionality: –Boolean queries –Free-text queries –Non-textual For different interface styles: –Command line –Forms / menus –Graphical

Jane Reid, AMSc IRIC, QMUL, 13/11/01 16 Boolean queries [1] Boolean queries problematic because: –Basic syntax is not intuitive –Size of results set often unsuitable or unworkable –Documents are not ranked Solutions: –Alternative, simpler syntax –Faceted queries: Query divided into facets, which are treated as separate queries Results sets combined Facets can be weighted to reflect importance

Jane Reid, AMSc IRIC, QMUL, 13/11/01 17 Boolean queries [2] –Post-coordinate ranking Documents ranked by proportion of query terms contained within them –Meta-data ranking Documents ranked by meta-data, e.g. date order, author name

Jane Reid, AMSc IRIC, QMUL, 13/11/01 18 Free-text queries [1] Natural language is a more intuitive method of query specification Generally treated as a “bag” of words Statistical ranking used Disadvantages: –Less feedback about occurrence of terms in the results –Less control over the results

Jane Reid, AMSc IRIC, QMUL, 13/11/01 19 Free-text queries [2] Variations: –Use of “mandatory” terms –Use of phrases and term proximity –Extraction of concepts –Use of natural language syntax e.g. if a person, date, place is required –Question-answering systems: FAQ systems Question template systems

Jane Reid, AMSc IRIC, QMUL, 13/11/01 20 Forms / menus Command and attribute information provided Recognition instead of recall Easier for non-expert and infrequent users

Jane Reid, AMSc IRIC, QMUL, 13/11/01 21 Graphical interfaces Often faster and more accurate for users Provides direct manipulation: –Continuous representation of current object –Physical actions –Rapid incremental reversible operations Examples: –Venn diagrams –Filter-flow model (DB queries only) –Query preview Possible future strategy: magic lenses

Jane Reid, AMSc IRIC, QMUL, 13/11/01 22 Presentation of results [1] Document surrogates used Show context for current document set: –Query terms within document: Highlight query term occurrences System scrolls to first query term occurrence –Query terms between documents Overview of retrieved documents organised by subset of query terms contained within them –Context via table of contents Context organised into TOC with sections

Jane Reid, AMSc IRIC, QMUL, 13/11/01 23 Presentation of results [2] –Categories for results set context Documents put into relevant meta-data categories –Hyperlinks to organise retrieval results Manually vs automatically generated –Tables Positioning documents in table arranged according to 2 or more variables

Jane Reid, AMSc IRIC, QMUL, 13/11/01 24 Relevance feedback [1] Method of query reformulation Different functionality: –Standard relevance feedback (automatic) Binary / scalar / negative –Interactive relevance feedback Possible query expansion terms offered to user –Pseudo-relevance feedback Query expansion terms extracted from top-ranked documents

Jane Reid, AMSc IRIC, QMUL, 13/11/01 25 Relevance feedback [2] Recommender systems: –Machine learning techniques –Implicit / explicit user input –Building up / modifying user profile Social recommendation systems: –Similarity between different users’ queries and relevance judgements exploited in order to identify other potential matches –Effective for “taste” activities, e.g. music, films

Jane Reid, AMSc IRIC, QMUL, 13/11/01 26 IS process as a whole [1] Layout of information on the screen Window management: –Content –Layout: Monolithic Overlapping Elastic windows Tiled Virtual workspaces

Jane Reid, AMSc IRIC, QMUL, 13/11/01 27 IS process as a whole [2] Search history Integration of: –Scanning –Selection –Querying

Jane Reid, AMSc IRIC, QMUL, 13/11/01 28 Summary Purpose of IR interfaces: to support users in information- seeking tasks IR interface design deals with issues of: –Functionality –Usability IR interface design takes account of: –General interface design principles –Visualisation principles and techniques –Stages of the information-seeking process