jane reid, amsc iric, qmul, 13/11/01 1 ir interfaces purpose: to support users in...
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Jane Reid, AMSc IRIC, QMUL, 13/11/01
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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
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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
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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
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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
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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
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Starting-point
• Lists
• Overviews
• Examples
• Automated source selection
Jane Reid, AMSc IRIC, QMUL, 13/11/01
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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IS process as a whole [2]
• Search history
• Integration of:– Scanning
– Selection
– Querying
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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