information seeking l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Information seeking PowerPoint Presentation
Download Presentation
Information seeking

Loading in 2 Seconds...

play fullscreen
1 / 31

Information seeking - PowerPoint PPT Presentation


  • 154 Views
  • Uploaded on

Information seeking. Information-seeking models Search strategies Search tactics. Information-seeking (IS) models. Holistic view of IS process Possible types of IS model User-centred Descriptive Process-oriented System-centred Prescriptive Object-oriented Other.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Information seeking' - jariah


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
information seeking
Information seeking
  • Information-seeking models
  • Search strategies
  • Search tactics

Jane Reid, AMSc IRIC, QMUL, 30/10/01

information seeking is models
Information-seeking (IS) models
  • Holistic view of IS process
  • Possible types of IS model
    • User-centred
      • Descriptive
      • Process-oriented
    • System-centred
      • Prescriptive
      • Object-oriented
    • Other

Jane Reid, AMSc IRIC, QMUL, 30/10/01

user centred is models
User-centred IS models
  • Description of IS stages / processes
  • May aid construction of supportive interface
  • Examples
    • Simple IS model
    • Kuhlthau’s ISP model

Jane Reid, AMSc IRIC, QMUL, 30/10/01

simple is model
Simple IS model
  • Formulate information need
  • Identify information sources / channels
  • Search for information
    • Formulate and submit query
    • Examine and evaluate results of search
    • Iteration of search stages if necessary

Jane Reid, AMSc IRIC, QMUL, 30/10/01

limitations of simple is model
Limitations of simple IS model
  • Not appropriate for browsing systems
  • Assumption of static information need
  • Overwhelming emphasis on search itself

Jane Reid, AMSc IRIC, QMUL, 30/10/01

isp model 1
ISP model [1]
  • Intended as a search strategy teaching tool for expert intermediaries
  • Modelling of variations in user uncertainty
  • Dimensions
    • Affective (emotional)
    • Cognitive (thoughts)
    • Physical (actions)

Jane Reid, AMSc IRIC, QMUL, 30/10/01

isp model 2
ISP model [2]
  • Problem formulation
    • Initiation
      • Awareness of lack of knowledge and understanding
      • Attempt to understand task and relate it to prior knowledge
    • Selection
      • Identification and selection of topic to be investigated

Jane Reid, AMSc IRIC, QMUL, 30/10/01

isp model 3
ISP model [3]
  • Exploration
    • Investigation of information on general topic
  • Formulation
    • Formation of focussed perspective on the topic
    • Development of ability to identify relevant information

Jane Reid, AMSc IRIC, QMUL, 30/10/01

isp model 4
ISP model [4]
  • Problem solving
    • Collection
      • Specification of need for relevant, focussed information
    • Presentation
      • Completion of search and usage of results

Jane Reid, AMSc IRIC, QMUL, 30/10/01

limitations of isp model
Limitations of ISP model
  • Not intended for browsing
    • Model has been partially validated for hypertext environment by another researcher
  • Highly idealised
  • Sequential (no iteration)

Jane Reid, AMSc IRIC, QMUL, 30/10/01

system centred is models
System-centred IS models
  • Description of desirable system functions
  • Aid in construction of intelligent systems
  • Example
    • Belkin’s MONSTRAT model

Jane Reid, AMSc IRIC, QMUL, 30/10/01

monstrat model 1
MONSTRAT model [1]
  • Based on cognitive model of IR interaction
  • Models
    • System characteristics
    • User characteristics
    • Problem characteristics
  • Ten functions which correspond to system modules

Jane Reid, AMSc IRIC, QMUL, 30/10/01

monstrat model 2
MONSTRAT model [2]
  • Dialogue mode
    • Determine appropriate dialogue type for situation
  • Problem state
    • Determine role of user in problem treatment process
  • Problem mode
    • Determine appropriate system capability
  • User model
    • Generate description of user type, goals, beliefs

Jane Reid, AMSc IRIC, QMUL, 30/10/01

monstrat model 3
MONSTRAT model [3]
  • Problem description
    • Generate description of problem type, topic, structure, environment, etc
  • Retrieval strategy
    • Choose and apply appropriate retrieval strategies to knowledge resource
  • Response generator
    • Determine structure of response appropriate to user and situation

Jane Reid, AMSc IRIC, QMUL, 30/10/01

monstrat model 4
MONSTRAT model [4]
  • Input analyst
    • Convert input from user into structures usable by functional experts
  • Output generator
    • Convert response to form appropriate to user and situation
  • Explanation
    • Describe system operation, capabilities etc to user

Jane Reid, AMSc IRIC, QMUL, 30/10/01

other is models 1
Other IS models [1]
  • Bates’ berry-picking model
    • Suitable for browsing
    • Information needs are dynamic
    • Knowledge is gathered throughout process
    • Implications for interface design

Jane Reid, AMSc IRIC, QMUL, 30/10/01

other is models 2
Other IS models [2]
  • Reid’s task-oriented model
    • Model the broader IS context
      • Work task
      • Contextual factors
      • Social factors

Jane Reid, AMSc IRIC, QMUL, 30/10/01

other is models 3
Other IS models [3]

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search strategies
Search strategies
  • General strategies
    • Overall plan for the search session
    • Different strategies for different access types
      • Query-based
      • Hypermedia
  • Term selection strategies
  • Specific strategies
    • For individual collections, systems, thesauri, etc

Jane Reid, AMSc IRIC, QMUL, 30/10/01

query based strategies 1
Query-based strategies [1]
  • Starting strategies
    • Select
      • Break complex query into topics and deal with each topic separately
    • Exhaust
      • Include most elements of the query in the initial query formulation

Jane Reid, AMSc IRIC, QMUL, 30/10/01

query based strategies 2
Query-based strategies [2]
  • Continuation strategies
    • Building blocks
      • Combination of discrete topics
    • Pearl growing
      • Small relevant set expanded gradually
    • Successive fractions
      • Large relevant set refined gradually

Jane Reid, AMSc IRIC, QMUL, 30/10/01

hypermedia strategies
Hypermedia strategies
  • Strategies often used in combination
    • Scanning (information structure)
    • Browsing (casual, undirected exploration)
    • Selection (choice of individual elements)
    • Navigation (chain of scan and select operations)

Jane Reid, AMSc IRIC, QMUL, 30/10/01

term selection strategies
Term selection strategies
  • Strategies employed by expert searchers depend on:
    • Vocabulary - free-text vs controlled
    • Current state of search process
    • Number of documents retrieved
    • NLP functionality, e.g. use of proper names
  • Used as the basis of expert system rules for query reformulation

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search tactics
Search tactics
  • Individual actions taken at a search stage
  • Three possible steps
    • Term tactics
      • Choose a source of new terms, e.g. thesaurus, WordNet, terms from relevant documents
    • Search formulation tactics
      • Design or redesign the search formulation
    • Idea tactics
      • Provide ideas to change search direction

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search formulation tactics 1
Search formulation tactics [1]
  • Exhaust
    • Add components to the query
  • Reduce
    • Remove components from the query
  • Union
    • Specify union of 2 sets representing different query components

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search formulation tactics 2
Search formulation tactics [2]
  • Intersect
    • Specify intersection of 2 sets representing different query components
  • Parallel
    • Include synonyms or conceptually similar terms
  • Vary
    • Alter / substitute some of the search terms

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search formulation tactics 3
Search formulation tactics [3]
  • Block / negate
    • Reject items containing, or indexed by, certain terms
  • Neighbour
    • Add additional “neighbouring” terms from current document

Jane Reid, AMSc IRIC, QMUL, 30/10/01

search formulation tactics 4
Search formulation tactics [4]
  • Trace
    • Examine documents already retrieved for new terms
  • Fix
    • Try alternative affixes

Jane Reid, AMSc IRIC, QMUL, 30/10/01

idea tactics 1
Idea tactics [1]
  • Skip
    • Shift view of the query laterally
      • Shift focus from one part of a complex query to another
      • View the query from a different conceptual angle
  • Focus
    • Take a narrower perspective of the query
      • Choose a limited subset of the query terms
      • Fix on a limited conceptualisation of the query

Jane Reid, AMSc IRIC, QMUL, 30/10/01

idea tactics 2
Idea tactics [2]
  • Limit
    • Limit the search
      • Specify constraints, e.g. for language, data set, publication year, etc

Jane Reid, AMSc IRIC, QMUL, 30/10/01

summary
Summary
  • Information-seeking models
    • System-centred
    • User-centred
    • Other, e.g. task-oriented
  • Search strategies
    • Overall plan for the search session
  • Search tactics
    • Individual actions taken at a search stage

Jane Reid, AMSc IRIC, QMUL, 30/10/01