Jane Reid, AMSc IRIC, QMUL, 30/10/01 1 Information seeking Information-seeking models Search...

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

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Information seeking

• Information-seeking models

• Search strategies

• Search tactics


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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


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User-centred IS models

• Description of IS stages / processes

• May aid construction of supportive interface

• Examples– Simple IS model– Kuhlthau’s ISP model


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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


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Limitations of simple IS model

• Not appropriate for browsing systems

• Assumption of static information need

• Overwhelming emphasis on search itself


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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)


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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


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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


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ISP model [4]

• Problem solving– Collection

• Specification of need for relevant, focussed information

– Presentation• Completion of search and usage of results


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Limitations of ISP model

• Not intended for browsing– Model has been partially validated for

hypertext environment by another researcher

• Highly idealised

• Sequential (no iteration)


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System-centred IS models

• Description of desirable system functions

• Aid in construction of intelligent systems

• Example– Belkin’s MONSTRAT model


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MONSTRAT model [1]

• Based on cognitive model of IR interaction

• Models– System characteristics– User characteristics– Problem characteristics

• Ten functions which correspond to system modules


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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


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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


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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


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Other IS models [1]

• Bates’ berry-picking model– Suitable for browsing– Information needs are dynamic– Knowledge is gathered throughout process– Implications for interface design


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Other IS models [2]

• Reid’s task-oriented model– Model the broader IS context

• Work task

• Contextual factors

• Social factors


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Other IS models [3]

task

performance

feedback

task performe r

task setter

task

requirements

task

performance

assessment

task

representation

task outcome

task model

information

need

IR

process

external

context


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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


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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


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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


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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)


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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


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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


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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


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• 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


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• Block / negate– Reject items containing, or indexed by, certain

terms

• Neighbour– Add additional “neighbouring” terms from

current document


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• Trace– Examine documents already retrieved for new

terms

• Fix– Try alternative affixes


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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


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Idea tactics [2]

• Limit– Limit the search

• Specify constraints, e.g. for language, data set, publication year, etc


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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 1 Information seeking Information-seeking models Search...

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