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

Jane Reid, AMSc IRIC, QMUL, 30/10/01 2 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 3 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 4 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 5 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 6 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 7 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 8 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 9 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 10 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 11 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 12 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 13 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 14 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 15 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 16 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 17 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 18 Other IS models [3]

Jane Reid, AMSc IRIC, QMUL, 30/10/01 19 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 20 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 21 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 22 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 23 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 24 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 25 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 26 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 27 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 28 Search formulation tactics [4] Trace –Examine documents already retrieved for new terms Fix –Try alternative affixes

Jane Reid, AMSc IRIC, QMUL, 30/10/01 29 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 30 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 31 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