1 / 31

Information seeking

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.

jariah
Télécharger la présentation

Information seeking

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. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

More Related