information seeking behavior prof. marti hearst sims 202, lecture 25

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Information Seeking Information Seeking Behavior Behavior Prof. Marti Hearst Prof. Marti Hearst SIMS 202, Lecture 25 SIMS 202, Lecture 25

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Page 1: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Information Seeking BehaviorInformation Seeking Behavior

Prof. Marti HearstProf. Marti Hearst

SIMS 202, Lecture 25SIMS 202, Lecture 25

Page 2: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

TodayToday

Information Seeking BehaviorInformation Seeking Behavior Combine tactics into strategies Two parts of a process:

search and retrieval analysis and synthesis of search results

This is a fuzzy area; we will look at This is a fuzzy area; we will look at several different working theories.several different working theories.

Page 3: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Finding Out AboutFinding Out About

Three phases:Three phases: Asking of a question Construction of an answer Assessment of the answer

Part of an iterative processPart of an iterative process ExamineExamine tactics tactics and and strategiesstrategies for for

each phaseeach phase

Page 4: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Tactics vs. StrategiesTactics vs. Strategies

Tactic: short term goals and Tactic: short term goals and maneuversmaneuvers operators, actions

Strategy: overall planningStrategy: overall planning link a sequence of operators together

to achieve some end

Page 5: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Lexis-Nexis InterfaceLexis-Nexis Interface

What tactics did you use?What tactics did you use? What strategies did you use?What strategies did you use?

Page 6: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Search Tactics and Search Tactics and StrategiesStrategies

Search TacticsSearch Tactics Bates 79

Search StrategiesSearch Strategies Belkin et al. 93, 94 Bates 90 O’Day and Jeffries 93

Page 7: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Information Search Tactics Information Search Tactics (after Bates 79)(after Bates 79)

Monitoring tacticsMonitoring tactics keep search on track

Source-level tacticsSource-level tactics navigate to and within sources

Term and Search Formulation tacticsTerm and Search Formulation tactics designing search forumulation selection and revision of specific terms

within search formulation

Page 8: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Term TacticsTerm Tactics

Move around the thesaurusMove around the thesaurus superordinate, subordinate, coordinate neighbor (semantic or alphabetic) trace -- pull out terms from information

already seen as part of search (titles, etc) morphological and other spelling variants antonyms (contrary)

Page 9: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Search Formulation TacticsSearch Formulation Tactics

Include or exclude termsInclude or exclude terms Boolean focus queriesBoolean focus queries

Page 10: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Source-level TacticsSource-level Tactics ““Bibble”:Bibble”:

look for a pre-defined result set e.g., a good link page on web

Survey:Survey: look ahead, review available options e.g., don’t simply use the first term or first

source that comes to mind Cut:Cut:

eliminate large proportion of search domain e.g., search on rarest term first

Page 11: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Source-level Tactics (cont.)Source-level Tactics (cont.)

StretchStretch use source in unintended way e.g., use patents to find addresses

ScaffoldScaffold take an indirect route to goal e.g., when looking for references to obscure

poet, look up contemporaries CleaveCleave

binary search in an ordered file

Page 12: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Monitoring TacticsMonitoring Tactics(strategy-level)(strategy-level) CheckCheck

compare original goal with current state WeighWeigh

make a cost/benefit analysis of current or anticipated actions

PatternPattern recognize common strategies

Correct ErrorsCorrect Errors RecordRecord

keep track of (incomplete) paths

Page 13: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Additional ConsiderationsAdditional Considerations(Bates 79)(Bates 79)

Add a Sort tactic!Add a Sort tactic! More detail is needed about short-term More detail is needed about short-term

cost/benefit decision rule strategiescost/benefit decision rule strategies When to stop?When to stop?

How to judge when enough information has been gathered?

How to decide when to give up an unsuccesful search?

When to stop searching in one source and move to another?

Page 14: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Information Seeking Information Seeking Strategies Strategies (Belkin et al. 93, 94)(Belkin et al. 93, 94)

A multi-dimensional space:A multi-dimensional space: very simple tactic types very simple goal types information vs. meta-information

Create a strategy type by choosing Create a strategy type by choosing a value from each dimensiona value from each dimension

Page 15: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

ISS DimensionsISS Dimensions

Goal of interactionGoal of interaction learning (browsing to get to know an area) selection (identifying useful items)

Method of interactionMethod of interaction scanning (looking for something interesting) searching (looking for a specific known item)

Resource typeResource type information meta-information

Page 16: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Information Seeking Information Seeking StrategiesStrategies(Modified from Belkin et al. 93)(Modified from Belkin et al. 93)

ISS Scan Search Learn Select Info Meta-Info

A X X XB X X XC X X XD X X XE X X XF X X XG X X XH X X X

Page 17: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Example ISS’sExample ISS’s

ISS G: prototypical specific searchISS G: prototypical specific search search through a specific information

source retrieve articles that match a keyword

specification of the topic

Page 18: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Example ISS’sExample ISS’s

ISS B: prototypical undirected ISS B: prototypical undirected searchsearch user approaches system with some

vague idea about a topic scans through a meta-information

structure learns about general topic

information

Page 19: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Example ISS’sExample ISS’s

ISS D:ISS D: scan through a table-of-contents of a

journal to select items on a particular topic

ISS A: ISS A: scan through a periodicals shelf to

learn what journals are available on a given topic

Page 20: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

New strategy typesNew strategy types

What happens if we place Bates’ What happens if we place Bates’ tactic types into Belkin et al.’s tactic types into Belkin et al.’s strategy space?strategy space?

Page 21: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

““Berry-Picking” as an Berry-Picking” as an Information Seeking Strategy Information Seeking Strategy (Bates 90)(Bates 90) Standard IR modelStandard IR model

assumes the information need remains the same throughout the search process

Berry-picking modelBerry-picking model interesting information is scattered like

berries among bushes the query is continually shifting

Page 22: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Berry-picking model (cont.)Berry-picking model (cont.)

The query is continually shifting Users may move through a variety of

sources New information may yield new ideas and

new directions The query is not satisfied by a single, final

retrieved set, but rather by a series of selections and bits of information found along the way

Page 23: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

A sketch of a searcher… “moving through many A sketch of a searcher… “moving through many actions towards a general goal of satisfactory actions towards a general goal of satisfactory completion of research related to an information completion of research related to an information need.” (after Bates 90)need.” (after Bates 90)

Q0

Q1

Q2

Q3

Q4

Q5

Page 24: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

ImplicationsImplications

Interfaces should make it easy to Interfaces should make it easy to store intermediate resultsstore intermediate results

Interfaces should make it easy to Interfaces should make it easy to follow trails with unanticipated follow trails with unanticipated resultsresults

Difficulties with evaluationDifficulties with evaluation

Page 25: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Orienteering Orienteering (O’Day & Jeffries (O’Day & Jeffries 93)93)

Interconnected but diverse searches on a Interconnected but diverse searches on a single, problem-based themesingle, problem-based theme

Focus on Focus on information deliveryinformation delivery rather than rather than search performancesearch performance

Classifications resulting from an Classifications resulting from an extended observational study:extended observational study: 15 clients of professional intermediaries financial analyst, venture capitalist, product

marketing engineer, statistician, etc.

Page 26: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

OrienteeringOrienteering (O’Day & Jeffries (O’Day & Jeffries 93)93)

Defined three main search typesDefined three main search types monitoring

a well-known topic over time e.g., research four competitors every quarter

following a plan a typical approach to the task at hand e.g., improve business process X

exploratory explore topic in an undirected fashion get to know an unfamiliar industry

Page 27: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Orienteering Orienteering (O’Day & Jeffries 93)(O’Day & Jeffries 93)

Trends:Trends: A series of interconnected but diverse

searches on one problem-based theme This happened in all three search modes Each analyst did at least two search types

Each stage followed by reading, Each stage followed by reading, assimilation, and analysis of resulting assimilation, and analysis of resulting materialmaterial

Page 28: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Orienteering Orienteering (O’Day & Jeffries 93)(O’Day & Jeffries 93)

**Searches tended to trigger new directionsSearches tended to trigger new directions Overview, then detail, repeat Information need shifted between search

requests Context of problem and previous searches

were carried to next stage of search **The value was contained in the The value was contained in the accumulationaccumulation

of search results, not the final result setof search results, not the final result set **Observations verified Bates’ predictionsObservations verified Bates’ predictions

Page 29: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Orienteering Orienteering (O’Day & Jeffries 93)(O’Day & Jeffries 93)

Triggers: motivation to switch from one Triggers: motivation to switch from one strategy to anotherstrategy to another next logical step in a plan encountering something interesting explaining change finding missing pieces

Page 30: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Stop Conditions Stop Conditions (O’Day & Jeffries (O’Day & Jeffries 93)93)

Categories not as clear as for triggersCategories not as clear as for triggers People stopped searching whenPeople stopped searching when

no more compelling triggers finished an appropriate amount of searching for the

task specific inhibiting factor

e.g., learning market was too small lack of increasing returns

80/20 rule

Missing information/inferences okMissing information/inferences ok business world different than scholarship

Page 31: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

After the Search:After the Search:

Analyzing and Synthesizing ResultsAnalyzing and Synthesizing Results Orienteering Study Sensemaking Work

Page 32: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Analyzing and Synthesizing Analyzing and Synthesizing Search ResultsSearch Results Orienteering Post-Search Behaviors:Orienteering Post-Search Behaviors:

Read and Annotate Analyze

six main types 80% fell into six main types the rest:

cross-referencecross-reference summarizesummarize find evocative visualizationsfind evocative visualizations miscellaneousmiscellaneous

Page 33: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Post-Search Analysis Types Post-Search Analysis Types (O’Day & Jeffries 93)(O’Day & Jeffries 93)

TrendsTrends ComparisonsComparisons Aggregation and ScalingAggregation and Scaling Identifying a Critical SubsetIdentifying a Critical Subset AssessingAssessing InterpretingInterpreting

Page 34: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

SenseMaking SenseMaking (Russell et al. 93)(Russell et al. 93)

The process of The process of encodingencoding retrieved retrieved information to answer task-specific information to answer task-specific questionsquestions

CombineCombine internal cognitive resources external retrieved resources

Create a good representationCreate a good representation an iterative process contend with a cost/benefit tradoff

Page 35: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

““Sensemaking” in the Sensemaking” in the Business Intelligence Business Intelligence Analysis Task Analysis Task (Russell et al. 93)(Russell et al. 93)

Established analysisscheme

Select importantdocuments

Collect documents

Organize documentsby topic

For each topic,instantiate schema

Collect additionalrequired documents

Write report

Evaluate responsesto report

Generate final report

Page 36: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Sensemaking Sensemaking (Russell et al. 93)(Russell et al. 93)

An An anytime anytime activityactivity at any point a workable solution

available usually more time -> better solution usually more properties -> better

solution

Page 37: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Sensemaking Sensemaking (Russell et al. 93)(Russell et al. 93)

A A good strategygood strategy maximizes long term rate of gain example:

new technology brings more info faster uniform increase in useful and useless

information best strategy: throw out bad stuff faster

Page 38: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Sensemaking Sensemaking (Russell et al. 93)(Russell et al. 93)

Most of the effort is in synthesis of Most of the effort is in synthesis of a good representationa good representation covers the data increase usability decrease cost-of-use

Page 39: Information Seeking Behavior Prof. Marti Hearst SIMS 202, Lecture 25

Marti A. HearstSIMS 202, Fall 1997

Coming UpComing Up

User Interfaces for Information User Interfaces for Information AccessAccess

Using MetaData in SearchUsing MetaData in Search Hypertext Navigation and SearchHypertext Navigation and Search