Information Retrieval in Context of Digital Libraries

- or DL in Context of IR

Peter IngwersenRoyal School of LIS

Denmark – pi@db.dkhttp://www.db.d/pi

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AgendaAgenda

Information RetrievalIn Context of Information BehaviorLaboratory Model = Digital Library

approach?Integrated Model – roles of context

The social perspective

Challenges in IR / DL according to model

Conclusions

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Information RetrievalInformation Retrieval

The processes involved in the representation, storage, searching, finding, filtering, presentation and use of information relevant to a requirement for information desired by a human user (The Turn, 2005)

Interaction – Time dimension

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Information behaviour and IRInformation behaviour and IRT. Wilson´s Onion Model, 1999 - extended:

Seeking

IRIR

Job-relatedWork TasksInterests

Non-job-relatedTasks and InterestsDaily-life behavior

Information behaviour

InteractiveIR

Behaviour

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Information behaviour … and other Information behaviour … and other central concepts in Information central concepts in Information

StudiesStudies Information behaviour:

to create information – e.g., on the Net - blogs; also human indexing, including social tagging;

to produce publications – e.g., as publisher

to communicate – face-to-face; chat; e-mail

to manage information sources – e.g. KM; selectivity

IB IB and other central and other central conceptsconcepts … …

Information seeking (behaviour) Information behaviour with interest for

Information Information need exist – even muddled or

exploratorySearching information sources – e.g.

colleagues Information Retrieval (I)IR

Searching information space via systems – Digital Library & Assets (interactive IR)

Retrieval models; relevance feedback & ranking; query modification; auto indexing and weighting;

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The Laboratory Model of IRThe Laboratory Model of IR(in the Cranfield-TREC Laboratory Research (in the Cranfield-TREC Laboratory Research

Framework)Framework)

Could just as well be a model for Digital Library development

Docu-ments

Represen-tation

Database

Searchrequest

Query

Matching

Represen-tation

QueryResult

QueryResult

PseudoRelevanceFeedback

The Lab IR Cave, with a VisitorThe Turn – Ingwersen & Järvelin, 2005

Docu-ments

Represen-tation

Database

Searchrequest

Query

Matching

Represen-tation

QueryResult

QueryResult

Context

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Simplistic model of (I)IRSimplistic model of (I)IR – – short-term short-term interaction – in contextinteraction – in context

Informationobjects

IT: EnginesLogics

Algorithms

InterfaceInformation

Seeker(s)

Org.

Cultural

RQuery

R = Request / Relevance feedback

Short-term IS&R & social interactionCognitive transformations and influence over time

Modification

Social

Interaction

Social Tagging

Recommender techniques

SocialContext

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Central Components of Interactive Central Components of Interactive IR – the basic IR – the basic Integrated Integrated

FrameworkFramework

Informationobjects

IT: EnginesLogics

Algorithms

InterfaceCognitiveActor(s)

(team)

Org.

Cultural

SocialContext

Informationobjects

IT: EnginesLogics

Algorithms

InterfaceCognitiveActor(s)

(team)

Org.

Cultural

SocialContext

The Lab./DL Framework In situ

recommendation

In situ tagging

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Integrated Framework and Relevance Integrated Framework and Relevance CriteriaCriteria

Docs

Repr

DB

Request

Query

Match

Repr

Result

A: Recall, precision, efficiency

B: Usability, Graded rel., CumGain; Quality of information/process

C: Quality work process/result; Graded R.

Work TaskSeeking Task

SeekingProcess

WorkProcess

Task Result

Seeking Result

EvaluationCriteria:

Work task context

Seeking context

IR context

Socio-organizational& cultural context

D: Socio-cognitive relevance; quality of work task result

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Moving into ContextMoving into ContextStrength:

Involvement of TASK (work/search) and …

Processes for fulfillment of task and …Task result / outcome

Seeking and retrieval tasks influenced by work tasks

Pointing to novel relevance measuresTask fulfillment measures; socio-

cognitive relevance; social utility (tagging, visits, downloads …)

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Challenges to IR/DLChallenges to IR/DL

“[If] we consider that unlike art IR is not there for its own sake … then IR is far, far more than a branch of computer science”

And what information and relevance means to IR, Tefko Saracevic states (1997, p. 17) …

“[In] broadest sense: Information is … that involves not only messages (first sense) that are cognitively processed (second sense), but also a context – a situation, task, problem-at-hand, the social horizon, … intentions …”

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Challenges to IR/DL – 2Challenges to IR/DL – 2

Understanding actors’ goals, tasks intentions – in diversity of contextsJob-related knowledge enquiries Daily-life information explorative behaviorsEntertainment - or simply ‘meaning making’

Inference of goals, tasks, intentions from implicit evidence from interaction behaviorImplicit relevance feedback study examples

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Challenges to IR/DL – 3Challenges to IR/DL – 3

Leading to finding out the best algorithmic models and solutions – not in themselves – but given understanding of characteristics of searcher goals, …

A lot of searching is undirected, vague, random, exploratory, muddled … (Skov, 2009)

A lot of tagging (and folksonomies) is randomly done - but can be filtered

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Challenges to IR/DL – 4Challenges to IR/DL – 4Belkin, Nick. Belkin, Nick. Sigir ForumSigir Forum, 42(1), 2008: 47-54, 42(1), 2008: 47-54

Recommender systems and personalization are relying on a narrow conception, applying vague correlations between a current searcher’s situation and previous Dwell time on page;Click-throughViewed, rated or saved objects by other

searchersSearch profiles’ contents

To tailor the rank of search results Or to find ‘things alike’ (probably better)

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Challenges to IR/DL – 5Challenges to IR/DL – 5

Which of the (personal) contextual features do we need to involve – incl. the IT context?

How to present retrieved and filtered documents?Zooming in/out – integrated searching of media &

document types: presentation form and relevance/usability:

Are interface issues solved by Google snippets and Microsoft’s detail-whole format?

Alternative (elaborated) evaluation methods for interaction design (IR/DL) are required

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The Circle of Systemic/Social Contexts in The Circle of Systemic/Social Contexts in interaction design: Digital Libraries & interaction design: Digital Libraries &

(I)IR – actor as centre(I)IR – actor as centre

Inter-face

CognitiveActor(s)

(team)

Org.

Cultural

SocialContext

Info.Objects

IT

Social Interactio

n

IR Interactio

n

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ConclusionsConclusions

IR and DL (or Digital Assets including museums and cultural heritage) face same challenges of addressing the Interactive nature of the information

processContexts – and their limitsEvaluation & research approachesNeed for combined efforts of IT and

behavior

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Thank You!