Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow 2005 1 THEORETICAL ISSUES IN CONTEXT MODELLING Kalervo Järvelin

Slides:



Advertisements
Similar presentations
UCLA : GSE&IS : Department of Information StudiesJF : 276lec1.ppt : 5/2/2015 : 1 I N F S I N F O R M A T I O N R E T R I E V A L S Y S T E M S Week.
Advertisements

Understanding the Research Process
Post-Positivist Perspectives on Theory Development
Information Retrieval: Human-Computer Interfaces and Information Access Process.
 delivers evidence that a solution developed achieves the purpose for which it was designed.  The purpose of evaluation is to demonstrate the utility,
Search Engines and Information Retrieval
CAP 252 Lecture Topic: Requirement Analysis Class Exercise: Use Cases.
CULTURE AND GENDER IN PLAY. FINDINGS ABOUT PLAY Play serves as common features of children’s lives, it can be found in all themes of culture. Consequently,
Information Retrieval February 24, 2004
Information Retrieval in Practice
INFO 624 Week 3 Retrieval System Evaluation
Retrieval Evaluation. Brief Review Evaluation of implementations in computer science often is in terms of time and space complexity. With large document.
Information Retrieval: Human-Computer Interfaces and Information Access Process.
Statistical Methods in Computer Science Why? Ido Dagan.
Creating Architectural Descriptions. Outline Standardizing architectural descriptions: The IEEE has published, “Recommended Practice for Architectural.
Experimental Components for the Evaluation of Interactive Information Retrieval Systems Pia Borlund Dawn Filan 3/30/04 610:551.
Retrieval Evaluation. Introduction Evaluation of implementations in computer science often is in terms of time and space complexity. With large document.
Chapter 5: Information Retrieval and Web Search
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
(Business Research Methods)
Research method2 Dr Majed El- Farra 1 Research methods Second meeting.
Research Methods in Nursing. Examining History 1600’s is the age of reasoning; finding reason and experimenting what is observed. Isaac Newton is a pioneer.
Alexandra Savelieva, Sergey Avdoshin, PhD National Research University “Higher School of Economics” Alexandra Savelieva, Sergey Avdoshin, PhD National.
Ciarán O’Leary Wednesday, 23 rd September Ciarán O’Leary School of Computing, Dublin Institute of Technology, Kevin St Research Interests Distributed.
Search Engines and Information Retrieval Chapter 1.
The context of the interface Ian Ruthven University of Strathclyde.
The Cognitive Perspective in Information Science Research Anthony Hughes Kristina Spurgin.
Philosophy of IR Evaluation Ellen Voorhees. NIST Evaluation: How well does system meet information need? System evaluation: how good are document rankings?
User-Oriented IR Models 571- Information Access and Retrieval.
B 203: Qualitative Research Techniques Interpretivism Symbolic Interaction Hermeneutics.
Big Idea 1: The Practice of Science Description A: Scientific inquiry is a multifaceted activity; the processes of science include the formulation of scientifically.
A Simple Unsupervised Query Categorizer for Web Search Engines Prashant Ullegaddi and Vasudeva Varma Search and Information Extraction Lab Language Technologies.
The Almighty Critical Look at Critical Language Teacher Education.
Data Mining Chapter 1 Introduction -- Basic Data Mining Tasks -- Related Concepts -- Data Mining Techniques.
Information Retrieval Evaluation and the Retrieval Process.
Introduction to Research
Actors & Structures in Foreign Policy Analysis January 23, 2014.
BEHAVIORAL TARGETING IN ON-LINE ADVERTISING: AN EMPIRICAL STUDY AUTHORS: JOANNA JAWORSKA MARCIN SYDOW IN DEFENSE: XILING SUN & ARINDAM PAUL.
Qualitative Research January 19, Selecting A Topic Trying to be original while balancing need to be realistic—so you can master a reasonable amount.
Users and Assessors in the Context of INEX: Are Relevance Dimensions Relevant? Jovan Pehcevski, James A. Thom School of CS and IT, RMIT University, Australia.
Plan for Today: Thinking about Theory 1.What is theory? 2.Is theory possible in IR? 3.Why is it important? 4.How can we distinguish among theories?
Information Retrieval in Context of Digital Libraries - or DL in Context of IR Peter Ingwersen Royal School of LIS Denmark –
Theme 2: Data & Models One of the central processes of science is the interplay between models and data Data informs model generation and selection Models.
Jane Reid, AMSc IRIC, QMUL, 30/10/01 1 Information seeking Information-seeking models Search strategies Search tactics.
Computer Science, Algorithms, Abstractions, & Information CSC 2001.
MDA & RM-ODP. Why? Warehouses, factories, and supply chains are examples of distributed systems that can be thought of in terms of objects They are all.
L&I SCI 110: Information science and information theory Instructor: Xiangming(Simon) Mu Sept. 9, 2004.
Research for Nurses: Methods and Interpretation Chapter 1 What is research? What is nursing research? What are the goals of Nursing research?
What Does the User Really Want ? Relevance, Precision and Recall.
Challenging students to acquire deeper knowledge in HCI course N. Ackovska and M. Kostoska 15 th Workshop on “Software Engineering and Reverse Engineering”
Case Studies and Review Week 4 NJ Kang. 5) Studying Cases Case study is a strategy for doing research which involves an empirical investigation of a particular.
Why IR test collections are so bad Mark Sanderson University of Sheffield.
Chapter. 3: Retrieval Evaluation 1/2/2016Dr. Almetwally Mostafa 1.
Paradigms. Positivism Based on the philosophical ideas of the French philosopher August Comte, He emphasized observation and reason as means of understanding.
ABRA Week 3 research design, methods… SS. Research Design and Method.
Understanding the Research Process
Chapter 1 Introduction to Research in Psychology.
Copyright © 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 1 Research: An Overview.
Two Central Research Frameworks in Information Retrieval: Drifting outside the Cave of the Laboratory Framework Peter Ingwersen* & Kalervo Järvelin** *
1 Prepared by: Laila al-Hasan. 1. Definition of research 2. Characteristics of research 3. Types of research 4. Objectives 5. Inquiry mode 2 Prepared.
Cedric D. Murry APT Instructor of Applied Technology in research and development.
Evaluation of an Information System in an Information Seeking Process Lena Blomgren, Helena Vallo and Katriina Byström The Swedish School of Library and.
Moshe Banai, PhD Editor International Studies of Management and Organization 1.
Information Retrieval in Practice
The scope and focus of the Research
CASE STUDY BY: JESSICA PATRON.
Research Methods in Nursing
Scientific Research in Computing
The Sense of Information: Understanding the cognitive conditional information concept in relation to information acquisition Peter Ingwersen* & Kalervo.
EFD-408: Foundations of American Education
Presentation transcript:

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow THEORETICAL ISSUES IN CONTEXT MODELLING Kalervo Järvelin University of Tampere Finland

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Talk Outline  Lab IR - traditional study designs and contributions  Contexts of IR  Modeling context - issues in modeling  A cognitive approach to modeling  Consequent research designs  Conclusion - does it matter?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow The Lab IR Framework Docu- ments Docu- ments Represen- tation Represen- tation Database Search request Search request Query Matching Represen- tation Represen- tation Query Result Query Result Evaluation Result Evaluation Result Evaluation Relevance assessment Relevance assessment Recall base Recall base

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow The most popular focus - it is CS, after all, isn’t it?! IR Research Goals  Traditional goals:  (a) theoretically (~formally) understanding IR,  (b) empirically testing IR methods, and  (c) designing better IR systems  This can be seen in typical IR study designs - by populating the framework with variables

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Lab IR Study Types / Designs  Study types:  experimental  methodological  constructive  theoretical  Experimental designs – IR evaluation  focus areas with variables  designs operate with these  fringe areas controlled (no analytical variables)  dependent variables: E R  many hidden variables

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow LabIR: Hypos, Laws, Theories  The dependent variables - typically recall and precision - using various metrics  The independent variables typically are the use or non-use of various techniques  The controlled variables - collection, requests  Thus Lab IR is about the explanation of the variation of recall and precision through IR techniques applied

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow LabIR: Contributions  IR technology  Theoretical growth  theory expansion, e.g., due to enrichment of indexing theory  greater analytical power through formal model building  improved empirical support through testing over several test collections  new research questions – within the given set of variables  Theoretical growth has been limited by not bringing in radically new concepts or relations  Cannot possibly analyze real world applicability

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Lab IR Tests  IR research typically considers only retrieval tasks which most often are:  (a) purely topical  (b) content-only  (c) well-defined  (d) static, and  (e) exhaustive This is like saying that no matter what your situation is, your needs always are purely topical, content-only, well-defined, static, and … … True, isn’t it?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Small World?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Psssst IR in Context Alternatives?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow One possible context: Task Performance Augmentation through IR Augmenting Task Performance Colleagues KnowledgeMethodology Education/Training Create Information Seeking Remember/Use Tools Work Task Situation Other Sources Education Documents Information Systems Acquire Knowledge Find Docs Docs Available Retrieve Docs Other Collections Colleagues... DocDBFactDB Context Web...

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Socio-organizational& cultural context Nested Context Frameworks  How much should one cover? Work Task Work Process Task Result Work task context Seeking Task Seeking Process Seeking Result Seeking context Docs Repr DB Request Query Match Repr Result IR context  How to model what is covered?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow What to cover?  Clearly, current IR test designs are not representative of real world IR  In principle,  whatever has important relationships with the application of IR, should be covered  however, what has, is not well known  answering this requires theoretical modeling, operationalization and empirical testing  so, what is context?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Context? What?!  Dervin (1997):  there is no term that is more often used, less often defined, and when defined defined so variously as context - it has become almost a ritualistic invocation  for some, context has the potential of being virtually anything that is not defined as the focus  for others, it is inextricable surround that denies all generalizations  there are endless lists of contextual factors  This is why we hate it - it is foreign to CS!

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Some Contextual Themes  Reality is discontinuous, knowledge partial  Context is not useful as an independent entity  Context requires a focus on process and relationships between product and process  Need to focus on multiple interdependencies  Context is a necessary source of meaning (Dervin 1997)

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow How to model? - IR Context Dimensions 1.Work task dimension 2.Search task dimension 3.Actor dimension 4.Perceived work task dimension 5.Perceived search task 6.Document dimension 7.Algorithmic search engine dimension 8.Algorithmic interface dimension 9.Access and interaction dimension Each dimension containing multiple variables Much more detail in the forthcoming book by Peter&Kal

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Information Objects Information Systems Interfaces Cognitive Actor(s) Organisat. Cultural = Cognitive transformation and influence = Interactive communication of cognitive structures Social & Context A Cognitive Model of IS&R

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Context around and within Information objects IT: Engines Algorithms Interface Information seeker Org. Cultural Social Context Real Social & Physical World Cognitive World Perceived Information objects Perceived IT: Engines Algorithms Perceived Interface Situation i.e. perceived task – need sources Social Org. / Cultural Perceived context

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Augmented IR Research Goals  Theoretically understanding the application of IR in / to context ; not just engines but also their use in varying situations  Empirically describing / testing the application of IR in / to various contexts  Supporting the design of information systems, services and information management  This does not downgrade IR into Social Science but rather means more / better engineering

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow New Research Settings  Extended laboratory experiments  What kinds of work tasks are typical in Domain X?  What kinds of search tasks do these generate?  What kinds of documents tend to be relevant?  IIR experiments  Lab approach but including the seeking actor  Research on interfaces / actors in context  interaction of actors and information system interfaces in diverse socio-organizational contexts

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Lab IR settings focused on domain/task variables and dimensions of IT and information objects Information objects IT Task Org. Context Interface Actor(s) Social Cultural

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Lab IR settings focusing on actor variables and dimensions of IT and information objects Information objects IT Task Org. Context Interface Social Cultural Work task perception Search task perception Actor types

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Conclusion  Context is endless and pervasive  its management requires perspective, goals and interests: what do we want to achieve??  we may see multiple, nested contexts  Thus, what is IR about? As technology...  developing systems based on a technological imperative? based on people’s communication / access needs?  As a discipline... [vs. a technology]  understanding... perhaps... but what? C-n-c-l?

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow Does context really matter?  We do not know really (if, or how much)  Some certainly wish / believe it does not  I don’t believe them until shown that  no matter what one’s situation is, one’s information needs are of just one type  no matter of what type information needs are, they are always best served in one already known way

Kalervo Järvelin – Issues in Context Modeling – ESF IRiX Workshop - Glasgow