Workplace Information Searching Behaviour -

How to Fulfil The Needs of The Information

Searcher

Marianne Lykke, professor, PhD.Aalborg UniversityDepartment of Communication, eLearning Lab

Agenda

• Workplace searching - in general

• Searching activities

• Information needs

• Queries

• Query structure – in specific

• Query structure, filters, semantic components

• Findings from searching test

Workplace information searching

• Information searching is closely related to the information environment, to the domain of interest, the set of people, the professions, work roles, problems and associated tasks

• Work tasks mould the querying activity

• Choice and combinations of search terms

• Use of system functionalities

• Relevance assessments

Workplace searching activities

• Gathering information

• Browsing with no specific goal

• Finding specific information

• Executing a transaction

• Housekeeping web content

• Communicating

(Sellen, Murphy & Shaw, 2002)

Workplace information needs

• Workplace searching is typically targeting a single “right answer”, and to a small set of useful documents

(Marchionini, 2006)

Workplace information needs

• The correct answer is context specific, consist of several search concepts, often non-topical concepts, e.g.

• Source• Authority• Genre• Customer• Products• Audience• Organisational unit

Product manager:

”I want to know which SSRI’s have the indication: treatment of young people and children for major depression”

Family practitioner:

”Søren has been attacked with knife. He comes in because he is nervous, dare not leave his apartment. Is it possible to refer Søren to free psychological help?”

Workplace queries

• Searchers submit more queries compared to general searching

• Queries in workplace searching consist of more search terms compared to general searching

• Queries are structured into a number of search facets

• Queries are jargon-heavy and use acronyms and abbreviations

Implications

• Support identification of search concepts

• Support structuring of query

• Support choice and variation of search vocabulary

Vocabulary support

Data

Warehousetxt

EDMSIntranet

XML

Thesaurus

software db

Knowledge

bases

Testing query structuring

• We developed the Semantic component model to facilitate formulation of specific, structured queries covering the search topic exhaustively by domain-specific dimensions

• We tested the model in a comparative search test with 30 family practitioners

• 4 search tasks, 2 tasks in System1 (control system) and 2 tasks in System2 (experimental system)

• Data collection by search logs, observation, questionnaires:

• search concepts, number of queries, structure of queries, query vocabulary, query performance

Semantic components

• Mark up segments of content in stead of assigning keywords

• Segments, semantic components, contain information about a certain aspect, e.g. diagnosis, treatment, referral, risk factors

• Solution builds on assumption that it will be easier to formulate structured, varied queries by searching for specific components

HIO 2009 Marianne Lykke

SC: General information

SC: Practical information

Document class: Clinical method

HIO 2009 Marianne Lykke

SC: General information

SC: Risk factors

After treatment

Document class: Clinical method

Findings

• System2 with semantic components improved performance 25.6%, measured by nDCG (Normalized Discounted Cumulative Gain)

• Test persons are consistent in choosing 2 main search concepts

• Test persons are interactive, but not hyperactive

• Use topical search concepts in queries

• Use filters for non-topical concepts:

• Region filter: 45% in System1 and 34% in System2

• Information filter: 49% in System1 and 29% in System2

• Semantic components: 68.1%

Consequences for design

• Only main search concepts, about 2 - 3 concepts

• No use of Information type filter

• No use of Region filter

• Best match implementation of Semantic components

Best query Problem Consequence

Use of 2-3 core search concepts. Consistent use

No documents fulfill all search concepts

Support in identifying core search concepts

No use of Informationtype filter

Divergence use of information type authority terms by searchers and indexers

Best match implementation

Better indexing policy

No use of Region filter No region-specific documents for all tasks

Best match implementation

Use of core semantic

components

Some components more

core than others

Exact match

implementation

Simplere SC model

Best match

implementation

Support in identifying core SC

Take aways

• Directed, multidimensional information needs

• Combination of topical and non-topical search concepts

• Skilled information searchers

• Domain-specific, jargon-heavy vocabulary

• Workplace information retrieval

• Support the structuring of queries

• Support choice and variation of search vocabulary

• Inform about limitations in indexing and search features

LiteratureCase, D.C. (2002). Looking for information. Amsterdam: Elsevier.

Fagin, R., Kumar, R., McCurley, K S., Novak, J., Sivakumar, D., Tomlin, J.A. & Williamson, D.P. (2003). Searching the workplace web. In: Proceedings of the 12th International World Wide Web Conference (WWW ’03), Budapest, Hungary, May 20-24, 2003. 366-375.

Freund, L., Toms, E. & Waterhouse, J. (2005). Modeling the information behaviour of software engineers using a work-task framework. In: Grove, A (ed.) ASIS&T ’05 Proceedings of the 68th Annual meeting, Charlotte, NC, October 28-November 2, 2005.

Freund, L., Toms, E.G. (2006) Enterprise search behaviour of software engineers . Poster session of the 29 th Annual International ACM SIGIR Conference , Seattle , Washington .

Lykke, M., Ingwersen, P.I., Bogers, T., Larsen, B. & Lund, H. (2010). Physicists’ information tasks: structure, lengthand retrieval performance. (Poster submitted til Information Interaction in Context (IIIX), New Brunswick (NJ), USA, August, 2010, 4 s.

Lykke, M., Price, S. L. & Delcambre, L. M. L. (2010). How doctors search: a study of family practitioners’ query behaviour and the impact on search results. 22 s. (Fortcoming)

Price, S. L., Nielsen, M. L., Delcambre, L. M. L., Vedsted, P. & Steinhauer, J. (2009). Using Semantic Components to Search for Domain-Specific Documents: An Evaluation from the System Perspective and the User Perspective. Information Systems, 34 (8). 778 – 806.

Stenmark, D. (2005). Searching the intranet: corporate users and their queries. In: Grove, A (ed.) ASIS&T ’05 Proceedings of the 68th Annual meeting, Charlotte, NC, October 28-November 2, 2005.

Vakkari, P. (2003). Task-based information searching. Annual Review of Information Science and Technology, 37, 413-466.

Knowledge workers’ web searching

(Sellen, Murphy & Shaw, 2002)

Research questions The purpose is to investigate how and why knowledge workers use the web

Methodology • Literature review

• Data collection:

• Diary study with 24 knowledge workers

• Examination of complete two-day set of web activities

• Free form description and supplemental questions

• Data analysis:

• 295 activities were recorded

• Descriptive statistics: mean of 12.3 activities, sd 6.1 across participants

• analysis

• Activity classification: Finding, Information gathering, Browsing,

Transacting, Communication, Housekeeping

• Importance analysis

Findings • Better tagging

• Better search tools

• Web scrapbooks (copy and save info bits)

• Better history functions

• Different kinds of Web activities points toward certain kinds of devices, services,

applications and infrastructure

Knowledge workers’ web searching