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Abstract

The research aim was to develop an understanding of information need characteristics for word co-occurrence-based search result filters (facets). No prior research has been identified into what enterprise searchers may find useful for exploratory search and why. Various word co-occurrence techniques were applied to results from sample queries performed on industry membership content. The results were used in an international survey of 54 practising petroleum engineers from 32 organizations. Subject familiarity, job role, personality and query specificity are possible causes for survey response variation. An information needs model is presented: Broad, Rich, Intriguing, Descriptive, General, Expert and Situational (BRIDGES). This may help professionals to more effectively meet their information needs and stimulate new needs, improving a system’s ability to facilitate serendipity. This research has implications for faceted search in enterprise search and digital library deployments.

Keywords

Enterprise search digital library exploratory search interactive information retrieval human–computer interaction (HCI)information discovery word co-occurrence text analytics oil and gas information-seeking behaviour serendipity user interface design

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References

De Saulles

. Information literacy amongst UK SMEs. An information policy gap. Association for Information Management (ASLIB) Proceedings: New Information Perspectives 2006; 59(1): 69–79.

Gantz

Reinsell

. Extracting value from chaos: Report ID 1142, http://www.emc.com/digital_universe (2011, accessed January 2014).

Gartner. Information management goes ‘extreme’: The biggest challenges for 21st century CIOs, http://www.sas.com/offices/NA/canada/lp/Big-Data/Extreme-Information-Management.pdf (2011, accessed March 2014).

Doane

. Cost benefit analysis: Integrating an enterprise taxonomy into a SharePoint environment. Journal of Digital Asset Management 2010; 6(5): 262–278.

International Data Corporation (IDC). The high cost of not finding information, http://www.ejitime.com/materials/IDC%20on%20The%20High%20Cost%20Of%20Not%20Finding%20Information.pdf (2001, accessed March 2013).

Adkins

. Information gathering in the electronic age: The hidden cost of the hunt. Safari Techbooks Online (2003, accessed November 2013).

Search Technologies, http://www.searchtechnologies.com/enterprise-search-surveys.html (accessed December 2013).

Webster

. Bridging the information worker productivity gap: New challenges and opportunities for IT, http://www.adobe.com/uk/products/acrobat/idc-bridging-productivity-gap-white-paper.html (2012, accessed January 2014).

Lowe

McMahon

Culley

. Characterising the requirements of engineering information systems. International Journal of Information Management 2004; 24: 401–422.

10.

Delphi Group. Taxonomy and content classification. Market Milestone Report, www.delphigroup.com (2002, accessed January 2014).

11.

Wipro and Oil Gas Journal. Oil and gas upstream data and information management survey, 2011, http://www.wipro.com/Documents/insights/oil_and_gas.pdf (accessed November 2013).

12.

McKinsey and International Data Corporation. Impact of Internet technologies: Search, 2012., http://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/High%20Tech/PDFs/Impact_of_Internet_technologies_search_final2.aspx (accessed March 2013).

13.

Majid

Anwar

Eisenshitz

. Information need and information seeking behaviour of agricultural scientists in Malaysia. Library and Information Science Research 2000; 22(2): 145–163.

14.

Findwise. Findability survey (Stockholm, May 2013), http://www2.findwise.com/findabilitysurvey2013 (accessed December 2013).

15.

Geosoft. Exploration information management survey, 2011, http://www.geosoft.com/media/uploads/resources/brochures/exploration_information_management_survey.pdf (accessed January 2014).

16.

International Data Corporation. The hidden costs of information work, 2005, http://www.slideshare.net/PingElizabeth/the-hidden-costs-of-information-work-2005-idc-report (accessed April 2013).

17.

International Data Corporation. Information advantage: Information access in tommorow’s enterprise, 2009, http://www.slideshare.net/PingElizabeth/the-information-advantage-information-access-in-tomorrows-enterprise (accessed November 2013).

18.

Association for Information and Image Management, Findability: The art and science of making content easy to find, 2008, http://www.aiim.org/Research-and-Publications/Research/Industry-Watch/Findability (accessed November 2013).

19.

Microsoft and Accenture, Upstream oil and gas computing trends survey (conducted by PennEnergy and the Oil and Gas Journal Research Centre), 2010, http://www.accenture.com/us-en/Pages/insight-upstream-oil-gas-trend-survey-2010-summary.aspx (accessed November 2013).

20.

Stratigos

. Online resource, http://www.businesswire.com/news/home/20050510005823/en/Outsell-Survey-Shows-Knowledge-Workers-Turning-Open#.U4BNkdFeHIU (2005, accessed January 2014).

21.

Mindmetre. Mind the enterprise Search Gap, 2011, http://www.smartlogic.com/home/knowledge-zone/white-papers/1600-mindmetre-research-report-sponsored-by-smartlogic (accessed March 2013).

22.

Hawking

. Challenges in enterprise search. Fifteenth Australasian database conference, Dunedin, 2004. Conferences in Research and Practice in Information Technology 2004; 27: 15–26.

23.

White

. Enterprise search, 1st edn. USA: O’Reilly, 2012, p. 164.

24.

Robinson

. An empirical analysis of engineer’s information behaviors. Journal of the American Society for Information Science and Technology 2010; 61(4): 640–658.

25.

Burnett

. The strategic role of knowledge auditing and mapping: An organizational case study. In: International forum on knowledge asset dynamics (IFKAD) – Knowledge cities world summit (KCWS), 12–15 June 2012, Matera, Italy.

26.

Wilson

. Models in information behaviour research. Journal of Documentation 1999; 55(3): 249–270.

27.

Kling

McKim

. Not just a matter of time: Field differences and the shaping of electronic media in supporting scientific communication. Journal of the American Society for Information Science 2000; 51(14): 1306–1320.

28.

Bates

. Information behavior. In: Bates

Maack

(eds) Encyclopedia of library and information sciences, 3rd edn. New York: CRC Press, 2010, pp. 2381–2391.

29.

Brown

Duguid

. Organizational learning and communities of practice: Towards a unified view of working, learning and innovation. Organizational Science 1991; 2(1).

30.

Stamper

. Signs, information norms and systems. In: Holmqvist (ed.) Signs of work, semiosis and information processing in organizations, 1st edn. New York: Walter de Gruyter, 1996.

31.

Taghavi

Patel

Schmidt

. An Analysis of web proxy logs with query distribution pattern approach for search engines. Computer Standards and Interfaces 2011; 34 (1): 162–170.

32.

Chilton

Teevan

. Addressing people’s information needs directly in a web search result page. In: Proceedings of the 20th international conference on World Wide Web, 2011, pp. 27–36.

33.

Russell-Rose

Lamantia

Burrell

. A taxonomy of enterprise search. Human Computer Information Retrieval 2011; 763 (Session 1): 15–18.

34.

Bates

. The design of browsing and berrypicking techniques for the online search interface. Online Information Review 1989; 13 (5): 407–424.

35.

Pirolli

Card

. Information foraging in information access environments. In: Computer Human Interaction 1995: Proceedings of the SIGCH conference on human factors in computing systems, 1995: 51–58.

36.

Aula

Russell

. Information seeking support systems. A workshop sponsored by the National Science Foundation, Capitol Hill June 26–27 2008. Complex and Exploratory Web Search, http://ils.unc.edu/ISSS/ (2008, accessed January 2014).

37.

Morville

Callendar

. Search patterns, 1st edn. Canada: O’Reilly, 2010.

38.

Ellis

Haugan

. Modelling the information seeking patterns of engineers and research scientists in an industrial environment. Journal of Documentation 2009; 53 (4): 384–403.

39.

Stenmark

. Identifying clusters of user behaviour in Intranet Search Engine Log Files. Journal of the American Society for Information Science and Technology 2008; 59 (14): 2232–2243.

40.

Ellis

. A behavioural approach to information retrieval and system design. Journal of Documentation 1989; 45(3): 171–212.

41.

Hearst

. Design recommendations for hierarchical faceted search interfaces. In: The Association for Computing Machinery (ACM) Special Interest Group for Information Retrieval (SIGIR) workshop on faceted search, 2006.

42.

Wilson

Andre

Schraefel

. Backward highlighting: Enhancing faceted search. In: Proceedings of the 21st symposium on user interface software and technology (UIST2008), 19–22 October 2008, Monterey, CA, pp. 235–238.

43.

Clarkson

Navathe

Foley

. Generalized formal models for faceted search interfaces. In: Joint conference on digital libraries (JCDL): 2009 proceedings of the 9th Association for Computing Machinery (ACM)/Institute of Electrical and Electronics Engineers (IEEE)–CS joint conference on digital libraries, 2009, pp. 125–134.

44.

Sacco

. Dynamic taxonomies and faceted search. Theory practice and experience, 1st edn. Berlin: Springer, 2009, p. 340.

45.

Perugini

. Supporting multiple paths to objects in information hierarchies: Faceted classification, faceted search, and symbolic links. Information Processing and Management 2010; 46: 22–43.

46.

Russell-Rose

Tate

. Designing the search experience: The information architecture of discovery, 1st edn China: Elsevier, 2013.

47.

Kaki

. Findex: Search result categories help users when document ranking fails. In: Computer Human Interaction (CHI) 2005, papers: Document interaction, 2–7 April 2005, Portland, OR.

48.

Fagan

. Usability studies of faceted browsing: A literature review. Information Technology and Libraries 2010: 58–66.

49.

Kules

Capra

Banta

. What do exploratory searchers look at in a faceted search interfaces. In: Joint conference on digital libraries (JCDL) 2009. Proceedings of the 9th Association for Computing Machinery (ACM)/Institute of Electrical and Electronics Engineers (IEEE)–CS joint conference on digital libraries, 2009, pp. 313–322.

50.

Marchionini

. Exploratory search: From finding to understanding. Communications of the Association for Computing Machinery 2006; 49(4): 41–46.

51.

Cleverley

. Improving Enterprise search in the upstream oil and gas industry by automatic query expansion using a non-probabilistic knowledge representation. International Journal of Applied Information Systems 2012; 1(1): 25–32.

52.

Hearst

. Clustering versus faceted categories for information exploration. Communications of the Association for Computing Machinery 2006; 49(4).

53.

Tunkelang

. Quotation. In: Russell-Rose

Tate

(eds) Designing the search experience: The information architecture of discovery, 1st edn. China: Elsevier, 2013, p. 165.

54.

Antelman

Lynema

Pace

. Toward a twenty first century catalog. Information Technology and Libraries 2006; 25(3).

55.

Niu

Lown

Hemminger

. Log based analysis of how faceted search interact in a library catalog interface. In: Proceedings of third workshop on human computer interaction and information retrieval, 2009, pp. 62–65.

56.

Niu

Hemminger

. Beyond text querying and ranking list: How people are searching through faceted catalogs in two library environments. In: Proceedings of the 73rd Association for Information Science and Technology (ASIS&T) annual meeting on navigating streams in an information ecosystem, 2010, Vol. 47(29)

57.

Ballard

Blaine

. User search limiting behaviour in online catalogs. Comparing classic catalog use to search behaviour in next generation catalogs. New Library World 2011; 112(5/6): 261–273.

58.

Kules

Capra

. Influence of training and stage of search on gaze behaviour in a library catalog faceted search interface. Journal of the American Society for Information Science and Technology 2010; 63(1): 114–138.

59.

Ren

. An unsupervised cascade learning scheme for ‘cluster-theme keywords’ structure extraction from scientific papers. Journal of Information Science 2014; 40(2): 167–179.

60.

Chen

Yim

Fye

. Automatic thesaurus generation for an electronic community system. Journal of the American Society for Information Science 1995; 46(3): 175–193.

61.

Ding

Chowdhury

Foo

. Incorporating the results of co-word analyses to increase search variety for information retrieval. Journal of Information Science 2000; 26(6): 429–452.

62.

Buzydlowski

White

Lin

. Term co-occurrence analysis as an interface for digital libraries. In: Börner

Chen

(eds) Visual interfaces to digital libraries, 1st edn. Berlin: Springer, 2002.

63.

Shiri

. Metadata enhanced visual interfaces to digital libraries. Journal of Information Science 2008; 34(6): 763–775.

64.

Olson

. Utility of a faceted catalog for scholarly research. Library Hi Tech Emerald 2007; 25(4): 550–561.

65.

Gwizdka

. What a difference a tag cloud makes: effects of tasks and cognitive abilities on search results interface use. Information Research 2009; 14(4).

66.

Low

. Usability and contemporary user experiences in digital libraries. For metadata and Web 2.0 – Cataloguing and Indexing Group Scotland (CIGS) Seminar, 23 February 2011, University of Edinburgh, http://www.slideshare.net/scottishlibraries/ux2-usability-and-contemporary-user-experience-in-digital-libraries (accessed January 2014).

67.

Heimerl

Lohmann

Lange . Word Cloud Explorer: Text analytics based on Word Clouds. In: Proceedings of the 47th Hawaii International Conference on System Science (HICSS 2014), 6–9 January 2014, http://www.vis.uni-stuttgart.de/uploads/tx_vispublications/HICSS2014_Word_Cloud_Explorer_preprint.pdf (accessed January 2014).

68.

Halvey

Keane

. An assessment of tag presentation techniques. In: Proceedings of 16th International World Wide Web Conference (WWW), 2007, http://www2007.org/htmlposters/poster988/ (accessed January 2014).

69.

Creswell

Plano Clark

. Designing and conducting mixed methods research, 2nd edn. Thousand Oaks, CA: Sage, 2011.

70.

Stenmark

Jadaan

. Intranet users’ information-seeking behaviour: An analysis of longitudinal search log data. In: 69th Annual meeting of the American Society for Information Science and Technology (ASIST), Austin, TX, 3–8 November 2006, Vol. 43(1).

71.

Raskin

. National Aeronautics Space Administration Semantic Web for Earth and Environmental Terminology (SWEET) ontology, http://sweet.jpl.nasa.gov/ontology/ (2011, accessed February 2013).

72.

Berger

Luckmann

. The social construction of reality. A treatise in the sociology of knowledge, 1st edn. London: Penguin, 1966.

73.

Society of Petroleum Engineers. Petrowiki based on Petroleum Engineering Handbook, http://petrowiki.org/PetroWiki (2014, accessed April 2014).

74.

Google. Google n-gram viewer, https://books.google.com/ngrams (2013, accessed September 2013).

75.

Vorhees

Hamman

. Overview of the seventh text retrieval conference (TREC-7). National Institute of Science and Technology (NIST) Publication 500–242 1998: pp.1.

76.

Cox

Fisher

. Expectation as a mediator of user satisfaction 2004. WWW 2004 Conference workshop, New York, 18 May 18, 2004.

77.

Harris

. Distributional structure. Word 1954; 10 (23): 146–162.

78.

Bartsch

. Structural and functional properties of collocations in English: A corpus study of lexical and pragmatic constraints on lexical cooccurrence, 2004, p. 92.

79.

Lund

Burgess

Atchley

. Semantic and associative priming in high-dimensional semantic space. In: Cognitive science proceedings, 1995, pp. 660–665, http://locutus.ucr.edu/Reprints.html (accessed October 2013).

80.

Bullinaria

Levy

. Extracting semantic representations from word co-occurrence statistics: A computational study. Behaviour Research Methods 2007; 39: 510–526.

81.

Veling

van der Weerd

. Conceptual grouping in word co-occurrence networks. In: Proceedings of the 16th international joint conference on artificial intelligence (IJCAI), 1999, Vol. 2, pp. 694–699.

82.

Vechtmova

Roberston

Jones

. Query expansion with long span collocates. Journal of Information Retrieval 2003; 6(2): 251–273.

83.

Python website, https://www.python.org/ (accessed February 2013).

84.

University of Glasgow. Information retrieval stop word list, http://ir.dcs.gla.ac.uk/resources/linguistic_utils/stop_words (accessed August 2013).

85.

Church

Hanks

. Word association norms, mutual information and lexicography. Computational Linguistics 1991; 16(1): 22–29.

86.

Glaser

Strauss

. The discovery of grounded theory: strategies for qualitative research, 7th edn. New Brunswick, NJ: Aldine, 2012.

87.

Strauss

Corbin

. Basics of qualitative research. Techniques and procedures for developing grounded theory, 2nd edn. Thousand Oaks, CA: Sage, 1998.

88.

Dey

. Grounding grounded theory: Guidelines for qualitative inquiry, 1st edn. Bingley: Emerald Group, 1999.

89.

Kidwell

Lebanon

Cleveland

. Visualizing incomplete and partially ranked data. Institute of Electrical and Electronics Engineers (IEEE) Transactions on Visualization and Computer Graphics 2008; 14(6): 1356–1363

90.

McCallum

. MALLET: A machine learning for language toolkit, http://mallet.cs.umass.edu/ (2002, accessed November 2013).

91.

Blei

Jordan

. Latent Dirichlet allocation. Journal of Machine Learning Research 2003; 3: 993–1022.

92.

Balagopalan

. Topic modelling tool, http://code.google.com/p/topic-modeling-tool/ (2011, accessed November 2013).

93.

Kralisch

Berendt

. Cultural determinants of search behaviour on websites. In: Proceedings of the international workshop on internationalisation of products and systems (IWIPS) 2004 conference on culture, trust and design innovation, Vancouver, 8–10 July, 2004, http://csi.ufs.ac.za/resres/files/Kralisch(6).pdf (accessed January 2014).

94.

Marcos

Garcia-Gavilanes

Bataineh

. Cultural differences on seeking information. An eye tracking study. In: Computer human interaction (CHI), Paris, 27 April to 2 May 2013, http://repositori.upf.edu/handle/10230/20943 (accessed November 2013).

95.

Sapsford

. Survey research, 2nd edn. London: Sage, 2007; pp. 169.

96.

Heinstrom

. Fast surfers, broad scanners and deep divers – personality and information seeking behaviour. Doctoral dissertation Abo Akademi University, 2002, http://users.abo.fi/jheinstr/ (accessed June 2013).

97.

Halder

Roy

Chakraborty

. The influence of personality traits on information seeking behaviour of students. Malaysian Journal of Library and Information Science 2010; 15(1): 41–53.

98.

Theodosiou

Vizirianakis

Angelis

. MeSHy: Mining unanticipated PubMed information using frequency of occurrences and concurrences of MeSH terms. Journal of Biomedical Informatics 2011; 44: 919–926.

99.

McCay-Peet

Toms

. Measuring the dimensions of serendipity in digital environments. Information Research 2011; 16(3).

100.

White

Mayr

. Pennants from descriptors. In: Networked knowledge organizational systems (NKOS) workshop, 2013.

101.

Spiteri

. Word association testing and thesaurus construction. Library and Information Science Research Electronic Journal (LIBRES) 2004; 14 (2).

102.

Pisi

. Contextual search: Issues and challenges. Usability symposium (USAB). Lecture Notes in Computer Science, Vol. 7058. Berlin: Springer, 2011, pp. 23–30.

103.

Beresi

Kim

Song

Ruthven

. Why did you pick that? Visualizing relevance criteria in exploratory search. International Journal of Digital Libraries 2010; 11(2): 59–74.

104.

Chuang

Manning

Heer

. ‘Without the clutter of unimportant words’: Descriptive keyphrases for text visualization. ACM Transactions on Computer–Human Interaction 2012; 19(3).

105.

White

Roth

. Exploratory search: Beyond the query–response paradigm, 1st edn. California: Morgan & Claypool, 2009.

106.

Wilson

. Search user interface design. In: Marchionini (ed.) Synthesis lectures on information concepts, retrieval, and services. California: Morgan & Claypool, 2011.

107.

Beavan

. Glimpses through the clouds: Collocates in a new light. Digital Humanities 2008, 25–29 June, University of Oulu.

108.

Kuo

Hentrich

Good

Wilkinson

. Tag clouds for summarizing web search results. In: Poster paper 16th international World Wide Web conference, Banff, Alberta, 8–12 May 2007.

109.

Society of Petroleum Engineers. Membership society and association online libraries sites. OnePetro Digital Library Search, https://www.onepetro.org/ (accessed January 2014).

110.

American Association of Petroleum Geologists. AAPG datapages, http://archives.datapages.com/data/index.html (accessed January 2014).

111.

Subscription, journal online library sites and web search engines. Elsevier: ScienceDirect Digital Library Search: http://www.sciencedirect.com/. Springer: SpringerLink Digital Library Search: http://link.springer.com/. Wiley: Wiley Online Digital Library Search, http://onlinelibrary.wiley.com/. Sage: Sage Library, http://library.sage.edu/. Emerald Group: Emerald Insight, http://www.emeraldinsight.com/. Google Scholar, http://scholar.google.co.uk/. Microsoft Academic Search, http://academic.research.microsoft.com/. Stanford University: Highwire Online Literature Search, http://highwire.stanford.edu/. Massachusetts Institute of Technology Library, http://libraries.mit.edu/. University of Cambridge Library, http://www.lib.cam.ac.uk/. University of Oxford Bodleian Library, http://www.bodleian.ox.ac.uk/. Worldcat, https://www.worldcat.org/. Deep web, http://deeperweb.com/. Clusty, http://www.clusty.com/ (all accessed January 2014).

112.

Enterprise search and text analytics sites and articles. Microsoft: Enterprise Search Case Study Online Article, http://www.microsoft.com/casestudies/Microsoft-FAST-Search-Server-2010-For-Sharepoint/International-Monetary-Fund/Economists-Quickly-Find-Information-Using-Enterprise-Search/4000011274. Google: Enterprise Search Case Study Online Articles, http://www.computerweekly.com/feature/Case-Study-How-BG-Group-made-Google-work-internally and http://www.slideshare.net/searchtechnologies/a-gsa-case-study-manufacturing-industry. Enterprise Search Europe 2014 Conference Presentations, http://www.enterprisesearcheurope.com/2014/ . Findwise Enterprise Search Case Study SlideShare Channel, http://www.slideshare.net/findwise. Butler Analytics, 2014 Online Article Text Analytics Platforms, http://butleranalytics.com/20-text-analytics-platforms/. Expert System, http://www.expertsystem.net/ (all accessed March 2014).

113.

Government online library sites. Carmarthenshire (Wales, UK) Local Government Library, http://www.carmarthenshire.gov.uk/english/education/libraries/Pages/Home.aspx. United States Library of Congress Online Public Access Catalog, http://www.loc.gov/library/libarch-digital.html (both accessed March 2014).

114.

Rasmus

. The Serendipity Economy. Harvard Business Review, http://blogs.hbr.org/2013/08/how-it-professionals-can-embrace-the-serendipity/ (2013, accessed May 2014).