Abstract
Innovation in the small-medium industries (SMI) sector, which has limited human resources, requires collaboration with academic researchers. Thus, SMI needs an appropriate search tool to find a suitable researcher. Since the skill classification of researchers arranged in an academic environment is very formal and hierarchical, it tend to be challenging for laypeople to understand that skills classification. This study proposes a method to combine expert retrieval based on portfolio content with expert topic maps based on search keywords from user preferences using local journal publication sources indexed at Portal Garuda. This research evaluates the TFIDF-VSM method with the BM25 Okapi for expert retrieval and text rank with text network analysis (betweenness centrality value) for the construction of a map of the topic of its expertise. Furthermore, the prototype was tested with the System Usability Scale instrument to measure the level of usability. The combined use of the BM25 Okapi method and the text network analysis with betweenness centrality value shows a pretty good usability with a value of 73,489. The different backgrounds of academics and SMI practitioners require an appropriate search method approach. Therefore, combining expert retrieval with expert topic maps based on keywords becomes a solution that can help ordinary people (SMI practitioners) find expert researchers to support product innovation in their SMI.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Al Hakim S, Sensuse DI (2018) Knowledge mapping system implementation in knowledge management : a systematic literature review. In: 2018 International conference on information management and technology (ICIMTech), September, 1–6
Al Hakim S, Sensuse DI, Budi I (2020) Conceptual model smart knowledge mapping with process and activity combination quadrant: finalization and implementation. J High Technol Manag Res 31(2):1–22. https://doi.org/10.1016/j.hitech.2020.100393
Al Hakim S, Indra SensuseLukman D (2019) Knowledge mapping system features for supporting researcher mobility into industries and sme from e-government perspective. J Phys Conf Ser 1196(1):1–8. https://doi.org/10.1088/1742-6596/1196/1/012028
Baeza-Yates R, Ribeiro-Neto B (2011) Modern information retrieval: the concepts and technology behind search, 2nd edn. Pearson Education Limited, New York
Balog K, Azzopardi L, de Rijke M (2009) A language modeling framework for expert finding. Inf Process Manag 45(1):1–19. https://doi.org/10.1016/j.ipm.2008.06.003
Bangor A, Staff T, Kortum P, Miller J (2009) Determining what individual SUS scores mean: adding an adjective rating scale. Journal of Usability Studies. 4(3):114–123
Balog K, Fang Y, De Rijke M, Serdyukov P, Si L (2012) Expertise retrieval. Found Trends Inf Retr 6(2–3):127–256. https://doi.org/10.1561/1500000024
Brandes U (2008) On variants of shortest-path betweenness centrality and their generic computation. Soc Netw 30(2):136–145. https://doi.org/10.1016/j.socnet.2007.11.001
Brooke J (1996) SUS—a quick and dirty usability scale. In: Usability evaluation in industry, 1st edn. Taylor and Francis, London, pp 1–6
Brooke J (2013) SUS: a retrospective. J Usability Stud 8(2):29–40
Esposito De Falco S, Renzi A, Orlando B, Cucari N (2017) Open collaborative innovation and digital platforms. Prod Plan Control 28(16):1344–1353. https://doi.org/10.1080/09537287.2017.1375143
Foo S (2011) Retrieval effectiveness of cross language information retrieval search engines. In: Proceedings of the international conference on asia-pacific digital libraries (ICADL2011), vol 7008, October 2011, pp 296–306. https://doi.org/10.1007/978-3-642-24826-9
Gonçalves R, Dorneles CF (2019) Automated expertise retrieval: a taxonomy-based survey and open issues. ACM Comput Surv 52(5):1–30. https://doi.org/10.1145/3331000
Gruszecka M, Pikusa M (2015) Using text network analysis in corpus studies—a comparative study on the 2010 TU-154 polish air force presidential plane crash newspaper coverage. Int J Soc Sci Human 5(2):233–236. https://doi.org/10.7763/ijssh.2015.v5.459
Husain O, Salim N, Alias RA, Abdelsalam S, Hassan A (2019) Expert finding systems: a systematic review. Appl Sci (switzerland) 9(20):1–32. https://doi.org/10.3390/app9204250
ISO (2018) ISO 9241-11:2018(en) Ergonomics of human-system interaction—part 11: usability: definitions and concepts. https://www.iso.org/obp/ui/#iso:std:iso:9241:-11:ed-2:v1:en
Lin S, Hong W, Wang D, Li T (2017) A survey on expert finding techniques. J Intell Inf Syst 49:255–279. https://doi.org/10.1007/s10844-016-0440-5
Liu P, Liu K (2010) Ontology-based expertise locator. In: Proceedings—3rd international conference on business intelligence and financial engineering, BIFE 2010, pp 81–85. https://doi.org/10.1109/BIFE.2010.29
Manning CD, Raghavan P, Schütze H (2008) The vector space model for scoring. In: Introduction to information retrieval (Issue c). Cambridge University Press, pp 120–126. http://www-nlp.stanford.edu/IR-book/
Manning CD, Raghavan P, Schütze H (2009) An introduction to information retrieval. In: Cambridge University Press, Cambridge, England. Cambridge University Press. https://doi.org/10.1210/endo-38-3-156
Maron ME, Kuhns JL (1960) On relevance, probabilistic indexing and information retrieval. J ACM (JACM) 7(3):216–244. https://doi.org/10.1145/321033.321035
Mihalcea R, Tarau P (2004). TextRank: bringing rrder into texts. In: Proceedings of the 2004 conference on empirical methods in natural language processing, vol 45, No. 4. https://doi.org/10.1016/0305-0491(73)90144-2
Minna, Saunila (2019) Innovation capability in SMEs: a systematic review of the literature. J Innov Knowl 3(1):44–55. https://doi.org/10.1016/j.jik.2017.06.002
Mooers CN (1951) Zatocoding applied to mechanical organization of knowledge. Am Doc 2(1):20–32. https://doi.org/10.1002/asi.5090020107
Mooers CN (1956) Zatocoding and developments in information retrieval. ASLIB Proc 22(4):115–134. https://doi.org/10.1108/eb050233
Moradi R, Mahani NT, Eghbali N, Ketabchi E, Mirian MS (2012). Knowledge map as a decision support tool for expert finding in research-based organizations. In: 2012 6th international symposium on telecommunications, IST 2012, pp 1195–1200. https://doi.org/10.1109/ISTEL.2012.6483170
Najafi-Tavani S, Najafi-Tavani Z, Naudé P, Oghazi P, Zeynaloo E (2018) How collaborative innovation networks affect new product performance: product innovation capability, process innovation capability, and absorptive capacity. Ind Market Manag 73(May 2016):193–205. https://doi.org/10.1016/j.indmarman.2018.02.009
Paranyushkin D (2011) Identifying the pathways for meaning circulation using text network analysis. Venture Fiction Pract 2(4):26
Rafiei M, Kardan AA (2015) A novel method for expert finding in online communities based on concept map and PageRank. Hum Centric Comput Inf Sci. https://doi.org/10.1186/s13673-015-0030-5
Sauro J (2011) Measuring usability with the system usability scale(SUS). https://measuringu.com/sus
Sauro J, Lewis JR (2012) Standardized usability questionnaires. In: Sauro J, Lewis JR (eds) Quantifying the user experience. https://doi.org/10.1016/B978-0-12-384968-7.00008-4
Sharfina Z, Santoso HB (2017) An Indonesian adaptation of the system usability scale (SUS). In: 2016 International conference on advanced computer science and information systems, ICACSIS 2016, pp 145–148. https://doi.org/10.1109/ICACSIS.2016.7872776
Trotman A, Puurula A, Burgess B (2014) Improvements to BM25 and language models examined. ACM Int Conf Proc Ser 58:65. https://doi.org/10.1145/2682862.2682863
Funding
This study was supported by the PUTI Q2 grant “The Concept Model Development of Social Media Application for Knowledge sharing between Researchers and Small and Medium Industries in Indonesia” (NKB-1483/UN2.RST/HKP.05.00/2020). We would express our gratitude to the Faculty of Computer Science and the directorate of Research and Community Engagement, Universitas Indonesia.
Author information
Authors and Affiliations
Contributions
Conceptualization was main contributed by SAH; Methodology was contributed by IB; Formal analysis and investigation were contributed by SAH; Writing—draft preparation was contributed by SAH; Writing—review and editing was contributed by AHAMS; Funding acquisition was contributed by DIS; Resources were contributed by IMIS; Supervision was contributed by DIS and IB.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests as defined by Springer or other interests that might be perceived to influence the results and discussion reported in this paper. This written manuscript is purely research related to the author's study on the smart knowledge mapping conceptual model, which has been published by (Al Hakim et al. 2020).
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Al Hakim, S., Sensuse, D.I., Budi, I. et al. Expert retrieval based on local journals metadata to drive small-medium industries (SMI) collaboration for product innovation. Soc. Netw. Anal. Min. 13, 68 (2023). https://doi.org/10.1007/s13278-023-01044-5
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s13278-023-01044-5