Construction of personal knowledge maps for a peer-to-peer information-sharing environment

Abstract

Purpose Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments. Design/methodology/approach The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers. Findings The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality. Research limitations/implications The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively. Originality/value It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

Development and validation of perceived workplace support for small and medium-sized enterprise employees

“…The PCS dimension gave a low forecast with R 2 at 0.349 which implied the employees’ perception of support from co-workers regarding help, encouragement, suggestions, knowledge sharing for learning and development through four questions developed by researchers. The empirical result was consistent with the theory and concept of Beales and Wilson (2015), Blanchard and Thacker (2012), Chiaburu and Harrison (2008), Elias and Upton-Davis (2015), Jenkins et al (2018), Na-nan et al (2017), Qin et al (2018), Thomas and Salzer (2017) and Thompson and Bolino (2018). Furthermore, the four questions were confirmed by statistical analysis and concurred with empirical data.…”

“…Previous research found that perceived workplace support (PWS) significantly influenced staff retention, competency, development and organisational commitment (Baran et al, 2012;Eisenberger et al, 2002;Masterson et al, 2000). Supporting factors in a workplace can be divided into perceived organisational support (POS) (Akgunduz et al, 2018;Gigliotti et al, 2018;Islam and Ahmed, 2018;Lee and Jeung, 2018;Naotunna and Arachchige, 2016), perceived supervisor support (PSS) (Gok et al, 2015;Straub et al, 2018;Zeffane et al, 2018), perceived co-worker support (PCS) (Jenkins et al, 2018;Qin et al, 2018;Thomas and Salzer, 2017) and perceived sufficient resource support (PSRS) (Küçükaslan Ekmekçi and Tekin, 2011;Nielsen et al, 2010;Obadara and Alaka, 2010).…”

“…However, a literature review suggested that not all factors have been tested simultaneously. For example, some researchers studied only factors of PWS, whereas others explored PWS together with PSS (Elias and Upton-Davis, 2015; Jenkins et al , 2018; Qin et al , 2018; Thomas and Salzer, 2017). In addition, some scholars selected to investigate only factors of PCS and PSRS in combination with others.…”

An empirical study of knowledge mapping implementation in Indonesian organizational context

“…Most of the study on knowledge mapping that we found through literature came from China country such as studies of research trends on virtual communities in publications in China , maps of personal knowledge in peer to peer environments from the CNKI database (Qin et al, 2018), search for medical image records that were using semantic metadata and ontology-based knowledge mapping are also built to capture and manage manufacturing company knowledge appropriately . China as a developed country while Indonesia as a developing country certainly has a different culture, therefore this study wants to see insight into the country of Indonesia as a developing country related to the implementation of knowledge mapping.…”