Probabilistic Latent Semantic Analyses (PLSA) in Bibliometric Analysis for Technology Forecasting
AbstractDue to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA) has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA) which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency
Download data is not yet available.
Metrics Loading ...
How to Cite
Zan, W., TSIM, Y., Yeung, W., Chan, K., & Liu, J. (2007). Probabilistic Latent Semantic Analyses (PLSA) in Bibliometric Analysis for Technology Forecasting. Journal of Technology Management & Innovation, 2(1), 11-24. Retrieved from https://www.jotmi.org/index.php/GT/article/view/art32
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).