Automatic Patents Classification Using Supervised Machine Learning

Shahid, Muhammad Laiq Ur Rahman; Ahmed, Adeel; Mushtaq, Muhammad Faheem; Ullah, Saleem; Matiullah,; Akram, Urooj

doi:10.1007/978-3-030-36056-6_29

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…ML allows machines to learn from supplied data and build predictions without being explicitly programmed for that task (Shahid et al, 2020); in other words, ML is a capability of the systems to acquire knowledge and improve automatically without programming the system and human assistance (Sangwan & Bhatnagar, 2020). As mentioned above, ML has been included in various ITSM activities.…”

Section: Text Miningmentioning

confidence: 99%

Assessment of Contributions of the Methodology for the Construction of a Catalog of Information Technology Services Aimed at Public Entities

Macías

Alonso

2021

International Journal of Service Science, Management, Engineering, and Technology

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Several field studies have shown low levels of implementation of this type of catalog in organizations in various countries around the world, which is accentuated in public organizations. To address this problem, the main objective of this research is to demonstrate the contribution of a methodology for the construction of a catalog of information technology services in the management of technology services aimed at public entities, which is tested and assessed in terms of its levels of contribution to the information management of technology services. The methodology used in this research was tested and evaluated by 46 IT professionals working in public organizations in Ecuador, verifying the contribution levels of the proposal in four aspects: 1) the identification of information technology services, 2) the classification of information technology services, 3) feedback from the service catalog as a transversal component, and 4) the automation of all the processes described. Favourable results were obtained regarding the proposed methodology.

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Section: Text Miningmentioning

confidence: 99%