Building a Technology Recommender System Using Web Crawling and Natural Language Processing Technology

Finding, retrieving, and processing information on technology from the Internet can be a tedious task. This article investigates if technological concepts such as web crawling natural language are suitable means for knowledge discovery unstructured development of recommender system by developing prototype system. It also analyzes how well resulting performs in regard to effectivity efficiency. The research strategy based design science consists four stages: (1) Awareness generation; (2) suggestion solution considering retrieval process; (3) an artefact form Python computer program; (4) evaluation within scope comparative experiment. yields that is highly efficient retrieving basic rather random extractive text summaries websites include desired search terms. However, effectivity, measured quality results unsatisfactory due aforementioned arrangement extracted sentences summaries. found indeed technologies program whilst use additional technology/concepts would add significant value potential user. Several areas incremental improvement identified.