## 5 Discussion  
The primary objective of this article was to explore the application of natural language processing, data clustering, and other machine learning techniques in determining job profile requirements within the Lithuanian context. The discussion focuses on the key methods to extract data from publicly available unstructured sources. Moreover, the paper delves into the subsequent processing of these data using various vectorization techniques, examining the advantages and disadvantages of each method. During the research, it was observed that the regex method yielded the most favorable results for data extraction in the case of the Lithuanian job advertisements. Regarding data vectorization and feature extraction, the study utilized two primary techniques--TF-IDF  
Figure 5: Job requirements profile 3 (programmer) over time. \begin{table}
\begin{tabular}{p{42.7 pt} p{284.5 pt}} \hline \hline
**Profile** & \multicolumn{2}{c}{**Synthesized Keyword-Based Job Profile**} \\ \hline \multirow{5}{*}{2} & This profile is about a finance and accounting professional with a strong background in economics and financial management. They have experience working as an accountant and are skilled in using Excel and other MS Office programs, as well as accounting software such as Navision and Rivíle. Their expertise includes tax preparation, regulation compliance, and legal aspects related to financial operations. They possess analytical and critical thinking abilities, which contribute to their effectiveness in the financial field. The individual has a higher level of education, potentially a degree in business or economics and has several years of experience in industry. They may also have knowledge of the financial regulations specific to a certain republic or region. \begin{table}
\begin{tabular}{p{42.7 pt} p{284.5 pt}} \hline \hline
**Profile** & \multicolumn{2}{c}{**Synthesized Keyword-Based Job Profile**} \\ \hline \multirow{5}{*}{2} & This profile is about a finance and accounting professional with a strong background in economics and financial management. They have experience working as an accountant and are skilled in using Excel and other MS Office programs, as well as accounting software such as Navision and Rivíle. Their expertise includes tax preparation, regulation compliance, and legal aspects related to financial operations. They possess analytical and critical thinking abilities, which contribute to their effectiveness in the financial field. The individual has a higher level of education, potentially a degree in business or economics and has several years of experience in industry. They may also have knowledge of the financial regulations specific to a certain republic or region. \begin{table}
\begin{tabular}{p{42.7 pt} p{284.5 pt}} \hline \hline
**Profile** & \multicolumn{2}{c}{**Synthesized Keyword-Based Job Profile**} \\ \hline \multirow{5}{*}{2} & This profile is about a software development and testing professional with expertise in various programming languages, tools, and technologies. They have experience working with databases, APIs, security, and data management in both web and Windows environments. They are also knowledgeable in Agile project management methodologies and have a strong understanding of software systems and development processes. Their skills include SQL, Python, and JavaScript programming, as well as using various testing and development tools.  
\end{table} 
Table 3: Synthesized keyword-based job profiles for two job profiles requirements. and sentence transformers (BERT model). Due to the high dimensionality of the feature extracted data (384 dimensions), dimensionality reduction methods were employed, with the ISOMAP approach achieving the best results. A total of 11,000 models for dimensionality reduction were created to assess the different dimensionality reduction methods and their parameters, as well as the optimal parameters set for each method. Nonetheless, other methods, such as UMAP, also demonstrated a satisfactory performance.