# The Role of Transliterated Words in Linking Bilingual News Articles in an Archive
## 3 Similarity Measure Based on Transliteration Words
### Role of Transliteration Words
The relevant news and features of the news articles were specified, such as the length of news, much similar news, exact match news, and the number of relevant news articles, as shown in Table 5. The computed precision and recall experimental results are shown in Table 8. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**UrduNews** & EngNews & **CRMDL** & **CT** \\ \hline \multirow{4}{*}{ur1} & & 0.254 & 18 \\  & eng6 & 0.118 & 13 \\  & eng10 & 0.113 & 13 \\  & eng7 & 0.065 & 20 \\  & eng4 & 0.035 & 6 \\ \hline \multirow{4}{*}{ur2} & & 0.191 & 37 \\  & eng6 & 0.054 & 11 \\  & eng8 & 0.049 & 12 \\  & eng5 & 0.044 & 9 \\  & eng3 & 0.038 & 9 \\ \hline \multirow{2}{*}{ur3} & & 0.111 & 25 \\  & eng4 & 0.048 & 12 \\ \hline \multirow{2}{*}{ur4} & & 0.105 & 41 \\  & eng7 & 0.028 & 15 \\ \hline \multirow{2}{*}{ur5} & & 0.14 & 37 \\  & eng1 & 0.072 & 16 \\ \hline \multirow{4}{*}{ur6} & & 0.255 & 41 \\  & eng2 & 0.098 & 15 \\ \cline{1-1}  & eng8 & 0.078 & 16 \\ \cline{1-1}  & eng1 & 0.066 & 8 \\ \cline{1-1}  & eng7 & 0.064 & 23 \\ \hline \multirow{4}{*}{ur7} & & 0.155 & 98 \\  & eng10 & 0.126 & 55 \\  & eng6 & 0.121 & 52 \\ \hline \multirow{4}{*}{ur8} & & 0.155 & 38 \\  & eng6 & 0.094 & 19 \\ \cline{1-1}  & eng2 & 0.062 & 12 \\ \cline{1-1}  & eng3 & 0.05 & 13 \\ \cline{1-1}  & eng3 & 0.034 & 8 \\ \hline \multirow{4}{*}{ur9} & & 0.165 & 38 \\ \cline{1-1}  & eng7 & 0.108 & 49 \\ \cline{1-1}  & eng6 & 0.059 & 15 \\ \hline \multirow{4}{*}{ur10} & & 0.192 & 42 \\ \cline{1-1}  & eng6 & 0.112 & 24 \\ \cline{1-1}  & eng1 & 0.097 & 17 \\ \cline{1-1}  & eng7 & 0.08 & 33 \\ \cline{1-1}  & eng9 & 0.042 & 8 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Computed Similarity for 20 News Articles using SMTWA \"similarity measure based on transliteration words (SMTW)\" seems feasible for calculating the content-based similarity for linking Urdu-to-English news articles during the preservation process. The SMTW is better for lengthy news articles than for short news and more feasible for sports news. The digital news stories archive preserves linked and formatted news articles to ensure that the related news articles were accessible in the future from an enormous corpus of news articles extracted from multiple sources using the SMTW measure. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**UnNews** & \(\
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### Common Ratio Measure and Transliteration Words Measure Comparison

The content-based techniques \"CRMDL\" and \"SMTW\" performed well for linking a low-resource language, i.e., Urdu, and a high-resource language, i.e., English. The SMTW was compared against the CRMDL and keenly analyzed, and the improvement imparted by the SMTW is highlighted in this section. The comparison is made for three evaluation parameters, which are:

1. Result Improvement The results of both the CRMDL and SMTW were compared, and the improved results of the SMTW were highlighted and ranked. Improvement means that the result includes all the relevant news in the top-five news or the rank of the relevant is improved, i.e., the most relevant news brought to the top of the top-five news articles. In contrast, \"Dropped\" means a similar news article in the top five is fallen, and \"None\" is used for the same results in both techniques or for no effect by the new technique. 2. Transliteration Words Impact The use of English transliterated words is frequent in Urdu scripts and will surely have an impact on the count of common terms. The impact of transliteration words on the results was analyzed and showed the effects of linking Urdu and English news articles. 3. Result Accuracy (precision and recall) The results' accuracy needs to be compared in terms of precision and recall for both dual-lingual news articles and to assess the overall feasibility of the proposed similarity measure. Table 9 shows the dominance and better performance of the SMTW over the CRMDL for linking Urdu news articles with relevant English news articles during the presentation and development of the DNSA.