Update appStore/vulnerability_analysis.py

appStore/vulnerability_analysis.py

@@ -41,7 +41,7 @@ def app():
 
         st.write(
             """     
-            The *SDG Analysis* app is an easy-to-use interface built \
+            The *Vulnerability Indicator* app is an easy-to-use interface built \
                 in Streamlit for analyzing policy documents with respect to SDG \
                  Classification for the paragraphs/texts in the document and \
                 extracting the keyphrase per SDG label - developed by GIZ Data \
@@ -55,30 +55,18 @@ def app():
             However, since we want to respect the sentence boundary the limit \
             can breach and hence this limit of 120 is tentative.  \n
             """)
-        st.write("""**SDG cLassification:** The application assigns paragraphs \
-            to 16 of the 17 United Nations Sustainable Development Goals (SDGs).\
-            SDG 17 “Partnerships for the Goals” is excluded from the analysis due \
-            to its broad nature which could potentially inflate the results. \
-            Each paragraph is assigned to one SDG only. Again, the results are \
-            displayed in a summary table including the number of the SDG, a \
+        st.write("""**Vulnerability cLassification:** The application assigns paragraphs \
+            to 18 different vulnerable groups in the climate context.\
+            Each paragraph is assigned to one vulnerable group only. Again, the results are \
+            displayed in a summary table including the vulnerability label, a \
             relevancy score highlighted through a green color shading, and the \
             respective text of the analyzed paragraph. Additionally, a pie \
             chart with a blue color shading is displayed which illustrates the \
-            three most prominent SDGs in the document. The SDG classification \
-            uses open-source training [data](https://zenodo.org/record/5550238#.Y25ICHbMJPY) \
-            from [OSDG.ai](https://osdg.ai/) which is a global \
-            partnerships and growing community of researchers and institutions \
-            interested in the classification of research according to the \
-            Sustainable Development Goals. The summary table only displays \
+            three most prominent groups mentioned in the document. Training data has been \
+            collected manually from different policy documents and been assigned to the groups. \
+            The summary table only displays \
             paragraphs with a calculated relevancy score above 85%.  \n""")
 
-        st.write("""**Keyphrase Extraction:** The application extracts 15 \
-            keyphrases from the document, for each SDG label and displays the \
-            results in a summary table. The keyphrases are extracted using \
-            using [Textrank](https://github.com/summanlp/textrank)\
-            which is an easy-to-use computational less expensive \
-            model leveraging combination of TFIDF and Graph networks.
-            """)
         st.write("")
         st.write("")
         st.markdown("Some runtime metrics tested with cpu: Intel(R) Xeon(R) CPU @ 2.20GHz, memory: 13GB")