Update README.md

README.md

@@ -49,7 +49,61 @@ topic_model.get_topic_info()
 To view all different topic representations (keywords, labels, summary, etc.) you can run the following:
 
 ```python
-topic_model.get_topic(1, full=True)
+>>> topic_model.get_topic(0, full=True)
+{'Main': [['dialogue', 0.02704485163341523],
+  ['dialog', 0.01677038224466311],
+  ['response', 0.011692640237477233],
+  ['responses', 0.01002788412923778],
+  ['intent', 0.00990720856306287],
+  ['oriented', 0.009217253131615378],
+  ['slot', 0.009177118721490055],
+  ['conversational', 0.009129311385144046],
+  ['systems', 0.009101146153425574],
+  ['conversation', 0.008845392252307181]],
+ 'POS': [['dialogue', 0.02704485163341523],
+  ['dialog', 0.01677038224466311],
+  ['response', 0.011692640237477233],
+  ['responses', 0.01002788412923778],
+  ['intent', 0.00990720856306287],
+  ['slot', 0.009177118721490055],
+  ['conversational', 0.009129311385144046],
+  ['systems', 0.009101146153425574],
+  ['conversation', 0.008845392252307181],
+  ['user', 0.008753551043296965]],
+ 'KeyBERTInspired': [['task oriented dialogue', 0.6559894680976868],
+  ['dialogue systems', 0.6249060034751892],
+  ['oriented dialogue', 0.5788208246231079],
+  ['dialog systems', 0.530449628829956],
+  ['dialogue state', 0.5167528390884399],
+  ['response generation', 0.5143576860427856],
+  ['spoken language understanding', 0.46739083528518677],
+  ['oriented dialog', 0.4600704610347748],
+  ['dialog', 0.4534587264060974],
+  ['dialogues', 0.44082391262054443]],
+ 'MMR': [['dialogue', 0.02704485163341523],
+  ['dialog', 0.01677038224466311],
+  ['response', 0.011692640237477233],
+  ['responses', 0.01002788412923778],
+  ['intent', 0.00990720856306287],
+  ['oriented', 0.009217253131615378],
+  ['slot', 0.009177118721490055],
+  ['conversational', 0.009129311385144046],
+  ['systems', 0.009101146153425574],
+  ['conversation', 0.008845392252307181]],
+ 'KeyBERT + MMR': [['task oriented dialogue', 0.6559894680976868],
+  ['dialogue systems', 0.6249060034751892],
+  ['oriented dialogue', 0.5788208246231079],
+  ['dialog systems', 0.530449628829956],
+  ['dialogue state', 0.5167528390884399],
+  ['response generation', 0.5143576860427856],
+  ['spoken language understanding', 0.46739083528518677],
+  ['oriented dialog', 0.4600704610347748],
+  ['dialog', 0.4534587264060974],
+  ['dialogues', 0.44082391262054443]],
+ 'OpenAI_Label': [['Challenges and Approaches in Developing Task-oriented Dialogue Systems',
+   1]],
+ 'OpenAI_Summary': [['Task-oriented dialogue systems and their components, such as dialogue policy, natural language understanding, dialogue state tracking, response generation, and end-to-end training using neural networks. These components are crucial in assisting users to complete various activities such as booking tickets and restaurant reservations through spoken language understanding dialogue. The challenge lies in tracking dialogue states of multiple domains and obtaining annotations for training. Effective SLU is achieved by utilizing context from the prior dialogue history.',
+   1]]}
 ```
 
 ## Topic overview