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README.md

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 # RESTBERTa
-RESTBERTa is a fine-tuned Transformer Encoder model that supports machines in processing structured syntax and unstructured natural language descriptions for semantics in Web API documentation.
+RESTBERTa stands for *Representational State Transfer on Bidirectional Encoder Representations from Transformers approach* and should support machines 
+in processing structured syntax and unstructured natural language descriptions for semantics in Web API documentation.
 In detail, we use question answering to solve the generic task of identifying a Web API syntax element (answer) in a syntax structure (paragraph) that matches the semantics described in a natural language query (question).
+The identification and extraction Web API syntax elements from Web API documentation is a common sub task of many Web API integration tasks, like parameter matching and endpoint discovery.
+Thus, RESTBERTa might be a foundation for several Web API integration tasks. 
+Technically, RESTBERTa covers the concepts for fine-tuning a Transformer Encoder model, i.e., a pre-trained BERT model, to question answering with task-specific samples in order to prepare
+a model for a specific Web API integration task.
+
+The paper ["Semantic Parameter Matching in Web APIs with Transformer-based Question Answering"](https://ieeexplore.ieee.org/document/10254746) demonstrates the application of RESTBERTa
+on semantic parameter matching:
+
 
 # RESTBERTa for Semantic Parameter Matching
 This repository contains the weights for a fined-tuned RESTBERTa model for the task of semantic parameter matching in Web APIs. For this, we formulate question answering as a multiple choice task: