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Analyzing SMS messages with Watson Knowledge Studio
This code pattern demonstrates how Watson Knowledge Studio can be used to build a custom model to better categorize SMS message content. This model supplements the capabilities already provided by Watson Natural Language Understanding.
Cognitive
In this developer journey we will guide the user to develop a solution using Watson Knowledge Studio and Watson Natural Language Understanding. Specifically, it will take the user through the steps to complete the following tasks:
- Using Watson Knowledge Studio to create and train the machine learning model using human annotated documents.
- Integrating the machine model into a NLU service.
- Extracting domain specific entities using this NLU service.
By Rajesh Gudikoti, Ramesh Poomalai, and Rich Hagarty
N/A
This code pattern describes how to analyze SMS messages with Watson Knowledge Studio (WKS) and Watson's Natural Language Understanding (NLU) capability to extract entities in the data. Current natural language processing techniques cannot extract or interpret data that is domain or industry specific because entities have different meanings in different domains. The best answer to such a problem is IBM's Watson Knowledge Studio.
The SMS messages provided for this Code Pattern are related to merchants offering special offers to their customers. NLU is capable of extracting some general information from each text, but we want to add the capability to extract out additional specific data, such as what the offer is, who is the merchant, how long is the offer valid, and what is the merchants phone number and website. This can be accomplished by loading sample messages into WKS and training it to recognize entities within each text. The end result is a model that can then be used to process additional messages.
After completing this code pattern, the user will learn how to:
- Upload a corpus with WKS
- Import types to WKS
- Use WKS to create a model
- Deploy a WKS model to NLU
- Call NLU APIs with a WKS model specified
- Load type system and corpus files into Watson Knowledge Studio.
- A user generates a model by training and evaluating data.
- The WKS model is deployed to Watson NLU.
- A user provides an SMS message to the app for analysis.
- The SMS message is analyzed by Watson NLS for processing and returns extracted domain specific entities based on the WKS model are returned.
- Watson Natural Language Understanding: An IBM Cloud service that can analyze text to extract meta-data from content such as concepts, entities, keywords, categories, sentiment, emotion, relations, semantic roles, using natural language understanding.
- Watson Knowledge Studio: Teach Watson the language of your domain with custom models that identify entities and relationships unique to your industry, in unstructured text. Use the models in Watson Discovery, Watson Natural Language Understanding, and Watson Explorer.
- Artificial Intelligence: Artificial intelligence can be applied to disparate solution spaces to deliver disruptive technologies.
- Java: A secure, object-oriented programming language for creating applications.