Natural Language Processing is the field of Computer science which deals with the study of interactions between computers and humans (users). Watson computing system is one such example which helped users to retrieve specific amount of information which they require. Watson API is built by a team of IBM. It processes large volumes of data, help users in decision making and moreover this system learns automatically from the feedback.
IBM has now announced API (Watson API) so that users can make use of this powerful system and programmers who are well versed with Restful APIs can use these services. Watson has made use of Natural Language Processing (NLP) technology to interpret the question and extract key elements such as the answer type and relationships between entities. IBM calls this API service as “Watson Ecosystem”.
How normal search is different from Watson search?
According to Schmidt, Google is “nowhere near close” to solving Internet search, as the company still can’t answer complex queries.
“Try a query like ‘show me flights under €300 for places where it’s hot in December and I can snorkel,’” Schmidt said. “That’s kind of complicated: Google needs to know about flights under €300; hot destinations in winter; and what places are near the water, with cool fish to see. That’s basically three separate searches that have to be cross-referenced to get to the right answer.”
The major difference between normal search and Watson search is that normal search searches for the specific keywords and returns a list of data which have may or may not have relevance to the query which the user has asked for but in the Watson search, the search is taken in the normal language as that of normal search but the system comprehends the query in detail and tries to make decisions and returns a precise answer to the question.
Brief overview of How Watson API works?
Watson API has access to over 200 million pages (including full data of Wikipedia). When user searches for a particular query, then it will search from the database (just like normal Google search).
- Normally, the best search results are kept.
- Then the searched results and the query are used to fetch support evidence from the database.
- Each searched result now forms hypothesis.
- These hypotheses are then evaluated on the fetched support evidence. Every answer is given some ranking on the bases of some merge algorithms.
- Highest ranked answer would be shown as a search result to the user.
There can be many applications in which the Watson API can come into play ranging from small to large business applications. Watson API can prove to be useful personal assistant in many domains namely health, travel, finance, customer service and more.
Here is the brief scenario explaining you How Watson API can help us?
For instance, let’s say user want to prescribe a medical solution for particular disease. Then user could tell Watson about all of the symptoms of the disease, and Watson would search from the existing database and would return most accurate medical solutions. Also physicians can use Watson in order to assist patients in diagnosing and recommend them by analyzing amounts of unstructured text.
The advantages can be numerous to this new era of technology and also many big companies are trying to work with this API.