As an example, consider that you have a small data set and you search for the word “expensive”. You first search keywords and you don’t get any hits on the exact word ‘expensive’ in your data set. But by using the context you could get hits on synonyms or semantically similar words such as “costly”, “high priced”, “pricey” etc. In this way, you get a much higher chance of finding relevant quotes for your search query.
If you write a longer search query, you can improve the result and help the model understand the query. It is, therefore, best if your search queries are full sentences. As an example, consider the different meanings of the word bank in this sentence; “after stealing money from the bank vault the bank robber was fishing on the Mississippi riverbank“. Bank as a word by itself can have many meanings, but as we add more words to the sentence we get the context and so does the search engine.
Example of Contextual Search
Notice in the screenshot for the contextual search that the matches are based on the context of the question and not the exact matches of words in the query.
In addition, our model for contextual search is multilingual and you can, therefore, search in English and get results in other local languages or visa versa. This will enable you to search across studies and create insights across markets.
P.S Soon you will be able to click the nuggets and find the most contextually similar nuggets to that one, in order to help you create your insights!