Chapter 2. From plain retrieval to text generation
Chapter 3 from Deep Learning for Search by Tommaso Teofili
- Expanding queries
- Using search logs to build training data
- Understanding recurrent neural networks
- Generating alternative queries with RNNs
In the early days of the internet and search engines (late 1990s), people only searched for keywords. Users might have typed “movie zemeckis future” to find information about the movie Back to the Future, directed by Robert Zemeckis. Although search engines have evolved, and today we can type queries using natural language, many users still rely on keywords when searching. For these users, it would be advantageous if the search engine could generate a proper query based on the keywords they type: for example, taking “movie Zemeckis future” and generating “Back to the Future by Robert Zemeckis.” Let’s call the generated query an alternative query, in the sense that it’s an alternative (text) representation of the information need expressed by the user.