An expressive query language for product recommender systems

We argue that existing approaches to the construction of content-based Product Recommender Systems (Filter-Based Retrieval and Similarity-Based Retrieval) use inadequately expressive query languages. We introduce a new approach, which we call Order-Based Retrieval. We define and exemplify the six operators that constitute its query language. We show how these operators can better support the elicitation of both the customer's initial requirements and refinements to the initial requirements.