In enterprise search scenarios information needs are quite diverse. If users know exactly which items they are looking for, they need support in known-item searches. But often information needs are vague and unclear, which means that users cannot explicitly define the search criteria that specify their search request. In these cases, exploratory search approaches are necessary to support users in interactively refining their search queries. Our approach for a retrieval system for complex search situations can be characterized by its four constituent parts: The approach deals with the heterogeneity of potential target objects when performing a search considering multiple artifact layers (e. g. projects, products, persons, and documents). The basic search paradigm applied is faceted search which is well-suited for exploratory interactive retrieval. To cope with result sets of different granularity, we include ranking facilities based on facet values as well as Query-by-Example (QbE) functionalities. Users can easily state their priorities visually by using preference functions. Finally, parallel coordinates (PC) are used to visualize the characteristics and dependencies of (intermediate) results in order to provide users with a deeper understanding of the data under investigation. These four cornerstones of our approach are reflected in the acronym LFRP-search (Multi-<u>L</u>ayer <u>F</u>aceted Search with <u>R</u>anking using <u>P</u>arallel <u>C</u>oordinates). The main contribution of this paper is the semi-formal description of the query options.