One way to improve inferences on sensor data is to tune the algorithms through a time-consuming offline procedure. A less expensive, and potentially more accurate method is to use an online procedure based on feedback from users, who often know best what the data means to them. We present a method for user-assisted location inference based on 802.11b wireless signal strengths. A user 'corrects' system geolocations by clicking on a map, recording a 'virtual access point' (VAP) at the selected point for future inferences. A best VAP is selected using simple criteria, including the VAP's creator. This permits using other's VAPs while getting their own if one exists, capturing user-specific behavior. The system is also self-maintaining with respect to changing access point deployments. Indoor experiments show very good accuracy for this simple method.