Ask HN: Tips for LAMP app recommendation engine solution

I was asked by a friendly company to improve their current product recommendation system which is currently a couple of complex SQL queries using fulltext search that match similar products based on title, description and tags (a single comma separated field). The new system must also take into account the click rate of a product (in regard of similar ones) when it's being recommended, meaning that when products B and C are presented as similar products of A and the user clicks on B, it's click rate in regard of A is increased and may influence the next recommendation of similar products of A which orders the result by similarity and click rate in relation to the displayed product. As a note, my customer is also interested in obtaining for example 8 products from this set plus 2 more with a low click rate to give them a chance of obtaining a higher click rate. It's also required to be able to configure the weights of the "variables", for example, 0.5clickRate+0.3description and so on. Instead of starting to hack a custom solution i've been looking for recommendation engines in PHP (the database is mysql) but haven't found much. I'm also aware of Apache Mahout, i could suggest the use of Mahout or a similar java engine as a webservice but i know the customer is very much prone to a "pure" PHP solution, as their applications are very basic stack-wise. Additionally i don't have experience with Mahout or recommendation engines in general, so i'm currently not aware how they manage the "related click rate" feature. My questions are: - Any suggestions? - Have i missed any tool? Thanks