This is fascinating, we started to experiment with the completion suggester few months ago. The first goal was to increase recall and use the ability to activate fuzzy lookups to handle small typos. It became clear that scoring was a critical part of this feature. Some prefixes are already very ambiguous (mar, cha, list ...) and enabling fuzziness does not help here. We tried to implement a score based on the data currently available (size, incoming_links, templates...) but this score is kind of "bigger is better". This is why we were interested in pageviews to add "popularity" in the score. Thanks for sharing this tool it is very helpful to have a quick look at how it would look like. I still don't know if pageviews can be the only score component or if we should compose with other factors like "quality", "authority". My concerns with pageviews are : - we certainly have outliers (caused by 3rd party tools/bots ...) - what's the coverage of pageviews: i.e. in one month how many pages get 0 pageviews? Quality: we have a set of templates that are already used to flag good/featured articles. Cirrus uses it on enwiki only, I'd really like to extend this to other wikis. I'm also very interested in the tool behind http://ores.wmflabs.org/scores/enwiki/wp10/?revids=686575075 . Authority/Centrality: Erik ran an experiment with a pagerank like algorithm and it shows very interesting results. I'm wondering if this approach can work, I tend to think that by using only one factor (pageviews) we can have both very long tails with 1 or 0 pageview and big outliers caused by new bots/tools we failed to detect. Using other factors not related to pageviews might help to mitigate these problems. So the question about normalization is also interesting to compute a composite score between 3 different components. For the question about weighting over time, I think you detailed the problem very well. It really depends on what we want to do here, near-real-time (12h or 24h) can lead to weird behaviors and will only work for very popular wikis. Concerning your experiment, do you plan to activate fuzzy search? On our side it was a bit difficult, completion suggester is still incomplete. Fuzzy results are not discounted so we had to workaround this problem with client-side rescoring. Thank you! Le 14/11/2015 00:10, Greg Lindahl a écrit :